Author: "Christian Hamilton-Craig" / Topic: medicine - Searchworks@Jio Institute Digital Library Search Results

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197 results on '"Christian Hamilton-Craig"'

1. Examining the Potential for Coronary Artery Calcium (CAC) Scoring for Individuals at Low Cardiovascular Risk

Author: Girish Dwivedi, Gemma A. Figtree, David Playford, and Christian Hamilton-Craig
Subjects: Pulmonary and Respiratory Medicine, medicine.medical_specialty, Computed tomography, Coronary Artery Disease, Coronary Angiography, Age and sex, Risk Assessment, Asymptomatic, Risk Factors, Internal medicine, medicine, Humans, cardiovascular diseases, Myocardial infarction, Risk factor, Vascular Calcification, Cause of death, medicine.diagnostic_test, business.industry, nutritional and metabolic diseases, medicine.disease, Coronary Vessels, Coronary artery calcium, Cardiovascular Diseases, Heart Disease Risk Factors, Cardiology, Calcium, medicine.symptom, Cardiology and Cardiovascular Medicine, business
Abstract: Atherosclerosis is the commonest cause of death in Australia. Cardiovascular (CV) risk calculators have an important role in preventative cardiology, although they are are strongly age-dependent and designed to identify individuals at high risk of an imminent event. The imprecision around “intermediate” or “low” risk generates therapeutic uncertainty, and a significant proportion of patients presenting with myocardial infarction come from these groups, often with no warning. This highlights a conundrum: “Low” risk does not mean “no” risk. A fresh approach may be required to address the clinical conundrum around CV preventative approaches in non-high-risk individuals. While probabilistic calculators do not measure atherosclerosis, calculation of Coronary Artery Calcium (CAC) scores by low-dose computed tomography (CT) can provide a snapshot of atherosclerotic burden. In intermediate-risk individuals, CAC is well-established as an aid to CV risk prediction. Although CAC scoring in low-risk asymptomatic people may be considered controversial, CAC has emerged as the single best predictor of CV events in asymptomatic individuals, independent of traditional risk factor calculators. Therefore, apart from the contribution of age and sex, the somewhat arbitrary distinction between “intermediate” and “low” CV risk using probabilistic calculators may need to be reconsidered. A zero CAC score has a very low future event rate and non-zero CAC scores are associated with a progressive, graded increase in risk as the CAC score rises. In this review, we examine the evidence for CAC screening in low-risk individuals, and propose more widespread use of CAC using simple new model intended to enhance established CV risk prediction equations.
Published: 2021

2. Electrophysiologic and imaging evidence for an occult myopathic substrate in patients with idiopathic ventricular arrhythmias

Author: Adam Lee, Haris M. Haqqani, Wendy Strugnell, Christian Hamilton-Craig, and Eric Vittinghoff
Subjects: medicine.medical_specialty, Heart Ventricles, medicine.medical_treatment, Cardiomyopathy, 030204 cardiovascular system & hematology, Ventricular Dysfunction, Left, 03 medical and health sciences, 0302 clinical medicine, Cardiac magnetic resonance imaging, Fibrosis, Internal medicine, Humans, Medicine, In patient, 030212 general & internal medicine, Subclinical infection, medicine.diagnostic_test, business.industry, Arrhythmias, Cardiac, medicine.disease, Ablation, Occult, Catheter Ablation, Tachycardia, Ventricular, Cardiology, Supraventricular tachycardia, Cardiomyopathies, Cardiology and Cardiovascular Medicine, business
Abstract: Background: Idiopathic VA are traditionally considered benign, although occasional patients develop an ectopy-mediated cardiomyopathy (EMC). It is unclear whether patients with idiopathic VA in the absence of left ventricular (LV) dysfunction harbor a subclinical cardiomyopathy. We aim to assess for cardiomyopathic substrate in patients with idiopathic ventricular arrhythmias (VA) using imaging and electrophysiologic markers of early fibrosis. Methods: Cardiac magnetic resonance (CMR) imaging and ventricular electroanatomic mapping was performed in 3 groups: patients undergoing ablation for idiopathic VA without (Group 1, n = 17) and with LV dysfunction (Group 2 [presumed EMC], n = 12) plus a control group undergoing ablation of supraventricular tachycardia (Group 3, n = 16). Global LV strain, T1 mapping and extended electrogram (EGM) characteristics were compared. Results: Global strain was impaired in patients with presumed EMC (Group 2, p < 0.001). Native T1 times did not differ between groups, however patients in both idiopathic VA groups (Groups 1 and 2) had shorter post-contrast T1 times at 8 min compared to SVT controls (Group 3, p = 0.04). Similarly, the duration of the bipolar EGM was subtly prolonged in both Group 1 and 2 compared to Group 3 (p = 0.002). There were no between group differences in unipolar or bipolar voltage, the no. of bipolar EGM deflections or the maximal unipolar EGM dV/dt. Conclusion: Patients with idiopathic VAs and apparently structurally normal hearts may have subtle CMR and electrophysiologic changes similar in magnitude to that seen in frank presumed EMC, possibly suggestive of an occult cardiomyopathic process.
Published: 2021

3. 7-Tesla Functional Cardiovascular MR Using Vectorcardiographic Triggering—Overcoming the Magnetohydrodynamic Effect

Author: Sabine Fletcher, William Crawford, Aiman Al Najjar, Graham J. Galloway, Markus Barth, Kieran O'Brien, Christian Hamilton-Craig, and Daniel Staeb
Subjects: Image quality, Phase contrast microscopy, Cardiac Volume, Computer applications to medicine. Medical informatics, R858-859.7, 030204 cardiovascular system & hematology, Ventricular Function, Left, Article, 030218 nuclear medicine & medical imaging, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, medicine, 7 tesla MRI, Humans, magnetic resonance imaging, Radiology, Nuclear Medicine and imaging, cardiovascular diseases, Ejection fraction, medicine.diagnostic_test, business.industry, Magnetic resonance scanner, Magnetic resonance imaging, Stroke Volume, Ecg triggering, Vascular flow, cardiology, Ventricular Function, Right, business, Nuclear medicine, Artifacts, MRI scans
Abstract: Objective: Ultra-high-field B0 ≥ 7 tesla (7T) cardiovascular magnetic resonance (CMR) offers increased resolution. However, electrocardiogram (ECG) gating is impacted by the magneto-hydrodynamic effect distorting the ECG trace. We explored the technical feasibility of a 7T magnetic resonance scanner using an ECG trigger learning algorithm to quantitatively assess cardiac volumes and vascular flow. Methods: 7T scans were performed on 10 healthy volunteers on a whole-body research MRI MR scanner (Siemens Healthineers, Erlangen, Germany) with 8 channel Tx/32 channels Rx cardiac coils (MRI Tools GmbH, Berlin, Germany). Vectorcardiogram ECG was performed using a learning phase outside of the magnetic field, with a trigger algorithm overcoming severe ECG signal distortions. Vectorcardiograms were quantitatively analyzed for false negative and false positive events. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented spoiled gradient echo, and 2D phase contrast flow imaging. Artefacts were assessed using a semi-quantitative scale. Results: 7T CMR scans were acquired in all patients (100%) using the vectorcardiogram learning method. 3,142 R-waves were quantitatively analyzed, yielding sensitivity of 97.6% and specificity of 98.7%. Mean image quality score was 0.9, sufficient to quantitate both cardiac volumes, ejection fraction, and aortic and pulmonary blood flow. Mean left ventricular ejection fraction was 56.4%, right ventricular ejection fraction was 51.4%. Conclusion: Reliable cardiac ECG triggering is feasible in healthy volunteers at 7T utilizing a state-of-the-art three-lead trigger device despite signal distortion from the magnetohydrodynamic effect. This provides sufficient image quality for quantitative analysis. Other ultra-high-field imaging applications such as human brain functional MRI with physiologic noise correction may benefit from this method of ECG triggering.
Published: 2021

4. Society for Cardiovascular Magnetic Resonance 2019 Case of the Week series

Author: Ahmed Heny, John F. Younger, Arushi Dhar, J. Michael Kennen, Vinayak Hedge, Omnia Mohammed, Anmar Kanaa'N, Bryant M. Baldwin, Shane Joseph, Maha Taher, Dominique de Waard, Santokh Dhillon, Madhusudan Ganigara, Yassar Nabeel, Jason N. Johnson, Jafar Alzubi, Christian Hamilton-Craig, Rajiv R. Shah, Ahmed Hamdy, Ahmad Jabri, Aoife Sweeney, Chris Hammet, Joseph A. Lahorra, Nilanjana Misra, Arun Dahiya, Sameh Khalil, Taher Moustafa, Sara Ragab, Ashish Aneja, Christopher Malozzi, Michael V. Cohen, Sylvia S. M. Chen, Maria S. Figarola, Charles Chao, Julia Kar, David Horne, Kurian Pannikottu, Shimaa Abdelrahman Ahmed, V. S. Katikireddi, Allan J. Wesley, Anam Chowdhry, and M. Farhan Nasser
Subjects: Cardiac tumor, medicine.medical_specialty, lcsh:Diseases of the circulatory (Cardiovascular) system, Cardiomyopathy, media_common.quotation_subject, Antineoplastic Agents, Review, Disease, Churg-Strauss Syndrome, 030204 cardiovascular system & hematology, Ventricular Function, Left, 030218 nuclear medicine & medical imaging, Diagnosis, Differential, Heart Neoplasms, Ventricular Dysfunction, Left, Young Adult, 03 medical and health sciences, Presentation, 0302 clinical medicine, Predictive Value of Tests, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Medical physics, Cardiac Tumors, Web site, Angiology, media_common, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Thrombosis, Magnetic resonance imaging, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Cardiotoxicity, lcsh:RC666-701, Female, Cardiology and Cardiovascular Medicine, business, MRI, Eosinophilic granulomatosis
Abstract: The Society for Cardiovascular Magnetic Resonance (SCMR) is an international society focused on the research, education, and clinical application of cardiovascular magnetic resonance (CMR). The SCMR web site (https://www.scmr.org) hosts a case series designed to present case reports demonstrating the unique attributes of CMR in the diagnosis or management of cardiovascular disease. Each clinical presentation is followed by a brief discussion of the disease and unique role of CMR in disease diagnosis or management guidance. By nature, some of these are somewhat esoteric, but all are instructive. In this publication, we provide a digital archive of the 2019 Case of the Week series as a means of further enhancing the education of those interested in CMR and as a means of more readily identifying these cases using a PubMed or similar search engine.
Published: 2021

5. International Impact of COVID-19 on the Diagnosis of Heart Disease

Author: Einstein, A. J., Shaw, L. J., Hirschfeld, C., Williams, M. C., Villines, T. C., Better, N., Vitola, J. V., Cerci, R., Dorbala, S., Raggi, P., Choi, A. D., Lu, B., Sinitsyn, V., Sergienko, V., Kudo, T., Norgaard, B. L., Maurovich-Horvat, P., Campisi, R., Milan, E., Louw, L., Allam, A. H., Bhatia, M., Malkovskiy, E., Goebel, B., Cohen, Y., Randazzo, M., Narula, J., Pascual, T. N. B., Pynda, Y., Dondi, M., Gerd Hinterleitner, Paez D., Yao, Lu, Olga, Morozova, Zhuoran, Xu, Juan, Lopez-Mattei, Purvi, Parwani, Mohammad Nawaz Nasery, Artan, Goda, Ervina, Shirka, Rabie, Benlabgaa, Salah, Bouyoucef, Abdelkader, Medjahedi, Qais, Nailli, Mariela, Agolti, Roberto Nicolas Aguero, Maria Del Carmen Alak, Lucia Graciela Alberguina, Guillermo, Arroñada, Andrea, Astesiano, Alfredo, Astesiano, Carolina Bas Norton, Pablo, Benteo, Juan, Blanco, Juan Manuel Bonelli, Jose Javier Bustos, Raul, Cabrejas, Jorge, Cachero, Alejandro, Canderoli, Silvia, Carames, Patrícia, Carrascosa, Ricardo, Castro, Oscar, Cendoya, Luciano Martin Cognigni, Carlos, Collaud, Claudia, Cortes, Javier, Courtis, Daniel, Cragnolino, Mariana, Daicz, Alejandro De La Vega, Silvia Teresa De Maria, Horacio Del Riego, Fernando, Dettori, Alejandro, Deviggiano, Laura, Dragonetti, Mario, Embon, Ruben Emilio Enriquez, Jorge, Ensinas, Fernando, Faccio, Adolfo, Facello, Diego, Garofalo, Ricardo, Geronazzo, Natalia, Gonza, Lucas, Gutierrez, Miguel Angel Guzzo, Victor, Hasbani, Melina, Huerin, Victor, Jäger, Julio Manuel Lewkowicz, Maria Nieves, A López De Munaín, Jose Maria Lotti, Alejandra, Marquez, Osvaldo, Masoli, Edgardo, Mastrovito, Matias, Mayoraz, Graciela Eva Melado, Anibal, Mele, Maria Fernanda Merani, Alejandro Horacio Meretta, Susana, Molteni, Marcos, Montecinos, Eduardo, Noguera, Carlos, Novoa, Claudio Pereyra Sueldo, Sebastian Perez Ascani, Pablo, Pollono, Maria Paula Pujol, Alejandro, Radzinschi, Gustavo, Raimondi, Marcela, Redruello, Marina, Rodríguez, Matías, Rodríguez, Romina Lorena Romero, Arturo Romero Acuña, Federico, Rovaletti, Lucas San Miguel, Lucrecia, Solari, Bruno, Strada, Sonia, Traverso, Sonia Simona Traverzo, Maria Del Huerto Velazquez Espeche, Juan Sebastian Weihmuller, Juan, Wolcan, Susana, Zeffiro, Mari, Sakanyan, Scott, Beuzeville, Raef, Boktor, Patrick, Butler, Jennifer, Calcott, Loretta, Carr, Virgil, Chan, Charles, Chao, Woon, Chong, Mark, Dobson, D'Arne, Downie, Girish, Dwivedi, Barry, Elison, Jean, Engela, Roslyn, Francis, Anand, Gaikwad, Ashok Gangasandra Basavaraj, Bruce, Goodwin, Robert, Greenough, Christian, Hamilton-Craig, Victar, Hsieh, Subodh, Joshi, Karin, Lederer, Kenneth, Lee, Joseph, Lee, John, Magnussen, Nghi, Mai, Gordon, Mander, Fiona, Murton, Dee, Nandurkar, Johanne, Neill, Edward, O'Rourke, Patricia, O'Sullivan, George, Pandos, Kunthi, Pathmaraj, Alexander, Pitman, Rohan, Poulter, Manuja, Premaratne, David, Prior, Lloyd, Ridley, Natalie, Rutherford, Hamid, Salehi, Connor, Saunders, Luke, Scarlett, Sujith, Seneviratne, Deepa, Shetty, Ganesh, Shrestha, Jonathan, Shulman, Vijay, Solanki, Tony, Stanton, Murch, Stuart, Michael, Stubbs, Ian, Swainson, Kim, Taubman, Andrew, Taylor, Paul, Thomas, Steven, Unger, Anthony, Upton, Shankar, Vamadevan, William Van Gaal, Johan, Verjans, Demetrius, Voutnis, Victor, Wayne, Peter, Wilson, David, Wong, Kirby, Wong, John, Younger, Gudrun, Feuchtner, Siroos, Mirzaei, Konrad, Weiss, Natallia, Maroz-Vadalazhskaya, Olivier, Gheysens, Filip, Homans, Rodrigo, Moreno-Reyes, Agnès, Pasquet, Veronique, Roelants, Caroline, M Van De Heyning, Raúl Araujo Ríos, Valentina, Soldat-Stankovic, Sinisa, Stankovic, Maria Helena Albernaz Siqueira, Augusto, Almeida, Paulo Henrique Alves Togni, Jose Henrique Andrade, Luciana, Andrade, Carlos, Anselmi, Roberta, Araújo, Guilherme, Azevedo, Sabbrina, Bezerra, Rodrigo, Biancardi, Gabriel Blacher Grossman, Simone, Brandão, Diego Bromfman Pianta, Lara, Carreira, Bruno, Castro, Tien, Chang, Fernando Cunali Jr, Roberto, Cury, Roberto, Dantas, Fernando de Amorim Fernandes, Andrea De Lorenzo, Robson De Macedo Filho, Fernanda, Erthal, Fabio, Fernandes, Juliano, Fernandes, Thiago Ferreira De Souza, Wilson Furlan Alves, Bruno, Ghini, Luiz, Goncalves, Ilan, Gottlieb, Marcelo, Hadlich, Vinícius, Kameoka, Ronaldo, Lima, Adna, Lima, Rafael Willain Lopes, Ricardo Machado, E Silva, Tiago, Magalhães, Fábio Martins Silva, Luiz Eduardo Mastrocola, Fábio, Medeiros, José Claudio Meneghetti, Vania, Naue, Danilo, Naves, Roberto, Nolasco, Cesar, Nomura, Joao Bruno Oliveira, Eduardo, Paixao, Filipe Penna De Carvalho, Ibraim, Pinto, Priscila, Possetti, Mayra, Quinta, Rodrigo Rizzo Nogueira Ramos, Ricardo, Rocha, Alfredo, Rodrigues, Carlos, Rodrigues, Leila, Romantini, Adelina, Sanches, Sara, Santana, Leonardo Sara da Silva, Paulo, Schvartzman, Cristina Sebastião Matushita, Tiago, Senra, Afonso, Shiozaki, Maria Eduarda Menezes de Siqueira, Cristiano, Siqueira, Paola, Smanio, Carlos Eduardo Soares, José Soares Junior, Marcio Sommer Bittencourt, Bernardo, Spiro, Cláudio Tinoco Mesquita, Jorge, Torreao, Rafael, Torres, Marly, Uellendahl, Guilherme Urpia Monte, Otávia, Veríssimo, Estevan Vieira Cabeda, Felipe Villela Pedras, Roberto, Waltrick, Marcello, Zapparoli, Hamid, Naseer, Marina, Garcheva-Tsacheva, Irena, Kostadinova, Youdaline, Theng, Gad, Abikhzer, Rene, Barette, Benjamin, Chow, Dominique, Dabreo, Matthias, Friedrich, Ria, Garg, Mohammed Nassoh Hafez, Chris, Johnson, Marla, Kiess, Jonathon, Leipsic, Eugene, Leung, Robert, Miller, Anastasia, Oikonomou, Stephan, Probst, Idan, Roifman, Gary, Small, Vikas, Tandon, Adwait, Trivedi, James, White, Katherine, Zukotynski, Jose, Canessa, Gabriel Castro Muñoz, Carmen, Concha, Pablo, Hidalgo, Cesar, Lovera, Teresa, Massardo, Luis Salazar Vargas, Pedro, Abad, Harold, Arturo, Sandra, Ayala, Luis, Benitez, Alberto, Cadena, Carlos, Caicedo, Antonio Calderón Moncayo, Sharon, Gomez, Claudia, T Gutierrez Villamil, Claudia, Jaimes, Juan Luis Londoño Blair, Luz, Pabon, Mauricio, Pineda, Juan Carlos Rojas, Diego, Ruiz, Manuel Valencia Escobar, Andres, Vasquez, Damiana, Vergel, Alejandro, Zuluaga, Isabel Berrocal Gamboa, Gabriel, Castro, Ulises, González, Ana, Baric, Tonci, Batinic, Maja, Franceschi, Maja Hrabak Paar, Mladen, Jukic, Petar, Medakovic, Viktor, Persic, Marina, Prpic, Ante, Punda, Juan Felipe Batista, Juan Manuel Gómez Lauchy, Yamile Marcos Gutierrez, Rayner, Menéndez, Amalia, Peix, Luis, Rochela, Christoforos, Panagidis, Ioannis, Petrou, Vaclav, Engelmann, Milan, Kaminek, Vladimír, Kincl, Otto, Lang, Milan, Simanek, Jawdat, Abdulla, Morten, Bøttcher, Mette, Christensen, Lars Christian Gormsen, Philip, Hasbak, Søren, Hess, Paw, Holdgaard, Allan, Johansen, Kasper, Kyhl, Kristian Altern Øvrehus, Niels Peter Rønnow Sand, Rolf, Steffensen, Anders, Thomassen, Zerahn, Bo, Alfredo, Perez, Giovanni Alejandro Escorza Velez, Mayra Sanchez Velez, Islam Shawky Abdel Aziz, Mahasen, Abougabal, Taghreed, Ahmed, Ahmed, Asfour, Mona, Hassan, Alia, Hassan, Ahmed, Ibrahim, Sameh, Kaffas, Ahmed, Kandeel, Mohamed Mandour Ali, Ahmad, Mansy, Hany, Maurice, Sherif, Nabil, Mahmoud, Shaaban, Ana Camila Flores, Anne, Poksi, Juhani, Knuuti, Velipekka, Kokkonen, Martti, Larikka, Valtteri, Uusitalo, Matthieu, Bailly, Samuel, Burg, Jean-François, Deux, Vincent, Habouzit, Fabien, Hyafil, Olivier, Lairez, Franck, Proffit, Hamza, Regaieg, Laure, Sarda-Mantel, Vania, Tacher, Roman, P Schneider, Harold, Ayetey, George, Angelidis, Aikaterini, Archontaki, Sofia, Chatziioannou, Ioannis, Datseris, Christina, Fragkaki, Panagiotis, Georgoulias, Sophia, Koukouraki, Maria, Koutelou, Eleni, Kyrozi, Evangelos, Repasos, Petros, Stavrou, Pipitsa, Valsamaki, Carla, Gonzalez, Goleat, Gutierrez, Alejandro, Maldonado, Klara, Buga, Ildiko, Garai, Erzsébet, Schmidt, Balint, Szilveszter, Edit, Várady, Nilesh, Banthia, Jinendra Kumar Bhagat, Rishi, Bhargava, Vivek, Bhat, Partha, Choudhury, Vijay Sai Chowdekar, Aparna, Irodi, Shashank, Jain, Elizabeth, Joseph, Sukriti, Kumar, Girijanandan, Mahapatra, Deepanjan, Mitra, Bhagwant Rai Mittal, Ahmad, Ozair, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Patel, Sudhir, Saxena, Shantanu, Sengupta, Santosh, Singh, Bhanupriya, Singh, Ashwani, Sood, Atul, Verma, Erwin, Affandi, Padma Savenadia Alam, Edison, Edison, Gani, Gunawan, Habusari, Hapkido, Basuki, Hidayat, Aulia, Huda, Anggoro Praja Mukti, Djoko, Prawiro, Erwin Affandi Soeriadi, Hilman, Syawaluddin, Amjed, Albadr, Majid, Assadi, Farshad, Emami, Golnaz, Houshmand, Majid, Maleki, Maryam Tajik Rostami, Seyed Rasoul Zakavi, Eed Abu Zaid, Svetlana, Agranovich, Yoav, Arnson, Rachel, Bar-Shalom, Alex, Frenkel, Galit, Knafo, Rachel, Lugassi, Israel Shlomo Maor Moalem, Maya, Mor, Noam, Muskal, Sara, Ranser, Aryeh, Shalev, Domenico, Albano, Pierpaolo, Alongi, Gaspare, Arnone, Elisa, Bagatin, Sergio, Baldari, Matteo, Bauckneht, Paolo, Bertelli, Francesco, Bianco, Rachele, Bonfiglioli, Roberto, Boni, Andrea, Bruno, Isabella, Bruno, Elena, Busnardo, Elena, Califaretti, Luca, Camoni, Aldo, Carnevale, Roberta, Casoni, Armando Ugo Cavallo, Giorgio, Cavenaghi, Franca, Chierichetti, Marcello, Chiocchi, Corrado, Cittanti, Mauro, Colletta, Umberto, Conti, Alberto, Cossu, Alberto, Cuocolo, Marco, Cuzzocrea, Maria Luisa De Rimini, Giuseppe De Vincentis, Eleonora Del Giudice, Alberico Del Torto, DELLA TOMMASINA, Veronica, Rexhep, Durmo, Erba, PAOLA ANNA, Laura, Evangelista, Riccardo, Faletti, Evelina, Faragasso, Mohsen, Farsad, Paola, Ferro, Luigia, Florimonte, Viviana, Frantellizzi, Fabio Massimo Fringuelli, Marco, Gatti, Angela, Gaudiano, Alessia, Gimelli, Raffaele, Giubbini, Francesca, Giuffrida, Salvatore, Ialuna, Riccardo, Laudicella, Lucia, Leccisotti, Lucia, Leva, Liga, Riccardo, Carlo, Liguori, Giampiero, Longo, Margherita, Maffione, Maria Elisabetta Mancini, Claudio, Marcassa, Barbara, Nardi, Sara, Pacella, Giovanna, Pepe, Gianluca, Pontone, Sabina, Pulizzi, Natale, Quartuccio, Lucia, Rampin, Fabrizio, Ricci, Pierluigi, Rossini, Giuseppe, Rubini, Vincenzo, Russo, Gian Mauro Sacchetti, Gianmario, Sambuceti, Massimo, Scarano, Roberto, Sciagrà, Massimiliano, Sperandio, Antonella, Stefanelli, Guido, Ventroni, Stefania, Zoboli, Dainia, Baugh, Duane, Chambers, Ernest, Madu, Felix, Nunura, Hiroshi, Asano, Chimura Misato Chimura, Shinichiro, Fujimoto, Koichiro, Fujisue, Tomohisa, Fukunaga, Yoshimitsu, Fukushima, Kae, Fukuyama, Jun, Hashimoto, Yasutaka, Ichikawa, Nobuo, Iguchi, Masamichi, Imai, Anri, Inaki, Hayato, Ishimura, Satoshi, Isobe, Toshiaki, Kadokami, Takao, Kato, Shinichiro, Kumita, Hirotaka, Maruno, Hiroyuki, Mataki, Masao, Miyagawa, Ryota, Morimoto, Masao, Moroi, Shigeki, Nagamachi, Kenichi, Nakajima, Tomoaki, Nakata, Ryo, Nakazato, Mamoru, Nanasato, Masanao, Naya, Takashi, Norikane, Yasutoshi, Ohta, Satoshi, Okayama, Atsutaka, Okizaki, Yoichi, Otomi, Hideki, Otsuka, Masaki, Saito, Sakata Yasushi Sakata, Masayoshi, Sarai, Daisuke, Sato, Shinya, Shiraishi, Yoshinobu, Suwa, Kentaro, Takanami, Kazuya, Takehana, Junichi, Taki, Nagara, Tamaki, Yasuyo, Taniguchi, Hiroki, Teragawa, Nobuo, Tomizawa, Kenichi, Tsujita, Kyoko, Umeji, Yasushi, Wakabayashi, Shinichiro, Yamada, Shinya, Yamazaki, Tatsuya, Yoneyama, Mohammad, Rawashdeh, Daultai, Batyrkhanov, Tairkhan, Dautov, Khalid, Makhdomi, Kevin, Ombati, Faridah, Alkandari, Masoud, Garashi, Tchoyoson Lim Coie, Sonexay, Rajvong, Artem, Kalinin, Marika, Kalnina, Mohamad, Haidar, Renata, Komiagiene, Giedre, Kviecinskiene, Mindaugas, Mataciunas, Donatas, Vajauskas, Christian, Picard, Noor Khairiah, A Karim, Luise, Reichmuth, Anthony, Samuel, Mohammad Aaftaab Allarakha, Ambedhkar Shantaram Naojee, Erick, Alexanderson-Rosas, Erika, Barragan, Alejandro Becerril González-Montecinos, Manuel, Cabada, Daniel Calderon Rodriguez, Isabel, Carvajal-Juarez, Violeta, Cortés, Filiberto, Cortés, Erasmo De La Peña, Manlio, Gama-Moreno, Luis, González, Nelsy Gonzalez Ramírez, Moisés, Jiménez-Santos, Luis, Matos, Edgar, Monroy, Martha, Morelos, Mario, Ornelas, Jose Alberto Ortga Ramirez, Andrés, Preciado-Anaya, Óscar Ulises Preciado-Gutiérrez, Adriana Puente Barragan, Sandra Graciela Rosales Uvera, Sigelinda, Sandoval, Miguel Santaularia Tomas, Lilia, M Sierra-Galan, Silvia, Siu, Enrique, Vallejo, Mario, Valles, Marc, Faraggi, Erdenechimeg, Sereegotov, Srdja, Ilic, Nozha, Ben-Rais, Nadia Ismaili Alaoui, Sara, Taleb, Khin Pa Pa Myo, Phyo Si Thu, Ram Kumar Ghimire, Bijoy, Rajbanshi, Peter, Barneveld, Andor, Glaudemans, Jesse, Habets, Klaas Pieter Koopmans, Jeroen, Manders, Stefan, Pool, Arthur, Scholte, Asbjørn, Scholtens, Riemer, Slart, Paul, Thimister, Erik-Jan Van Asperen, Niels, Veltman, Derk, Verschure, Nils, Wagenaar, John, Edmond, Chris, Ellis, Kerryanne, Johnson, Ross, Keenan, Shaw Hua Anthony Kueh, Christopher, Occleshaw, Alexander, Sasse, Andrew, To, Niels Van Pelt, Calum, Young, Teresa, Cuadra, Hector Bladimir Roque Vanegas, Idrissa Adamou Soli, Djibrillou Moussa Issoufou, Tolulope, Ayodele, Chibuzo, Madu, Yetunde, Onimode, Elen, Efros-Monsen, Signe Helene Forsdahl, Jenni-Mari Hildre Dimmen, Arve, Jørgensen, Isabel, Krohn, Pål, Løvhaugen, Anders Tjellaug Bråten, Humoud Al Dhuhli, Faiza Al Kindi, Naeema, Al-Bulushi, Zabah, Jawa, Naima, Tag, Muhammad Shehzad Afzal, Shazia, Fatima, Muhammad Numair Younis, Musab, Riaz, Mohammad, Saadullah, Yariela, Herrera, Dora, Lenturut-Katal, Manuel Castillo Vázquez, José, Ortellado, Afroza, Akhter, Dianbo, Cao, Stephen, Cheung, Dai, Xu, Lianggeng, Gong, Dan, Han, Yang, Hou, Caiying, Li, Tao, Li, Dong, Li, Sijin, Li, Jinkang, Liu, Hui, Liu, Ming Yen Ng, Kai, Sun, Gongshun, Tang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wang, Jiang, Wu, Zhifang, Wu, Liming, Xia, Jiangxi, Xiao, Lei, Xu, Youyou, Yang, Yin, Wu, Jianqun, Yu, Yuan, Li, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhang, Zhu, Li, Ana, Alfaro, Paz, Abrihan, Asela, Barroso, Eric, Cruz, Marie Rhiamar Gomez, Vincent Peter Magboo, John Michael Medina, Jerry, Obaldo, Davidson, Pastrana, Christian Michael Pawhay, Alvin, Quinon, Jeanelle Margareth Tang, Bettina, Tecson, Kristine Joy Uson, Mila, Uy, Magdalena, Kostkiewicz, Jolanta, Kunikowska, Nuno, Bettencourt, Guilhermina, Cantinho, Antonio, Ferreira, Ghulam, Syed, Samer, Arnous, Said, Atyani, Angela, Byrne, Tadhg, Gleeson, David, Kerins, Conor, Meehan, David, Murphy, Mark, Murphy, John, Murray, Julie, O'Brien, Ji-In, Bang, Henry, Bom, Sang-Geon, Cho, Chae Moon Hong, Su Jin Jang, Yong Hyu Jeong, Won Jun Kang, Ji-Young, Kim, Jaetae, Lee, Chang Kyeong Namgung, Young, So, Kyoung Sook Won, Venjamin, Majstorov, Marija, Vavlukis, Barbara Gužic Salobir, Monika, Štalc, Theodora, Benedek, Imre, Benedek, Raluca, Mititelu, Claudiu Adrian Stan, Alexey, Ansheles, Olga, Dariy, Olga, Drozdova, Nina, Gagarina, Vsevolod Milyevich Gulyaev, Irina, Itskovich, Anatoly, Karalkin, Alexander, Kokov, Ekaterina, Migunova, Viktor, Pospelov, Daria, Ryzhkova, Guzaliya, Saifullina, Svetlana, Sazonova, Irina, Shurupova, Tatjana, Trifonova, Wladimir Yurievich Ussov, Margarita, Vakhromeeva, Nailya, Valiullina, Konstantin, Zavadovsky, Kirill, Zhuravlev, Mirvat, Alasnag, Subhani, Okarvi, Dragana Sobic Saranovic, Felix, Keng, Jia Hao Jason See, Ramkumar, Sekar, Min Sen Yew, Andrej, Vondrak, Shereen, Bejai, George, Bennie, Ria, Bester, Gerrit, Engelbrecht, Osayande, Evbuomwan, Harlem, Gongxeka, Magritha Jv Vuuren, Mitchell, Kaplan, Purbhoo, Khushica, Hoosen, Lakhi, Nico, Malan, Katarina, Milos, Moshe, Modiselle, Stuart, More, Mathava, Naidoo, Leonie, Scholtz, Mboyo, Vangu, Santiago, Aguadé-Bruix, Isabel, Blanco, Antonio, Cabrera, Alicia, Camarero, Irene, Casáns-Tormo, Hug, Cuellar-Calabria, Albert, Flotats, Maria Eugenia Fuentes Cañamero, María Elia García, Amelia, Jimenez-Heffernan, Rubén, Leta, Javier Lopez Diaz, Luis, Lumbreras, Juan Javier Marquez-Cabeza, Francisco, Martin, Anxo Martinez de Alegria, Francisco, Medina, Maria Pedrera Canal, Virginia, Peiro, Virginia, Pubul-Nuñez, Juan Ignacio Rayo Madrid, Cristina Rodríguez Rey, Ricardo Ruano Perez, Joaquín, Ruiz, Gertrudis Sabatel Hernández, Ana, Sevilla, Nahla, Zeidán, Damayanthi, Nanayakkara, Chandraguptha, Udugama, Magnus, Simonsson, Hatem, Alkadhi, Ronny Ralf Buechel, Peter, Burger, Luca, Ceriani, Bart De Boeck, Christoph, Gräni, Alix Juillet de Saint Lager Lucas, Christel, H Kamani, Nadine, Kawel-Boehm, Robert, Manka, John, O Prior, Axel, Rominger, Jean-Paul, Vallée, Benjapa, Khiewvan, Teerapon, Premprabha, Tanyaluck, Thientunyakit, Ali, Sellem, Kemal Metin Kir, Haluk, Sayman, Mugisha Julius Sebikali, Zerida, Muyinda, Yaroslav, Kmetyuk, Pavlo, Korol, Olena, Mykhalchenko, Volodymyr, Pliatsek, Maryna, Satyr, Batool, Albalooshi, Mohamed Ismail Ahmed Hassan, Jill, Anderson, Punit, Bedi, Thomas, Biggans, Anda, Bularga, Russell, Bull, Rajesh, Burgul, John-Paul, Carpenter, Duncan, Coles, David, Cusack, Aparna, Deshpande, John, Dougan, Timothy, Fairbairn, Alexia, Farrugia, Deepa, Gopalan, Alistair, Gummow, Prasad Guntur Ramkumar, Mark, Hamilton, Mark, Harbinson, Thomas, Hartley, Benjamin, Hudson, Nikhil, Joshi, Michael, Kay, Andrew, Kelion, Azhar, Khokhar, Jamie, Kitt, Ken, Lee, Chen, Low, Sze Mun Mak, Ntouskou, Marousa, Jon, Martin, Elisa, Mcalindon, Leon, Menezes, Gareth, Morgan-Hughes, Alastair, Moss, Anthony, Murray, Edward, Nicol, Dilip, Patel, Charles, Peebles, Francesca, Pugliese, Jonathan Carl Luis Rodrigues, Christopher, Rofe, Nikant, Sabharwal, Rebecca, Schofield, Thomas, Semple, Naveen, Sharma, Peter, Strouhal, Deepak, Subedi, William, Topping, Katharine, Tweed, Jonathan, Weir-Mccall, Suhny, Abbara, Taimur, Abbasi, Brian, Abbott, Shady, Abohashem, Sandra, Abramson, Tarek, Al-Abboud, Mouaz, Al-Mallah, Omar, Almousalli, Karthikeyan, Ananthasubramaniam, Mohan Ashok Kumar, Jeffrey, Askew, Lea, Attanasio, Mallory, Balmer-Swain, Richard, R Bayer, Adam, Bernheim, Sabha, Bhatti, Erik, Bieging, Ron, Blankstein, Stephen, Bloom, Sean, Blue, David, Bluemke, Andressa, Borges, Kelley, Branch, Paco, Bravo, Jessica, Brothers, Matthew, Budoff, Renée, Bullock-Palmer, Angela, Burandt, Floyd, W Burke, Kelvin, Bush, Candace, Candela, Elizabeth, Capasso, Joao, Cavalcante, Donald, Chang, Saurav, Chatterjee, Yiannis, Chatzizisis, Michael, Cheezum, Tiffany, Chen, Jennifer, Chen, Marcus, Chen, Andrew, Choi, James, Clarcq, Ayreen, Cordero, Matthew, Crim, Sorin, Danciu, Bruce, Decter, Nimish, Dhruva, Neil, Doherty, Rami, Doukky, Anjori, Dunbar, William, Duvall, Rachael, Edwards, Kerry, Esquitin, Husam, Farah, Emilio, Fentanes, Maros, Ferencik, Daniel, Fisher, Daniel, Fitzpatrick, Cameron, Foster, Tony, Fuisz, Michael, Gannon, Lori, Gastner, Myron, Gerson, Brian, Ghoshhajra, Alan, Goldberg, Brian, Goldner, Jorge, Gonzalez, Rosco, Gore, Sandra, Gracia-López, Fadi, Hage, Agha, Haider, Sofia, Haider, Yasmin, Hamirani, Karen, Hassen, Mallory, Hatfield, Carolyn, Hawkins, Katie, Hawthorne, Nicholas, Heath, Robert, Hendel, Phillip, Hernandez, Gregory, Hill, Stephen, Horgan, Jeff, Huffman, Lynne, Hurwitz, Ami, Iskandrian, Rajesh, Janardhanan, Christine, Jellis, Scott, Jerome, Dinesh, Kalra, Summanther, Kaviratne, Fernando, Kay, Faith, Kelly, Omar, Khalique, Mona, Kinkhabwala, George Kinzfogl Iii, Jacqueline, Kircher, Rachael, Kirkbride, Michael, Kontos, Anupama, Kottam, Joseph, Krepp, Jay, Layer, Steven, H Lee, Jeffrey, Leppo, John, Lesser, Steve, Leung, Howard, Lewin, Diana, Litmanovich, Yiyan, Liu, Kathleen, Magurany, Jeremy, Markowitz, Amanda, Marn, Stephen, E Matis, Michael, Mckenna, Tony, Mcrae, Fernando, Mendoza, Michael, Merhige, David, Min, Chanan, Moffitt, Karen, Moncher, Warren, Moore, Shamil, Morayati, Michael, Morris, Mahmud, Mossa-Basha, Zorana, Mrsic, Venkatesh, Murthy, Prashant, Nagpal, Kyle, Napier, Katarina, Nelson, Prabhjot, Nijjar, Medhat, Osman, Edward, Passen, Amit, Patel, Pravin, Patil, Ryan, Paul, Lawrence, Phillips, Venkateshwar, Polsani, Rajaram, Poludasu, Brian, Pomerantz, Thomas, Porter, Ryan, Prentice, Amit, Pursnani, Mark, Rabbat, Suresh, Ramamurti, Florence, Rich, Hiram Rivera Luna, Austin, Robinson, Kim, Robles, Cesar, Rodríguez, Mark, Rorie, John, Rumberger, Raymond, Russell, Philip, Sabra, Diego, Sadler, Mary, Schemmer, U Joseph Schoepf, Samir, Shah, Nishant, Shah, Sujata, Shanbhag, Gaurav, Sharma, Steven, Shayani, Jamshid, Shirani, Pushpa, Shivaram, Steven, Sigman, Mitch, Simon, Ahmad, Slim, David, Smith, Alexandra, Smith, Prem, Soman, Aditya, Sood, Monvadi Barbara Srichai-Parsia, James, Streeter, Albert, T Ahmed Tawakol, Dustin, Thomas, Randall, Thompson, Tara, Torbet, Desiree, Trinidad, Shawn, Ullery, Samuel, Unzek, Seth, Uretsky, Srikanth, Vallurupalli, Vikas, Verma, Alfonso, Waller, Ellen, Wang, Parker, Ward, Gaby, Weissman, George, Wesbey, Kelly, White, David, Winchester, David, Wolinsky, Sandra, Yost, Michael, Zgaljardic, Omar, Alonso, Mario, Beretta, Rodolfo, Ferrando, Miguel, Kapitan, Fernando, Mut, Omoa, Djuraev, Gulnora, Rozikhodjaeva, Ha Le Ngoc, Son Hong Mai, Xuan Canh Nguyen, Einstein, A. J., Shaw, L. J., Hirschfeld, C., Williams, M. C., Villines, T. C., Better, N., Vitola, J. V., Cerci, R., Dorbala, S., Raggi, P., Choi, A. D., Lu, B., Sinitsyn, V., Sergienko, V., Kudo, T., Norgaard, B. L., Maurovich-Horvat, P., Campisi, R., Milan, E., Louw, L., Allam, A. H., Bhatia, M., Malkovskiy, E., Goebel, B., Cohen, Y., Randazzo, M., Narula, J., Pascual, T. N. B., Pynda, Y., Dondi, M., Paez, D., Cuocolo, A., Einstein, A, Shaw, L, Hirschfeld, C, Williams, M, Villines, T, Better, N, Vitola, J, Cerci, R, Dorbala, S, Raggi, P, Choi, A, Lu, B, Sinitsyn, V, Sergienko, V, Kudo, T, Norgaard, B, Maurovich-Horvat, P, Campisi, R, Milan, E, Louw, L, Allam, A, Bhatia, M, Malkovskiy, E, Goebel, B, Cohen, Y, Randazzo, M, Narula, J, Pascual, T, Pynda, Y, Dondi, M, Paez, D, Pacella, S, and Erba, P
Subjects: INCAPS COVID Investigators Group, Heart disease, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], Diagnostic Techniques, Cardiovascular, coronavirus, global health, IAEA, Disease, Telehealth, Cardiorespiratory Medicine and Haematology, 030204 cardiovascular system & hematology, Cardiovascular, 0302 clinical medicine, cardiovascular disease, cardiac testing, COVID-19, diagnostic techniques, cardiovascular, health care surveys, heart diseases, humans, international agencies, Pandemic, Global health, 030212 general & internal medicine, COVID-19 Heart Disease, Cause of death, STATEMENT, Heart Disease, International Agencie, Public Health and Health Services, Biomedical Imaging, Cardiology and Cardiovascular Medicine, Human, medicine.medical_specialty, Heart Diseases, 03 medical and health sciences, Clinical Research, medicine, Humans, Personal protective equipment, Heart Disease - Coronary Heart Disease, business.industry, International Agencies, medicine.disease, the, coronaviru, Diagnostic Techniques, Good Health and Well Being, Clinical research, Cardiovascular System & Hematology, Health Care Survey, Health Care Surveys, Emergency medicine, Global Health, business
Abstract: BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has adversely affected diagnosis and treatment of noncommunicable diseases. Its effects on delivery of diagnostic care for cardiovascular disease, which remains the leading cause of death worldwide, have not been quantified. OBJECTIVES The study sought to assess COVID-19`s impact on global cardiovascular diagnostic procedural volumes and safety practices. METHODS The International Atomic Energy Agency conducted a worldwide survey assessing alterations in cardiovascular procedure volumes and safety practices resulting from COVID-19. Noninvasive and invasive cardiac testing volumes were obtained from participating sites for March and April 2020 and compared with those from March 2019. Availability of personal protective equipment and pandemic-related testing practice changes were ascertained. RESULTS Surveys were submitted from 909 inpatient and outpatient centers performing cardiac diagnostic procedures, in 108 countries. Procedure volumes decreased 42% from March 2019 to March 2020, and 64% from March 2019 to April 2020. Transthoradc echocardiography decreased by 59%, transesophageat echocardiography 76%, and stress tests 78%, which varied between stress modalities. Coronary angiography (invasive or computed tomography) decreased 55% (p < 0.001 for each procedure). hi multivariable regression, significantly greater reduction in procedures occurred for centers in countries with lower gross domestic product. Location in a low-income and lower-middle-income country was associated with an additional 22% reduction in cardiac procedures and less availability of personal protective equipment and teteheatth. CONCLUSIONS COVID-19 was associated with a significant and abrupt reduction in cardiovascular diagnostic testing across the globe, especially affecting the world's economically challenged. Further study of cardiovascular outcomes and COVID-19-related changes in care delivery is warranted. (C) 2021 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.
Published: 2021

6. A Rare Case of Severe Nontropical Isolated Right Ventricular Endomyocardial Fibrosis

Author: S. Laher, David Godbolt, David Platts, Christian Hamilton-Craig, Anil Prabhu, A. Dashwood, Yee Weng Wong, Elizabeth Cheesman, and Bruce Thomson
Subjects: 0301 basic medicine, medicine.medical_specialty, endomyocardial fibrosis, Endomyocardial fibrosis, TTE, Transthoracic echocardiogram, Hemodynamics, right ventricle, 030105 genetics & heredity, RVOT, right ventricular outflow tract, Late presentation, 03 medical and health sciences, 0302 clinical medicine, CMR, cardiac magnetic resonance, EMF, endomyocardial fibrosis, Internal medicine, Rare case, Mini-Focus Issue: Cardiomyopathies and Myocarditis, Diseases of the circulatory (Cardiovascular) system, Medicine, LV, left ventricular, CE, contrast-enhanced, Tricuspid valve, business.industry, contrast enhanced TTE, RVOT - Right ventricular outflow tract, ECMO - Extracorporeal membrane oxygenation, RA, right atrial, medicine.anatomical_structure, Ventricle, RC666-701, Cardiology, TV, tricuspid valve, Case Report: Clinical Case, RV, right ventricular, Cardiology and Cardiovascular Medicine, business, ECMO, extracorporeal membrane oxygenation, 030217 neurology & neurosurgery
Abstract: We present a case of late presentation nontropical endomyocardial fibrosis isolated to the right ventricle and tricuspid valve (TV). In response to deteriorating hemodynamics, surgical debulking and TV removal were performed before initiation of centralized venoarterial extracorporeal membrane oxygenation support. Definitive endomyocardial resection with a TV prosthesis was then successfully completed. (Level of Difficulty: Advanced.), Central Illustration
Published: 2020

7. Gadobutrol-Enhanced Cardiac Magnetic Resonance Imaging for Detection of Coronary Artery Disease

Author: Andrew E. Arai, Jeanette Schulz-Menger, Daniel Berman, Heiko Mahrholdt, Yuchi Han, W. Patricia Bandettini, Matthias Gutberlet, Arun Abraham, Pamela K. Woodard, Joseph B. Selvanayagam, Gerry P. McCann, Christian Hamilton-Craig, U. Joseph Schoepf, Ru San Tan, Christopher M. Kramer, Matthias G. Friedrich, Daniel Haverstock, Zheyu Liu, Guenther Brueggenwerth, Claudia Bacher-Stier, Marta Santiuste, Dudley J. Pennell, Dudley Pennell, Ulrich Kramer, Giso von der Recke, Kai Nassenstein, Christoph Tillmanns, Matthias Taupitz, Gregor Pache, Oliver Mohrs, Joachim Lotz, Sung-Min Ko, Ki Seok Choo, Yon Mi Sung, Joon-Won Kang, Stefano Muzzarelli, Uma Valeti, Gerry McCann, Sukumaran Binukrishnam, Pierre Croisille, Alexis Jacquier, Brett Cowan, Andrew Arai, Dipan Shah, Pamela Woodard, Ryan Avery, Joseph Schoepf, James Carr, Christopher Kramer, Scott Flamm, Mukesh Harsinghani, Stamitios Lerakis, Raymond Kim, Subha Raman, Francois Marcotte, Ali Islam, Matthias Friedrich, Joseph Selvanayagam, Woon Kit Chong, Li San Lynette Teo, and British Heart Foundation
Subjects: Male, Cardiac & Cardiovascular Systems, MULTICENTER, Contrast Media, CAD, Coronary Artery Disease, 030204 cardiovascular system & hematology, ANGIOGRAPHY, Gadobutrol, Coronary artery disease, 0302 clinical medicine, FRACTIONAL FLOW RESERVE, Prevalence, 030212 general & internal medicine, CMR, 1102 Cardiorespiratory Medicine and Haematology, medicine.diagnostic_test, Area under the curve, Middle Aged, EMISSION-COMPUTED-TOMOGRAPHY, Magnetic Resonance Imaging, myocardial infarction, Cardiology, HEART-FAILURE, Female, GUIDED PCI, Cardiology and Cardiovascular Medicine, Life Sciences & Biomedicine, gadobutrol, Perfusion, myocardial perfusion, medicine.drug, medicine.medical_specialty, MYOCARDIAL-PERFUSION MRI, GadaCAD Investigators, MEDICAL THERAPY, 1117 Public Health and Health Services, 03 medical and health sciences, Cardiac magnetic resonance imaging, Internal medicine, Organometallic Compounds, medicine, Humans, DIAGNOSTIC-ACCURACY, cardiovascular diseases, Aged, Science & Technology, business.industry, Magnetic resonance imaging, medicine.disease, Cardiac Imaging Techniques, Stenosis, Cardiovascular System & Hematology, Cardiovascular and Metabolic Diseases, Cardiovascular System & Cardiology, FOLLOW-UP, business
Abstract: Background Gadolinium-based contrast agents were not approved in the United States for detecting coronary artery disease (CAD) prior to the current studies. Objectives The purpose of this study was to determine the sensitivity and specificity of gadobutrol for detection of CAD by assessing myocardial perfusion and late gadolinium enhancement (LGE) imaging. Methods Two international, single-vendor, phase 3 clinical trials of near identical design, “GadaCAD1” and “GadaCAD2,” were performed. Cardiovascular magnetic resonance (CMR) included gadobutrol-enhanced first-pass vasodilator stress and rest perfusion followed by LGE imaging. CAD was defined by quantitative coronary angiography (QCA) but computed tomography coronary angiography could exclude significant CAD. Results Because the design and results for GadaCAD1 (n = 376) and GadaCAD2 (n = 388) were very similar, results were summarized as a fixed-effect meta-analysis (n = 764). The prevalence of CAD was 27.8% defined by a ≥70% QCA stenosis. For detection of a ≥70% QCA stenosis, the sensitivity of CMR was 78.9%, specificity was 86.8%, and area under the curve was 0.871. The sensitivity and specificity for multivessel CAD was 87.4% and 73.0%. For detection of a 50% QCA stenosis, sensitivity was 64.6% and specificity was 86.6%. The optimal threshold for detecting CAD was a ≥67% QCA stenosis in GadaCAD1 and ≥63% QCA stenosis in GadaCAD2. Conclusions Vasodilator stress and rest myocardial perfusion CMR and LGE imaging had high diagnostic accuracy for CAD in 2 phase 3 clinical trials. These findings supported the U .S. Food and Drug Administration approval of gadobutrol-enhanced CMR (0.1 mmol/kg) to assess myocardial perfusion and LGE in adult patients with known or suspected CAD.
Published: 2020

8. Right Ventricular Electrogram Characteristics in a T1 Mapping-Validated Normal Population

Author: Christian Hamilton-Craig, Haris M. Haqqani, Wendy Strugnell, Eric Vittinghoff, and Adam Lee
Subjects: medicine.medical_specialty, education.field_of_study, Ejection fraction, Substrate mapping, Heart disease, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Population, 030204 cardiovascular system & hematology, medicine.disease, Ablation, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Cardiac magnetic resonance imaging, Ventricle, Internal medicine, Cardiology, medicine, 030212 general & internal medicine, Right Ventricular Free Wall, business, education
Abstract: Objectives: The aim of this study was to define normal ventricular electrographic characteristics in T1 mapping–validated normal patients using a contemporary contact force catheter. Background: Reference values for human endocardial ventricular electrographic characteristics have not been defined using contemporary mapping equipment in patients without heart disease or ventricular arrhythmias. Methods: Fourteen patients undergoing SVT ablation underwent mapping of the right ventricle and cardiac magnetic resonance imaging with T1 mapping. Electrograms (EGMs) from sites with >10 g of contact force from the right ventricular free wall (RVFW) and right ventricular septum (RVS) were analyzed. Values 95th percentile were defined as abnormal. Results: The median age was 27 years, 64% of patients were men, and the mean left ventricular ejection fraction was 60%. Native T1 values (mean 979 ms) of the study population were comparable with that of a normal volunteer population. Ninety-five percent of bipolar EGMs had 0.23 mV/ms (RVFW) or >0.24 mV/ms (RVS). Ninety-five percent of unipolar EGMs had a peak-to-peak voltage >3.8 mV (RVFW) or >4.5 mV (RVS). Conclusions: In structurally normal hearts, the threshold for abnormal endocardial unipolar voltage in the RVFW (3.8 mV) is lower than that of the current standard (5.5 mV). The unipolar voltage characteristics of the RVS is distinct from that of the RVFW and left ventricle. This has implications for the detection of intramural or epicardial and especially midseptal scar.
Published: 2020

9. The Cardiac Society of Australia and New Zealand Position Statement on the Diagnosis and Management of Arrhythmogenic Right Ventricular Cardiomyopathy (2019 Update)

Author: Christopher Semsarian, Andrew J. Taylor, Haris M. Haqqani, Andre La Gerche, Andrew J. Martin, Christian Hamilton-Craig, Andrew D. McGavigan, John Atherton, and Tony Stanton
Subjects: Pulmonary and Respiratory Medicine, Position statement, medicine.medical_specialty, Referral, Disease, 030204 cardiovascular system & hematology, Right ventricular cardiomyopathy, Sudden cardiac death, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Humans, 030212 general & internal medicine, Arrhythmogenic Right Ventricular Dysplasia, Societies, Medical, medicine.diagnostic_test, business.industry, Australia, Magnetic resonance imaging, medicine.disease, Arrhythmogenic right ventricular dysplasia, medicine.anatomical_structure, Ventricle, Practice Guidelines as Topic, Cardiology, Cardiology and Cardiovascular Medicine, business, New Zealand
Abstract: Key Points: 1. Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a disease affecting the right, and/or the left ventricle, and commonly presents as an electrical disorder with ventricular arrhythmias and increased risk of sudden cardiac death. 2. ARVC cannot be diagnosed by a single test, and is a clinical diagnosis supported by electrophysiologic, morpho-functional, genetic, and histological data based on the 2010 Task Force 2 criteria. 3. Familial involvement occurs in more than 50%, and referral to a specialist centre with access to genotyping is appropriate in selected cases. 4. Implantable cardioverter-defibrillator (ICD) therapy carries risk, and appropriate thresholds should apply before offering this, particularly in younger individuals.
Published: 2020

10. Global longitudinal strain as a prognostic marker in cardiac resynchronisation therapy: A systematic review

Author: Christian Hamilton-Craig, Vinesh Appadurai, Nicholas D'Elia, Gregory M. Scalia, Stephen Tomlinson, Thomas Mew, and Jonathan Chan
Subjects: Global longitudinal strain, medicine.medical_specialty, Longitudinal strain, genetic structures, medicine.medical_treatment, MEDLINE, Speckle tracking echocardiography, Fibrosis, Internal medicine, medicine, Diseases of the circulatory (Cardiovascular) system, cardiovascular diseases, Heart transplantation, Original Paper, business.industry, Left bundle branch block, medicine.disease, Systematic review, Heart failure, RC666-701, Cardiology, cardiovascular system, Cardiac resynchronisation therapy, Cardiology and Cardiovascular Medicine, business, circulatory and respiratory physiology
Abstract: Highlights • Left ventricular global longitudinal strain (LV GLS) is a sensitive parameter that correlates with myocardial scar burden and fibrosis with potential value in CRT candidates. • First systematic review evaluating the existing evidence for the prognostic value of LV GLS in patients undergoing CRT implantation. • Despite significantly abnormal baseline GLS at CRT implantation, there is still a significant association between incrementally worse LV GLS at CRT implantation and prognostic outcomes on long-term follow-up., Purpose Cardiac resynchronisation therapy (CRT) has proven mortality benefits for heart failure patients with moderate to severe systolic left ventricular dysfunction and evidence of a left bundle branch block. Determining responders to this therapy can be difficult due to the presence of myocardial fibrosis and scar. Left ventricular global longitudinal strain (LV GLS) is a robust and sensitive measure of myocardial function and fibrosis that has significant prognostic value for a plethora of cardiac pathologies. Our aim was to perform a systematic review of the value of LV GLS for predicting outcomes in patients undergoing CRT. Methods A systematic review of the literature was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) protocol for reporting on systematic reviews and meta-analyses. An electronic search of all English, adult publications in EMBASE, MEDLINE/PubMed and the Cochrane Database of Systematic reviews was undertaken. Results The search yielded, 9 studies that included 3,981 patients with symptomatic heart failure, undergoing CRT implantation with LV GLS utilised as a predictor of all-cause mortality, cardiovascular death, rehospitalisation, LVAD implantation/ heart transplantation or left ventricular reverse remodelling. Significant heterogeneity was observed in study outcome measures, included populations, LV-GLS cut-offs and follow-up definitions, resulting in the inability to reliably conduct a meta-analyses. Overall, pre-CRT LV GLS was found to be a predictor of outcome post CRT insertion. Conclusions In conclusion, all studies implied that incrementally abnormal baseline LV GLS pre-CRT implantation was associated with a long term poorer outcome.
Published: 2021

11. Reduction of cardiac imaging tests during the COVID-19 pandemic: The case of Italy. Findings from the IAEA Non-invasive Cardiology Protocol Survey on COVID-19 (INCAPS COVID)

Author: Dondi, M., Milan, E., Pontone, G., Hirschfeld, C. B., Williams, M., Shaw, L. J., Pynda, Y., Raggi, P., Cerci, R., Vitola, J., Better, N., Villines, T. C., Dorbala, S., Pascual, T. N. B., Giubbini, R., Einstein, A. J., Paez, D., Italy: Domenico Albano, Pierpaolo, Alongi, Gaspare, Arnone, Elisa, Bagatin, Sergio, Baldari, Matteo, Bauckneht, Paolo, Bertelli, Francesco, Bianco, Rachele, Bonfiglioli, Roberto, Boni, Andrea, Bruno, Isabella, Bruno, Elena, Busnardo, Elena, Califaretti, Luca, Camoni, Aldo, Carnevale, Roberta, Casoni, Armando Ugo Cavallo, Giorgio, Cavenaghi, Franca, Chierichetti, Marcello, Chiocchi, Corrado, Cittanti, Mauro, Colletta, Umberto, Conti, Alberto, Cossu, Alberto, Cuocolo, Marco, Cuzzocrea, Maria Luisa De Rimini, Giuseppe De Vincentis, Eleonora Del Giudice, Alberico Del Torto, Veronica Della Tommasina, Rexhep, Durmo, Paola Anna Erba, Laura, Evangelista, Riccardo, Faletti, Evelina, Faragasso, Mohsen, Farsad, Paola, Ferro, Luigia, Florimonte, Viviana, Frantellizzi, Fabio Massimo Fringuelli, Marco, Gatti, Angela, Gaudiano, Alessia, Gimelli, Raffaele, Giubbini, Francesca, Giuffrida, Salvatore, Ialuna, Riccardo, Laudicella, Lucia, Leccisotti, Lucia, Leva, Liga, Riccardo, Carlo, Liguori, Giampiero, Longo, Margherita, Maffione, Maria Elisabetta Mancini, Claudio, Marcassa, Elisa, Milan, Barbara, Nardi, Sara, Pacella, Giovanna, Pepe, Gianluca, Pontone, Sabina, Pulizzi, Natale, Quartuccio, Lucia, Rampin, Fabrizio, Ricci, Pierluigi, Rossini, Giuseppe, Rubini, Vincenzo, Russo, Gian Mauro Sacchetti, Gianmario, Sambuceti, Massimo, Scarano, Roberto, Sciagrà, Massimiliano, Sperandio, Antonella, Stefanelli, Guido, Ventroni, Stefania Zoboli Members from Rest of the World (alphabetically by country and last name) Afghanistan: Mohammad Nawaz Nasery Albania: Artan Goda, Ervina Shirka Algeria: Rabie Benlabgaa, Salah, Bouyoucef, Abdelkader, Medjahedi, Qais Nailli Argentina: Mariela Agolti, Roberto Nicolas Aguero, Maria del Carmen Alak, Lucia Graciela Alberguina, Guillermo, Arroñada, Andrea, Astesiano, Alfredo, Astesiano, Carolina Bas Norton, Pablo, Benteo, Juan, Blanco, Juan Manuel Bonelli, Jose Javier Bustos, Raul, Cabrejas, Jorge, Cachero, Roxana, Campisi, Alejandro, Canderoli, Silvia, Carames, Patrícia, Carrascosa, Ricardo, Castro, Oscar, Cendoya, Luciano Martin Cognigni, Carlos, Collaud, Claudia, Cortes, Javier, Courtis, Daniel, Cragnolino, Mariana, Daicz, Alejandro De La Vega, Silvia Teresa De Maria, Horacio Del Riego, Fernando, Dettori, Alejandro, Deviggiano, Laura, Dragonetti, Mario, Embon, Ruben Emilio Enriquez, Jorge, Ensinas, Fernando, Faccio, Adolfo, Facello, Diego, Garofalo, Ricardo, Geronazzo, Natalia, Gonza, Lucas, Gutierrez, Miguel Angel Guzzo, Victor, Hasbani, Melina, Huerin, Victor, Jäger, Julio Manuel Lewkowicz, Maria Nieves, A López De Munaín, Jose Maria Lotti, Alejandra, Marquez, Osvaldo, Masoli, Osvaldo Horacio Masoli, Edgardo, Mastrovito, Matias, Mayoraz, Graciela Eva Melado, Anibal, Mele, Maria Fernanda Merani, Alejandro Horacio Meretta, Susana, Molteni, Marcos, Montecinos, Eduardo, Noguera, Carlos, Novoa, Claudio Pereyra Sueldo, Sebastian Perez Ascani, Pablo, Pollono, Maria Paula Pujol, Alejandro, Radzinschi, Gustavo, Raimondi, Marcela, Redruello, Marina, Rodríguez, Matías, Rodríguez, Romina Lorena Romero, Arturo Romero Acuña, Federico, Rovaletti, Lucas San Miguel, Lucrecia, Solari, Bruno, Strada, Sonia, Traverso, Sonia Simona Traverzo, Maria del Huerto Velazquez Espeche, Juan Sebastian Weihmuller, Juan, Wolcan, Susana Zeffiro Armenia: Mari Sakanyan Australia: Scott Beuzeville, Raef, Boktor, Patrick, Butler, Jennifer, Calcott, Loretta, Carr, Virgil, Chan, Charles, Chao, Woon, Chong, Mark, Dobson, D'Arne, Downie, Girish, Dwivedi, Barry, Elison, Jean, Engela, Roslyn, Francis, Anand, Gaikwad, Ashok Gangasandra Basavaraj, Bruce, Goodwin, Robert, Greenough, Christian, Hamilton-Craig, Victar, Hsieh, Subodh, Joshi, Karin, Lederer, Kenneth, Lee, Joseph, Lee, John, Magnussen, Nghi, Mai, Gordon, Mander, Fiona, Murton, Dee, Nandurkar, Johanne, Neill, Edward, O'Rourke, Patricia, O'Sullivan, George, Pandos, Kunthi, Pathmaraj, Alexander, Pitman, Rohan, Poulter, Manuja, Premaratne, David, Prior, Lloyd, Ridley, Natalie, Rutherford, Hamid, Salehi, Connor, Saunders, Luke, Scarlett, Sujith, Seneviratne, Deepa, Shetty, Ganesh, Shrestha, Jonathan, Shulman, Vijay, Solanki, Tony, Stanton, Murch, Stuart, Michael, Stubbs, Ian, Swainson, Kim, Taubman, Andrew, Taylor, Paul, Thomas, Steven, Unger, Anthony, Upton, Shankar, Vamadevan, William Van Gaal, Johan, Verjans, Demetrius, Voutnis, Victor, Wayne, Peter, Wilson, David, Wong, Kirby, Wong, John Younger Austria: Gudrun Feuchtner, Siroos, Mirzaei, Konrad Weiss Belarus: Natallia Maroz-Vadalazhskaya Belgium: Olivier Gheysens, Filip, Homans, Rodrigo, Moreno-Reyes, Agnès, Pasquet, Veronique, Roelants, Van De Heyning Bolivia: Raúl Araujo Ríos Bosnia - Herzegovina: Valentina Soldat-Stankovic, Caroline M., Sinisa Stankovic Brazil: Maria Helena Albernaz Siqueira, Augusto, Almeida, Paulo Henrique Alves Togni, Jose Henrique Andrade, Luciana, Andrade, Carlos, Anselmi, Roberta, Araújo, Guilherme, Azevedo, Sabbrina, Bezerra, Rodrigo, Biancardi, Gabriel Blacher Grossman, Simone, Brandão, Diego Bromfman Pianta, Lara, Carreira, Bruno, Castro, Tien, Chang, Fernando Cunali, Jr., Roberto, Cury, Roberto, Dantas, Fernando de Amorim Fernandes, Andrea De Lorenzo, Robson De Macedo Filho, Fernanda, Erthal, Fabio, Fernandes, Juliano, Fernandes, Thiago Ferreira De Souza, Wilson Furlan Alves, Bruno, Ghini, Luiz, Goncalves, Ilan, Gottlieb, Marcelo, Hadlich, Vinícius, Kameoka, Ronaldo, Lima, Adna, Lima, Rafael Willain Lopes, Ricardo Machado, e Silva, Tiago, Magalhães, Fábio Martins Silva, Luiz Eduardo Mastrocola, Fábio, Medeiros, José Claudio Meneghetti, Vania, Naue, Danilo, Naves, Roberto, Nolasco, Cesar, Nomura, Joao Bruno Oliveira, Eduardo, Paixao, Filipe Penna De Carvalho, Ibraim, Pinto, Priscila, Possetti, Mayra, Quinta, Rodrigo Rizzo Nogueira Ramos, Ricardo, Rocha, Alfredo, Rodrigues, Carlos, Rodrigues, Leila, Romantini, Adelina, Sanches, Sara, Santana, Leonardo Sara da Silva, Paulo, Schvartzman, Cristina Sebastião Matushita, Tiago, Senra, Afonso, Shiozaki, Maria Eduarda Menezes de Siqueira, Cristiano, Siqueira, Paola, Smanio, Carlos Eduardo Soares, José Soares Junior, Marcio Sommer Bittencourt, Bernardo, Spiro, Cláudio Tinoco Mesquita, Jorge, Torreao, Rafael, Torres, Marly, Uellendahl, Guilherme Urpia Monte, Otávia, Veríssimo, Estevan Vieira Cabeda, Felipe Villela Pedras, Roberto, Waltrick, Marcello Zapparoli Brunei Darussalam: Hamid Naseer Bulgaria: Marina Garcheva-Tsacheva, Irena Kostadinova Cambodia: Youdaline Theng Canada: Gad Abikhzer, Rene, Barette, Benjamin, Chow, Dominique, Dabreo, Matthias, Friedrich, Ria, Garg, Mohammed Nassoh Hafez, Chris, Johnson, Marla, Kiess, Jonathon, Leipsic, Eugene, Leung, Robert, Miller, Anastasia, Oikonomou, Stephan, Probst, Idan, Roifman, Gary, Small, Vikas, Tandon, Adwait, Trivedi, James, White, Katherine Zukotynski Chile: Jose Canessa, Gabriel Castro Muñoz, Carmen, Concha, Pablo, Hidalgo, Cesar, Lovera, Teresa, Massardo, Luis Salazar Vargas Colombia: Pedro Abad, Harold, Arturo, Sandra, Ayala, Luis, Benitez, Alberto, Cadena, Carlos, Caicedo, Antonio Calderón Moncayo, Sharon, Gomez, Gutierrez Villamil, Claudia T., Claudia, Jaimes, Juan, Londoño, Juan Luis Londoño Blair, Luz, Pabon, Mauricio, Pineda, Juan Carlos Rojas, Diego, Ruiz, Manuel Valencia Escobar, Andres, Vasquez, Damiana, Vergel, Alejandro Zuluaga Costa Rica: Isabel Berrocal Gamboa, Gabriel, Castro, Ulises, González, Croatia: Ana Baric, Tonci, Batinic, Maja, Franceschi, Maja Hrabak Paar, Mladen, Jukic, Petar, Medakovic, Viktor, Persic, Marina, Prpic, Ante Punda Cuba: Juan Felipe Batista, Juan Manuel Gómez Lauchy, Yamile Marcos Gutierrez, Rayner, Menéndez, Amalia, Peix, Luis Rochela Cyprus: Christoforos Panagidis, Ioannis Petrou Czech Republic: Vaclav Engelmann, Milan, Kaminek, Vladimír, Kincl, Otto, Lang, Milan Simanek Denmark: Jawdat Abdulla, Morten, Bøttcher, Mette, Christensen, Lars Christian Gormsen, Philip, Hasbak, Søren, Hess, Paw, Holdgaard, Allan, Johansen, Kasper, Kyhl, Bjarne Linde Norgaard, Kristian Altern Øvrehus, Niels Peter Rønnow Sand, Rolf, Steffensen, Anders, Thomassen, Bo Zerahn Dominican Republic: Alfredo Perez Ecuador: Giovanni Alejandro Escorza Velez, Mayra Sanchez Velez Egypt: Islam Shawky Abdel Aziz, Mahasen, Abougabal, Taghreed, Ahmed, Adel, Allam, Ahmed, Asfour, Mona, Hassan, Alia, Hassan, Ahmed, Ibrahim, Sameh, Kaffas, Ahmed, Kandeel, Mohamed Mandour Ali, Ahmad, Mansy, Hany, Maurice, Sherif, Nabil, Mahmoud Shaaban El Salvador: Ana Camila Flores Estonia: Anne Poksi Finland: Juhani Knuuti, Velipekka, Kokkonen, Martti, Larikka, Valtteri Uusitalo France: Matthieu Bailly, Samuel, Burg, Jean-François, Deux, Vincent, Habouzit, Fabien, Hyafil, Olivier, Lairez, Franck, Proffit, Hamza, Regaieg, Laure, Sarda-Mantel, Schneider Ghana: Harold Ayetey Greece: George Angelidis, Vania Tacher Germany: Roman P., Aikaterini, Archontaki, Sofia, Chatziioannou, Ioannis, Datseris, Christina, Fragkaki, Panagiotis, Georgoulias, Sophia, Koukouraki, Maria, Koutelou, Eleni, Kyrozi, Evangelos, Repasos, Petros, Stavrou, Pipitsa Valsamaki Guatemala: Carla Gonzalez, Goleat Gutierrez Honduras: Alejandro Maldonado Hungary: Klara Buga, Ildiko, Garai, Pál, Maurovich-Horvat, Erzsébet, Schmidt, Balint, Szilveszter, Edit Várady India: Nilesh Banthia, Jinendra Kumar Bhagat, Rishi, Bhargava, Vivek, Bhat, Mona, Bhatia, Partha, Choudhury, Vijay Sai Chowdekar, Aparna, Irodi, Shashank, Jain, Elizabeth, Joseph, Sukriti, Kumar, Prof Dr Girijanandan Mahapatra, Deepanjan, Mitra, Bhagwant Rai Mittal, Ahmad, Ozair, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Patel, Sudhir, Saxena, Shantanu, Sengupta, Santosh, Singh, Bhanupriya, Singh, Ashwani, Sood, Atul Verma Indonesia: Erwin Affandi, Padma Savenadia Alam, Edison, Edison, Gani, Gunawan, Habusari, Hapkido, Basuki, Hidayat, Aulia, Huda, Anggoro Praja Mukti, Djoko, Prawiro, Erwin Affandi Soeriadi, Hilman Syawaluddin Iraq: Amjed Albadr Islamic Republic of Iran: Majid Assadi, Farshad, Emami, Golnaz, Houshmand, Majid, Maleki, Maryam Tajik Rostami, Seyed Rasoul Zakavi Israel: Eed Abu Zaid, Svetlana, Agranovich, Yoav, Arnson, Rachel, Bar-Shalom, Alex, Frenkel, Galit, Knafo, Rachel, Lugassi, Israel Shlomo Maor Moalem, Maya, Mor, Noam, Muskal, Sara, Ranser, Aryeh Shalev Jamaica: Dainia Baugh, Duane, Chambers, Ernest, Madu, Felix Nunura Japan: Hiroshi Asano, Chimura Misato Chimura, Shinichiro, Fujimoto, Koichiro, Fujisue, Tomohisa, Fukunaga, Yoshimitsu, Fukushima, Kae, Fukuyama, Jun, Hashimoto, Yasutaka, Ichikawa, Nobuo, Iguchi, Masamichi, Imai, Anri, Inaki, Hayato, Ishimura, Satoshi, Isobe, Toshiaki, Kadokami, Takao, Kato, Takashi, Kudo, Shinichiro, Kumita, Hirotaka, Maruno, Hiroyuki, Mataki, Masao, Miyagawa, Ryota, Morimoto, Masao, Moroi, Shigeki, Nagamachi, Kenichi, Nakajima, Tomoaki, Nakata, Ryo, Nakazato, Mamoru, Nanasato, Masanao, Naya, Takashi, Norikane, Yasutoshi, Ohta, Satoshi, Okayama, Atsutaka, Okizaki, Yoichi, Otomi, Hideki, Otsuka, Masaki, Saito, Sakata Yasushi Sakata, Masayoshi, Sarai, Daisuke, Sato, Shinya, Shiraishi, Yoshinobu, Suwa, Kentaro, Takanami, Kazuya, Takehana, Junichi, Taki, Nagara, Tamaki, Yasuyo, Taniguchi, Hiroki, Teragawa, Nobuo, Tomizawa, Kenichi, Tsujita, Kyoko, Umeji, Yasushi, Wakabayashi, Shinichiro, Yamada, Shinya, Yamazaki, Tatsuya Yoneyama Jordan: Mohammad Rawashdeh Kazakhstan: Daultai Batyrkhanov, Tairkhan Dautov Kenya: Khalid Makhdomi, Kevin Ombati Kuwait: Faridah Alkandari, Masoud Garashi Lao People's Democratic Republic: Tchoyoson Lim Coie, Sonexay Rajvong Latvia: Artem Kalinin, Marika Kalnina Lebanon: Mohamad Haidar Lithuania: Renata Komiagiene, Giedre, Kviecinskiene, Mindaugas, Mataciunas, Karim Malta: Luise Reichmuth, Donatas Vajauskas Luxembourg: Christian Picard Malaysia: Noor Khairiah A., Anthony Samuel Mauritius: Mohammad Aaftaab Allarakha, Ambedhkar Shantaram Naojee Mexico: Erick Alexanderson-Rosas, Erika, Barragan, Alejandro Becerril González-Montecinos, Manuel, Cabada, Daniel Calderon Rodriguez, Isabel, Carvajal-Juarez, Violeta, Cortés, Filiberto, Cortés, Erasmo De La Peña, Manlio, Gama-Moreno, Luis, González, Nelsy Gonzalez Ramírez, Moisés, Jiménez-Santos, Luis, Matos, Edgar, Monroy, Martha, Morelos, Mario, Ornelas, Jose Alberto Ortga Ramirez, Andrés, Preciado-Anaya, Óscar Ulises Preciado-Gutiérrez, Adriana Puente Barragan, Sandra Graciela Rosales Uvera, Sigelinda, Sandoval, Miguel Santaularia Tomas, Sierra-Galan, Lilia M., Silvia, Siu, Enrique, Vallejo, Mario Valles Monaco: Marc Faraggi Mongolia: Erdenechimeg Sereegotov Montenegro: Srdja Ilic Morocco: Nozha Ben-Rais, Nadia Ismaili Alaoui, Sara Taleb Myanmar: Khin Pa Pa Myo, Phyo Si Thu Nepal: Ram Kumar Ghimire, Bijoy Rajbanshi Netherlands: Peter Barneveld, Andor, Glaudemans, Jesse, Habets, Klaas Pieter Koopmans, Jeroen, Manders, Stefan, Pool, Arthur, Scholte, Asbjørn, Scholtens, Riemer, Slart, Paul, Thimister, Erik-Jan Van Asperen, Niels, Veltman, Derk, Verschure, Nils Wagenaar New Zealand: John Edmond, Chris, Ellis, Kerryanne, Johnson, Ross, Keenan, Shaw Hua (Anthony) Kueh, Christopher, Occleshaw, Alexander, Sasse, Andrew, To, Niels Van Pelt, Calum Young Nicaragua: Teresa Cuadra, Hector Bladimir Roque Vanegas Niger: Idrissa Adamou Soli, Djibrillou Moussa Issoufou Nigeria: Tolulope Ayodele, Chibuzo, Madu, Yetunde Onimode Norway: Elen Efros-Monsen, Signe Helene Forsdahl, Jenni-Mari Hildre Dimmen, Arve, Jørgensen, Isabel, Krohn, Pål, Løvhaugen, Anders Tjellaug Bråten Oman: Humoud Al Dhuhli, Faiza Al Kindi, Naeema, Al-Bulushi, Zabah, Jawa, Naima Tag Pakistan: Muhammad Shehzad Afzal, Shazia, Fatima, Muhammad Numair Younis, Musab, Riaz, Mohammad Saadullah Panama: Yariela Herrera Papua New Guinea: Dora Lenturut-Katal Paraguay: Manuel Castillo Vázquez, José Ortellado People's Republic of Bangladesh: Afroza Akhter People's Republic of China: Dianbo Cao, Stephen, Cheung, Dai, Xu, Lianggeng, Gong, Dan, Han, Yang, Hou, Caiying, Li, Tao, Li, Dong, Li, Sijin, Li, Jinkang, Liu, Hui, Liu, Bin, Lu, Ming Yen Ng, Kai, Sun, Gongshun, Tang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wang, Jiang, Wu, Zhifang, Wu, Liming, Xia, Jiangxi, Xiao, Lei, Xu, Youyou, Yang, Yin, Wu, Jianqun, Yu, Yuan, Li, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhang, Li Zhu Peru: Ana Alfaro Philippines: Paz Abrihan, Asela, Barroso, Eric, Cruz, Marie Rhiamar Gomez, Vincent Peter Magboo, John Michael Medina, Jerry, Obaldo, Davidson, Pastrana, Christian Michael Pawhay, Alvin, Quinon, Jeanelle Margareth Tang, Bettina, Tecson, Kristine Joy Uson, Mila Uy Poland: Magdalena Kostkiewicz, Jolanta Kunikowska Portugal: Nuno Bettencourt, Guilhermina, Cantinho, Antonio Ferreira Qatar: Ghulam Syed Republic of Ireland: Samer Arnous, Said, Atyani, Angela, Byrne, Tadhg, Gleeson, David, Kerins, Conor, Meehan, David, Murphy, Mark, Murphy, John, Murray, Julie O'Brien Republic of Korea: Ji-In Bang, Henry, Bom, Sang-Geon, Cho, Chae Moon Hong, Su Jin Jang, Yong Hyu Jeong, Won Jun Kang, Ji-Young, Kim, Jaetae, Lee, Chang Kyeong Namgung, Young, So, Kyoung Sook Won Republic of North Macedonia: Venjamin Majstorov, Marija Vavlukis Republic of Slovenia: Barbara Gužic Salobir, Monika Štalc Romania: Theodora Benedek, Imre, Benedek, Raluca, Mititelu, Claudiu Adrian Stan Russian Federation: Alexey Ansheles, Olga, Dariy, Olga, Drozdova, Nina, Gagarina, Vsevolod Milyevich Gulyaev, Irina, Itskovich, Anatoly, Karalkin, Alexander, Kokov, Ekaterina, Migunova, Viktor, Pospelov, Daria, Ryzhkova, Guzaliya, Saifullina, Svetlana, Sazonova, Vladimir, Sergienko, Irina, Shurupova, Tatjana, Trifonova, Wladimir Yurievich Ussov, Margarita, Vakhromeeva, Nailya, Valiullina, Konstantin, Zavadovsky, Kirill Zhuravlev Saudi Arabia: Mirvat Alasnag, Subhani Okarvi Serbia: Dragana Sobic Saranovic Singapore: Felix Keng, Jia Hao Jason See, Ramkumar, Sekar, Min Sen Yew Slovak Republic: Andrej Vondrak South Africa: Shereen Bejai, George, Bennie, Ria, Bester, Gerrit, Engelbrecht, Osayande, Evbuomwan, Harlem, Gongxeka, Magritha Jv Vuuren, Mitchell, Kaplan, Purbhoo, Khushica, Hoosen, Lakhi, Lizette, Louw, Nico, Malan, Katarina, Milos, Moshe, Modiselle, Stuart, More, Mathava, Naidoo, Leonie, Scholtz, Mboyo Vangu Spain: Santiago Aguadé-Bruix, Isabel, Blanco, Antonio, Cabrera, Alicia, Camarero, Irene, Casáns-Tormo, Hug, Cuellar-Calabria, Albert, Flotats, Maria Eugenia Fuentes Cañamero, María Elia García, Amelia, Jimenez-Heffernan, Rubén, Leta, Javier Lopez Diaz, Luis, Lumbreras, Juan Javier Marquez-Cabeza, Francisco, Martin, Anxo Martinez de Alegria, Francisco, Medina, Maria Pedrera Canal, Virginia, Peiro, Virginia, Pubul-Nuñez, Juan Ignacio Rayo Madrid, Cristina Rodríguez Rey, Ricardo Ruano Perez, Joaquín, Ruiz, Gertrudis Sabatel Hernández, Ana, Sevilla, Nahla Zeidán Sri Lanka: Damayanthi Nanayakkara, Chandraguptha Udugama Sweden: Magnus Simonsson Switzerland: Hatem Alkadhi, Ronny Ralf Buechel, Peter, Burger, Luca, Ceriani, Bart De Boeck, Christoph, Gräni, Alix Juillet de Saint Lager Lucas, Kamani, Christel H., Nadine, Kawel-Boehm, Robert, Manka, Prior, John O., Axel, Rominger, Jean-Paul Vallée Thailand: Benjapa Khiewvan, Teerapon, Premprabha, Tanyaluck Thientunyakit Tunisia: Ali Sellem Turkey: Kemal Metin Kir, Haluk Sayman Uganda: Mugisha Julius Sebikali, Zerida Muyinda Ukraine: Yaroslav Kmetyuk, Pavlo, Korol, Olena, Mykhalchenko, Volodymyr, Pliatsek, Maryna Satyr United Arab Emirates: Batool Albalooshi, Mohamed Ismail Ahmed Hassan United Kingdom: Jill Anderson, Punit, Bedi, Thomas, Biggans, Anda, Bularga, Russell, Bull, Rajesh, Burgul, John-Paul, Carpenter, Duncan, Coles, David, Cusack, Aparna, Deshpande, John, Dougan, Timothy, Fairbairn, Alexia, Farrugia, Deepa, Gopalan, Alistair, Gummow, Prasad Guntur Ramkumar, Mark, Hamilton, Mark, Harbinson, Thomas, Hartley, Benjamin, Hudson, Nikhil, Joshi, Michael, Kay, Andrew, Kelion, Azhar, Khokhar, Jamie, Kitt, Ken, Lee, Chen, Low, Sze Mun Mak, Ntouskou, Marousa, Jon, Martin, Elisa, Mcalindon, Leon, Menezes, Gareth, Morgan-Hughes, Alastair, Moss, Anthony, Murray, Edward, Nicol, Dilip, Patel, Charles, Peebles, Francesca, Pugliese, Jonathan Carl Luis Rodrigues, Christopher, Rofe, Nikant, Sabharwal, Rebecca, Schofield, Thomas, Semple, Naveen, Sharma, Peter, Strouhal, Deepak, Subedi, William, Topping, Katharine, Tweed, Jonathan Weir-Mccall United States of America: Suhny Abbara, Taimur, Abbasi, Brian, Abbott, Shady, Abohashem, Sandra, Abramson, Tarek, Al-Abboud, Mouaz, Al-Mallah, Omar, Almousalli, Karthikeyan, Ananthasubramaniam, Mohan Ashok Kumar, Jeffrey, Askew, Lea, Attanasio, Mallory, Balmer-Swain, Bayer, Richard R., Adam, Bernheim, Sabha, Bhatti, Erik, Bieging, Ron, Blankstein, Stephen, Bloom, Sean, Blue, David, Bluemke, Andressa, Borges, Kelley, Branch, Paco, Bravo, Jessica, Brothers, Matthew, Budoff, Renée, Bullock-Palmer, Angela, Burandt, Burke, Floyd W., Kelvin, Bush, Candace, Candela, Elizabeth, Capasso, Joao, Cavalcante, Donald, Chang, Saurav, Chatterjee, Yiannis, Chatzizisis, Michael, Cheezum, Tiffany, Chen, Jennifer, Chen, Marcus, Chen, Andrew, Choi, James, Clarcq, Ayreen, Cordero, Matthew, Crim, Sorin, Danciu, Bruce, Decter, Nimish, Dhruva, Neil, Doherty, Rami, Doukky, Anjori, Dunbar, William, Duvall, Rachael, Edwards, Kerry, Esquitin, Husam, Farah, Emilio, Fentanes, Maros, Ferencik, Daniel, Fisher, Daniel, Fitzpatrick, Cameron, Foster, Tony, Fuisz, Michael, Gannon, Lori, Gastner, Myron, Gerson, Brian, Ghoshhajra, Alan, Goldberg, Brian, Goldner, Jorge, Gonzalez, Rosco, Gore, Sandra, Gracia-López, Fadi, Hage, Agha, Haider, Sofia, Haider, Yasmin, Hamirani, Karen, Hassen, Mallory, Hatfield, Carolyn, Hawkins, Katie, Hawthorne, Nicholas, Heath, Robert, Hendel, Phillip, Hernandez, Gregory, Hill, Stephen, Horgan, Jeff, Huffman, Lynne, Hurwitz, Ami, Iskandrian, Rajesh, Janardhanan, Christine, Jellis, Scott, Jerome, Dinesh, Kalra, Summanther, Kaviratne, Fernando, Kay, Faith, Kelly, Omar, Khalique, Mona, Kinkhabwala, George Kinzfogl Iii, Jacqueline, Kircher, Rachael, Kirkbride, Michael, Kontos, Anupama, Kottam, Joseph, Krepp, Jay, Layer, Steven, H Lee, Jeffrey, Leppo, John, Lesser, Steve, Leung, Howard, Lewin, Diana, Litmanovich, Yiyan, Liu, Juan, Lopez-Mattei, Kathleen, Magurany, Jeremy, Markowitz, Amanda, Marn, Stephen, E Matis, Michael, Mckenna, Tony, Mcrae, Fernando, Mendoza, Michael, Merhige, David, Min, Chanan, Moffitt, Karen, Moncher, Warren, Moore, Shamil, Morayati, Michael, Morris, Mahmud, Mossa-Basha, Zorana, Mrsic, Venkatesh, Murthy, Prashant, Nagpal, Kyle, Napier, Jagat, Narula, Katarina, Nelson, Prabhjot, Nijjar, Medhat, Osman, Purvi, Parwani, Edward, Passen, Amit, Patel, Pravin, Patil, Ryan, Paul, Lawrence, Phillips, Venkateshwar, Polsani, Rajaram, Poludasu, Brian, Pomerantz, Thomas, Porter, Ryan, Prentice, Amit, Pursnani, Mark, Rabbat, Suresh, Ramamurti, Florence, Rich, Hiram Rivera Luna, Austin, Robinson, Kim, Robles, Cesar, Rodríguez, Mark, Rorie, John, Rumberger, Raymond, Russell, Philip, Sabra, Diego, Sadler, Mary, Schemmer, Joseph Schoepf, U., Samir, Shah, Nishant, Shah, Sujata, Shanbhag, Gaurav, Sharma, Steven, Shayani, Jamshid, Shirani, Pushpa, Shivaram, Steven, Sigman, Mitch, Simon, Ahmad, Slim, David, Smith, Alexandra, Smith, Prem, Soman, Aditya, Sood, Monvadi Barbara Srichai-Parsia, James, Streeter, Albert, T, Ahmed, Tawakol, Dustin, Thomas, Randall, Thompson, Tara, Torbet, Desiree, Trinidad, Shawn, Ullery, Samuel, Unzek, Seth, Uretsky, Srikanth, Vallurupalli, Vikas, Verma, Alfonso, Waller, Ellen, Wang, Parker, Ward, Gaby, Weissman, George, Wesbey, Kelly, White, David, Winchester, David, Wolinsky, Sandra, Yost, Michael Zgaljardic Uruguay: Omar Alonso, Mario, Beretta, Rodolfo, Ferrando, Miguel, Kapitan, Fernando Mut Uzbekistan: Omoa Djuraev, Gulnora Rozikhodjaeva Vietnam: Ha Le Ngoc, Son Hong Mai, and Xuan Canh Nguyen
Subjects: medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Cardiology, Settore MED/11 - Malattie dell'Apparato Cardiovascolare, COVID-19, Cardiac imaging, Cardiovascular disease, Article, cardiac imaging, Healthcare delivery, cardiovascular disease, Intensive care, Surveys and Questionnaires, Health care, Pandemic, medicine, Humans, Pandemics, Protocol (science), business.industry, SARS-CoV-2, Non invasive, Italy, humans, pandemics, surveys and questionnaires, cardiology, Emergency medicine, Cardiology and Cardiovascular Medicine, business
Abstract: Background: In early 2020, COVID-19 massively hit Italy, earlier and harder than any other European country. This caused a series of strict containment measures, aimed at blocking the spread of the pandemic. Healthcare delivery was also affected when resources were diverted towards care of COVID-19 patients, including intensive care wards. Aim of the study: The aim is assessing the impact of COVID-19 on cardiac imaging in Italy, compare to the Rest of Europe (RoE) and the World (RoW). Methods: A global survey was conducted in May–June 2020 worldwide, through a questionnaire distributed online. The survey covered three periods: March and April 2020, and March 2019. Data from 52 Italian centres, a subset of the 909 participating centres from 108 countries, were analyzed. Results: In Italy, volumes decreased by 67% in March 2020, compared to March 2019, as opposed to a significantly lower decrease (p < 0.001) in RoE and RoW (41% and 40%, respectively). A further decrease from March 2020 to April 2020 summed up to 76% for the North, 77% for the Centre and 86% for the South. When compared to the RoE and RoW, this further decrease from March 2020 to April 2020 in Italy was significantly less (p = 0.005), most likely reflecting the earlier effects of the containment measures in Italy, taken earlier than anywhere else in the West. Conclusions: The COVID-19 pandemic massively hit Italy and caused a disruption of healthcare services, including cardiac imaging studies. This raises concern about the medium- and long-term consequences for the high number of patients who were denied timely diagnoses and the subsequent lifesaving therapies and procedures.
Published: 2021

12. Coronary CT radiation dose reduction strategies at an Australian Tertiary Care Center – improvements in radiation exposure through an evidence‐based approach

Author: Allan J. Wesley, Karman Tandon, Chris Burley, Kelley R. Branch, J. Neill, Rachael O'Rourke, Bianca Kwan, Christian Hamilton-Craig, and Karen DeBoni
Subjects: lcsh:Medical physics. Medical radiology. Nuclear medicine, cardiovascular computed tomography, tube voltage, Male, medicine.medical_specialty, Evidence-based practice, prospectively triggered coronary CT, lcsh:R895-920, Coronary Angiography, Radiation Dosage, Tertiary care, 030218 nuclear medicine & medical imaging, Ionizing radiation, Tertiary Care Centers, 03 medical and health sciences, 0302 clinical medicine, Heart rate, medicine, Humans, Radiology, Nuclear Medicine and imaging, education, Evidence-Based Medicine, Radiological and Ultrasound Technology, Coronary ct, business.industry, Radiation dose, Australia, coronary CT, Original Articles, Radiation Exposure, Radiation exposure, 030220 oncology & carcinogenesis, Practice Guidelines as Topic, Dose reduction, Original Article, Female, Radiology, business, radiation dose, Tomography, X-Ray Computed
Abstract: Introduction Coronary CT Angiography (CCTA) is a rapidly increasing technique for coronary imaging; however, it exposes patients to ionising radiation. We examined the impact of dose reduction techniques using ECG‐triggering, kVp/mAs reduction and high‐pitch modes on radiation exposure in a large Australian tertiary CCTA service. Methods Data on acquisition modes and dose exposure were prospectively collected on all CCTA scans from November 2009 to March 2014 at an Australian tertiary care centre. A dose reduction algorithm was developed using published techniques and implemented with education of medical staff, radiographers and referrers. Associations of CCTA acquisition to radiation over time were analysed with multivariate regression. Specificity in positive CCTA was assessed by correlation with invasive coronary angiography. Results 3333 CCTAs were analysed. Mean radiation dose decreased from 8.4 mSv to 5.3, 4.4, 3.7, 2.9 and 2.8 mSv (P, Cardiac CT angiography dosing was reviewed after implementation of dose reduction strategies. 3333 CCTAs were analyzed. Implementation of evidence‐based dose reduction strategies and a decision‐support algorithm accounted for 91% of dose reduction, with 9% attributable to hardware. Significant reductions in radiation exposure are feasible in real‐world clinical practice and can be successfully applied through better education and training.
Published: 2019

13. 72-year-old woman after a left atrial appendage occluder

Author: Matthew Lambert, Christian Hamilton-Craig, and Aaron C.W. Lin
Subjects: Appendage, medicine.medical_specialty, Percutaneous, business.industry, Atrial fibrillation, 030204 cardiovascular system & hematology, Pericardial space, medicine.disease, Pericardial effusion, 03 medical and health sciences, 0302 clinical medicine, Left atrial, Parasternal line, Internal medicine, medicine, Cardiology, 030212 general & internal medicine, Transthoracic echocardiogram, Cardiology and Cardiovascular Medicine, business
Abstract: A 72-year-old woman presented for routine echocardiography 6 months following percutaneous insertion of a left atrial appendage occluder (LAAO) due to atrial fibrillation with contraindications to anticoagulation. The procedure was uncomplicated, and she was clinically well. On echocardiography an abnormality was seen in the posterior pericardial space (Figure 1, arrows). Figure 1 Transthoracic Echocardiogram: left, parasternal long axis. right, parasternal short axis …
Published: 2019

14. 7-Tesla Functional Cardiovascular MR Using Vectorcardiographic Triggering – overcoming the magnetohydrodynamic effect

Author: Sabine Fletcher, Kieran O'Brien, Markus Barth, Graham J. Galloway, Daniel Staeb, Aiman Al-Najjar, Christian Hamilton-Craig, and William Crawford
Subjects: Ejection fraction, medicine.diagnostic_test, Image quality, business.industry, Cardiac Volume, Phase contrast microscopy, Magnetic resonance imaging, Signal, law.invention, law, Vascular flow, Distortion, medicine, Nuclear medicine, business
Abstract: ObjectiveUltra-high-field (B0 ≥ 7 Tesla) cardiovascular magnetic resonance (CMR) offers increased resolution. However, ECG gating is impacted by the magneto-hydrodynamic (MHD) effect distorting the ECG trace. We explored the technical feasibility of a 7T MR scanner using ECG trigger learning algorithm to quantitatively assess cardiac volumes and vascular flow.Methods7T scans performed on 10 healthy volunteers on a whole-body research MRI (Siemens Healthcare, Erlangen, Germany) with 8 channel Tx/32 channel Rx cardiac coil (MRI Tools GmbH, Berlin, Germany). Vectorcardiogram ECG was performed using a learning phase outside of the magnetic field, with a trigger algorithm overcoming severe ECG signal distortions.Vectorcardiograms were quantitatively analyzed for false negative and false positive events. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented spoiled gradient echo, and 2D phase contrast flow imaging. Artefacts were assessed using a semi-quantitative scale.Results7T CMR scans were acquired in all patients (100%) using the VCG learning method. 3,142 R-waves were quantitatively analyzed, yielding sensitivity 97.6%, specificity 98.7%. Mean image quality score was 0.9, sufficient to quantitate both cardiac volumes, ejection fraction (EF), aortic and pulmonary blood flow. Mean LVEF was 56.4%, RVEF 51.4%.ConclusionReliable cardiac ECG triggering is feasible in healthy volunteers at 7T utilizing a state-of-the-art 3-lead trigger device despite signal distortion from the MHD effect. This provides sufficient image quality for quantitative analysis. Other ultra-high-field imaging applications such as human brain functional MRI with physiologic noise correction may benefit from this method of ECG triggering.Key pointsUltra-high field 7 Tesla cardiac MRI is challenging due to the impact of the magneto-hydrodynamic (MHD) effect causing severe distortions in the ECG trace.Using VCG with a learning phase outside the ultra-high field magnet, the R waves can be adequately detected to perform high quality Cardiac MRI scans, overcoming signal distortion from the MHD effect.
Published: 2021

15. LV non-compaction in patients with coarctation of the aorta: prevalence and effects on cardiac function

Author: David S. Celermajer, Christian Hamilton-Craig, Shelby Kutty, Rajesh Puranik, Preeti Choudhary, and Wendy Strugnell
Subjects: Cardiac function curve, Adult, Heart Defects, Congenital, Male, medicine.medical_specialty, Heart disease, Coarctation of the aorta, Diastole, 030204 cardiovascular system & hematology, Sudden death, Aortic Coarctation, Ventricular Function, Left, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Cardiac magnetic resonance imaging, Internal medicine, medicine, Prevalence, Humans, Ejection fraction, medicine.diagnostic_test, business.industry, Stroke Volume, General Medicine, medicine.disease, Heart failure, Pediatrics, Perinatology and Child Health, cardiovascular system, Cardiology, Female, Cardiology and Cardiovascular Medicine, business
Abstract: Background:Left ventricular non-compaction has been associated with heart failure, arrhythmia, thromboembolism and sudden death. The prevalence of non-compaction in patients with coarctation of the aorta and its clinical significance remains unknown, although obstructive left heart disease is common in patients with non-compaction. We sought to evaluate the prevalence of left ventricular non-compaction in patients with repaired aortic coarctation as well as its effect on left ventricular size and systolic function.Methods and results:In total, 268 patients (Mean age 26 (inter-quartile range 21–37) years, 63% male) undergoing cardiac magnetic resonance imaging for clinical follow-up were included from three tertiary centres for adult congenital heart disease. Clinical data was obtained from medical records and correlated with ventricular volumes and function. Left ventricular non-compaction was defined as a diastolic non-compacted:compacted dimension ratio >2.3 in the worst affected segment on a long-axis view. Left ventricular non-compaction was present in 8.2% of patients with repaired coarctation. Left ventricular end-diastolic volumes and stroke volumes were significantly higher in patients with non-compaction compared to those without. There were no significant differences in ventricular mass or ejection fraction in these two groups.Conclusions:Left ventricular non-compaction is relatively common in patients with repaired coarctation of the aorta and correlates with increased left ventricular end-diastolic volumes.
Published: 2021

16. Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance

Author: Charlotte Manisty, Gianluca Pontone, Gabriella Captur, Ntobeko A B Ntusi, João B Augusto, Rhodri H Davies, Thomas A. Treibel, Bernhard Gerber, Peter P Swoboda, Kristopher D Knott, Rebecca K. Hughes, Christian Hamilton-Craig, Chiara Bucciarelli-Ducci, Anish N Bhuva, Steffen E. Petersen, Mashael Alfarih, Clement Lau, Erik B. Schelbert, James C. Moon, John P Greenwood, Milind Y. Desai, Andreas Seraphim, Hunain Shiwani, João L. Cavalcante, Luis R. Lopes, UCL - SSS/IREC/CARD - Pôle de recherche cardiovasculaire, and UCL - (SLuc) Service de pathologie cardiovasculaire
Subjects: Adult, Male, Coefficient of variation, Heart Ventricles, Medicine (miscellaneous), Health Informatics, Machine learning, computer.software_genre, Risk Assessment, Machine Learning, Health Information Management, Medicine, Humans, Decision Sciences (miscellaneous), Aged, Observer Variation, Reproducibility, business.industry, Hypertrophic cardiomyopathy, Reproducibility of Results, Cardiomyopathy, Hypertrophic, Middle Aged, medicine.disease, Magnetic Resonance Imaging, United Kingdom, Test (assessment), Sample size determination, Risk stratification, Female, Artificial intelligence, Cutoff point, business, Wall thickness, computer, Algorithms
Abstract: Background: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT measurement and compared precision (reproducibility) with that of 11 international experts, using a dataset of patients with hypertrophic cardiomyopathy. Methods: 60 adult patients with hypertrophic cardiomyopathy, including those carrying hypertrophic cardiomyopathy gene mutations, were recruited at three institutes in the UK from August, 2018, to September, 2019: Barts Heart Centre, University College London Hospital (The Heart Hospital), and Leeds Teaching Hospitals NHS Trust. Participants had two cardiovascular magnetic resonance scans (test and retest) on the same day, ensuring no biological variability, using four cardiac MRI scanner models represented across two manufacturers and two field strengths. End-diastolic short-axis MWT was measured in test and retest by 11 international experts (from nine centres in six countries) and an automated machine learning method, which was trained to segment endocardial and epicardial contours on an independent, multicentre, multidisease dataset of 1923 patients. Machine learning MWT measurement was done with a method based on solving Laplace's equation. To assess test–retest reproducibility, we estimated the absolute test–retest MWT difference (precision), the coefficient of variation (CoV) for duplicate measurements, and the number of patients reclassified between test and retest according to different thresholds (MWT >15 mm and >30 mm). We calculated the sample size required to detect a prespecified MWT change between pairs of scans for machine learning and each expert. Findings: 1440 MWT measurements were analysed, corresponding to two scans from 60 participants by 12 observers (11 experts and machine learning). Experts differed in the MWT they measured, ranging from 14·9 mm (SD 4·2) to 19·0 mm (4·7; p
Published: 2021

17. Impact of COVID-19 Pandemic on Cardiovascular Testing in Asia

Author: Takashi Kudo, Ryan Lahey, Cole B. Hirschfeld, Michelle C. Williams, Bin Lu, Mirvat Alasnag, Mona Bhatia, Hee-Seung Henry Bom, Tairkhan Dautov, Reza Fazel, Ganesan Karthikeyan, Felix Y.J. Keng, Ronen Rubinshtein, Nathan Better, Rodrigo Julio Cerci, Sharmila Dorbala, Paolo Raggi, Leslee J. Shaw, Todd C. Villines, João V. Vitola, Andrew D. Choi, Eli Malkovskiy, Benjamin Goebel, Yosef A. Cohen, Michael Randazzo, Thomas N.B. Pascual, Yaroslav Pynda, Maurizio Dondi, Diana Paez, Andrew J. Einstein, Rodrigo Cerci, Joao V. Vitola, Gerd Hinterleitner, Yao Lu, Olga Morozova, Zhuoran Xu, Yosef Cohen, Andrew Choi, Juan Lopez-Mattei, Purvi Parwani, Mohammad Nawaz Nasery, Artan Goda, Ervina Shirka, Rabie Benlabgaa, Salah Bouyoucef, Abdelkader Medjahedi, Qais Nailli, Mariela Agolti, Roberto Nicolas Aguero, Maria del Carmen Alak, Lucia Graciela Alberguina, Guillermo Arroñada, Andrea Astesiano, Alfredo Astesiano, Carolina Bas Norton, Pablo Benteo, Juan Blanco, Juan Manuel Bonelli, Jose Javier Bustos, Raul Cabrejas, Jorge Cachero, Roxana Campisi, Alejandro Canderoli, Silvia Carames, Patrícia Carrascosa, Ricardo Castro, Oscar Cendoya, Luciano Martin Cognigni, Carlos Collaud, Claudia Cortes, Javier Courtis, Daniel Cragnolino, Mariana Daicz, Alejandro De La Vega, Silvia Teresa De Maria, Horacio Del Riego, Fernando Dettori, Alejandro Deviggiano, Laura Dragonetti, Mario Embon, Ruben Emilio Enriquez, Jorge Ensinas, Fernando Faccio, Adolfo Facello, Diego Garofalo, Ricardo Geronazzo, Natalia Gonza, Lucas Gutierrez, Miguel Angel Guzzo, Victor Hasbani, Melina Huerin, Victor Jäger, Julio Manuel Lewkowicz, Maria Nieves A. López De Munaín, Jose Maria Lotti, Alejandra Marquez, Osvaldo Masoli, Osvaldo Horacio Masoli, Edgardo Mastrovito, Matias Mayoraz, Graciela Eva Melado, Anibal Mele, Maria Fernanda Merani, Alejandro Horacio Meretta, Susana Molteni, Marcos Montecinos, Eduardo Noguera, Carlos Novoa, Claudio Pereyra Sueldo, Sebastian Perez Ascani, Pablo Pollono, Maria Paula Pujol, Alejandro Radzinschi, Gustavo Raimondi, Marcela Redruello, Marina Rodríguez, Matías Rodríguez, Romina Lorena Romero, Arturo Romero Acuña, Federico Rovaletti, Lucas San Miguel, Lucrecia Solari, Bruno Strada, Sonia Traverso, Sonia Simona Traverzo, Maria del Huerto Velazquez Espeche, Juan Sebastian Weihmuller, Juan Wolcan, Susana Zeffiro, Mari Sakanyan, Scott Beuzeville, Raef Boktor, Patrick Butler, Jennifer Calcott, Loretta Carr, Virgil Chan, Charles Chao, Woon Chong, Mark Dobson, D'Arne Downie, Girish Dwivedi, Barry Elison, Jean Engela, Roslyn Francis, Anand Gaikwad, Ashok Gangasandra Basavaraj, Bruce Goodwin, Robert Greenough, Christian Hamilton-Craig, Victar Hsieh, Subodh Joshi, Karin Lederer, Kenneth Lee, Joseph Lee, John Magnussen, Nghi Mai, Gordon Mander, Fiona Murton, Dee Nandurkar, Johanne Neill, Edward O'Rourke, Patricia O'Sullivan, George Pandos, Kunthi Pathmaraj, Alexander Pitman, Rohan Poulter, Manuja Premaratne, David Prior, Lloyd Ridley, Natalie Rutherford, Hamid Salehi, Connor Saunders, Luke Scarlett, Sujith Seneviratne, Deepa Shetty, Ganesh Shrestha, Jonathan Shulman, Vijay Solanki, Tony Stanton, Murch Stuart, Michael Stubbs, Ian Swainson, Kim Taubman, Andrew Taylor, Paul Thomas, Steven Unger, Anthony Upton, Shankar Vamadevan, William Van Gaal, Johan Verjans, Demetrius Voutnis, Victor Wayne, Peter Wilson, David Wong, Kirby Wong, John Younger, Gudrun Feuchtner, Siroos Mirzaei, Konrad Weiss, Natallia Maroz-Vadalazhskaya, Olivier Gheysens, Filip Homans, Rodrigo Moreno-Reyes, Agnès Pasquet, Veronique Roelants, Caroline M. Van De Heyning, Raúl Araujo Ríos, Valentina Soldat-Stankovic, Sinisa Stankovic, Maria Helena Albernaz Siqueira, Augusto Almeida, Paulo Henrique Alves Togni, Jose Henrique Andrade, Luciana Andrade, Carlos Anselmi, Roberta Araújo, Guilherme Azevedo, Sabbrina Bezerra, Rodrigo Biancardi, Gabriel Blacher Grossman, Simone Brandão, Diego Bromfman Pianta, Lara Carreira, Bruno Castro, Tien Chang, Fernando Cunali, Roberto Cury, Roberto Dantas, Fernando de Amorim Fernandes, Andrea De Lorenzo, Robson De Macedo Filho, Fernanda Erthal, Fabio Fernandes, Juliano Fernandes, Thiago Ferreira De Souza, Wilson Furlan Alves, Bruno Ghini, Luiz Goncalves, Ilan Gottlieb, Marcelo Hadlich, Vinícius Kameoka, Ronaldo Lima, Adna Lima, Rafael Willain Lopes, Ricardo Machado e Silva, Tiago Magalhães, Fábio Martins Silva, Luiz Eduardo Mastrocola, Fábio Medeiros, José Claudio Meneghetti, Vania Naue, Danilo Naves, Roberto Nolasco, Cesar Nomura, Joao Bruno Oliveira, Eduardo Paixao, Filipe Penna De Carvalho, Ibraim Pinto, Priscila Possetti, Mayra Quinta, Rodrigo Rizzo Nogueira Ramos, Ricardo Rocha, Alfredo Rodrigues, Carlos Rodrigues, Leila Romantini, Adelina Sanches, Sara Santana, Leonardo Sara da Silva, Paulo Schvartzman, Cristina Sebastião Matushita, Tiago Senra, Afonso Shiozaki, Maria Eduarda Menezes de Siqueira, Cristiano Siqueira, Paola Smanio, Carlos Eduardo Soares, José Soares Junior, Marcio Sommer Bittencourt, Bernardo Spiro, Cláudio Tinoco Mesquita, Jorge Torreao, Rafael Torres, Marly Uellendahl, Guilherme Urpia Monte, Otávia Veríssimo, Estevan Vieira Cabeda, Felipe Villela Pedras, Roberto Waltrick, Marcello Zapparoli, Hamid Naseer, Marina Garcheva-Tsacheva, Irena Kostadinova, Youdaline Theng, Gad Abikhzer, Rene Barette, Benjamin Chow, Dominique Dabreo, Matthias Friedrich, Ria Garg, Mohammed Nassoh Hafez, Chris Johnson, Marla Kiess, Jonathon Leipsic, Eugene Leung, Robert Miller, Anastasia Oikonomou, Stephan Probst, Idan Roifman, Gary Small, Vikas Tandon, Adwait Trivedi, James White, Katherine Zukotynski, Jose Canessa, Gabriel Castro Muñoz, Carmen Concha, Pablo Hidalgo, Cesar Lovera, Teresa Massardo, Luis Salazar Vargas, Pedro Abad, Harold Arturo, Sandra Ayala, Luis Benitez, Alberto Cadena, Carlos Caicedo, Antonio Calderón Moncayo, Sharon Gomez, Claudia T. Gutierrez Villamil, Claudia Jaimes, Juan Londoño, Juan Luis Londoño Blair, Luz Pabon, Mauricio Pineda, Juan Carlos Rojas, Diego Ruiz, Manuel Valencia Escobar, Andres Vasquez, Damiana Vergel, Alejandro Zuluaga, Isabel Berrocal Gamboa, Gabriel Castro, Ulises González, Ana Baric, Tonci Batinic, Maja Franceschi, Maja Hrabak Paar, Mladen Jukic, Petar Medakovic, Viktor Persic, Marina Prpic, Ante Punda, Juan Felipe Batista, Juan Manuel Gómez Lauchy, Yamile Marcos Gutierrez, Rayner Menéndez, Amalia Peix, Luis Rochela, Christoforos Panagidis, Ioannis Petrou, Vaclav Engelmann, Milan Kaminek, Vladimír Kincl, Otto Lang, Milan Simanek, Jawdat Abdulla, Morten Bøttcher, Mette Christensen, Lars Christian Gormsen, Philip Hasbak, Søren Hess, Paw Holdgaard, Allan Johansen, Kasper Kyhl, Bjarne Linde Norgaard, Kristian Altern Øvrehus, Niels Peter Rønnow Sand, Rolf Steffensen, Anders Thomassen, Bo Zerahn, Alfredo Perez, Giovanni Alejandro Escorza Velez, Mayra Sanchez Velez, Islam Shawky Abdel Aziz, Mahasen Abougabal, Taghreed Ahmed, Adel Allam, Ahmed Asfour, Mona Hassan, Alia Hassan, Ahmed Ibrahim, Sameh Kaffas, Ahmed Kandeel, Mohamed Mandour Ali, Ahmad Mansy, Hany Maurice, Sherif Nabil, Mahmoud Shaaban, Ana Camila Flores, Anne Poksi, Juhani Knuuti, Velipekka Kokkonen, Martti Larikka, Valtteri Uusitalo, Matthieu Bailly, Samuel Burg, Jean-François Deux, Vincent Habouzit, Fabien Hyafil, Olivier Lairez, Franck Proffit, Hamza Regaieg, Laure Sarda-Mantel, Vania Tacher, Roman P. Schneider, Harold Ayetey, George Angelidis, Aikaterini Archontaki, Sofia Chatziioannou, Ioannis Datseris, Christina Fragkaki, Panagiotis Georgoulias, Sophia Koukouraki, Maria Koutelou, Eleni Kyrozi, Evangelos Repasos, Petros Stavrou, Pipitsa Valsamaki, Carla Gonzalez, Goleat Gutierrez, Alejandro Maldonado, Klara Buga, Ildiko Garai, Pál Maurovich-Horvat, Erzsébet Schmidt, Balint Szilveszter, Edit Várady, Nilesh Banthia, Jinendra Kumar Bhagat, Rishi Bhargava, Vivek Bhat, Partha Choudhury, Vijay Sai Chowdekar, Aparna Irodi, Shashank Jain, Elizabeth Joseph, Sukriti Kumar, Prof Dr Girijanandan Mahapatra, Deepanjan Mitra, Bhagwant Rai Mittal, Ahmad Ozair, Chetan Patel, Tapan Patel, Ravi Patel, Shivani Patel, Sudhir Saxena, Shantanu Sengupta, Santosh Singh, Bhanupriya Singh, Ashwani Sood, Atul Verma, Erwin Affandi, Padma Savenadia Alam, Edison Edison, Gani Gunawan, Habusari Hapkido, Basuki Hidayat, Aulia Huda, Anggoro Praja Mukti, Djoko Prawiro, Erwin Affandi Soeriadi, Hilman Syawaluddin, Amjed Albadr, Majid Assadi, Farshad Emami, Golnaz Houshmand, Majid Maleki, Maryam Tajik Rostami, Seyed Rasoul Zakavi, Eed Abu Zaid, Svetlana Agranovich, Yoav Arnson, Rachel Bar-Shalom, Alex Frenkel, Galit Knafo, Rachel Lugassi, Israel Shlomo Maor Moalem, Maya Mor, Noam Muskal, Sara Ranser, Aryeh Shalev, Domenico Albano, Pierpaolo Alongi, Gaspare Arnone, Elisa Bagatin, Sergio Baldari, Matteo Bauckneht, Paolo Bertelli, Francesco Bianco, Rachele Bonfiglioli, Roberto Boni, Andrea Bruno, Isabella Bruno, Elena Busnardo, Elena Califaretti, Luca Camoni, Aldo Carnevale, Roberta Casoni, Armando Ugo Cavallo, Giorgio Cavenaghi, Franca Chierichetti, Marcello Chiocchi, Corrado Cittanti, Mauro Colletta, Umberto Conti, Alberto Cossu, Alberto Cuocolo, Marco Cuzzocrea, Maria Luisa De Rimini, Giuseppe De Vincentis, Eleonora Del Giudice, Alberico Del Torto, Veronica Della Tommasina, Rexhep Durmo, Paola Anna Erba, Laura Evangelista, Riccardo Faletti, Evelina Faragasso, Mohsen Farsad, Paola Ferro, Luigia Florimonte, Viviana Frantellizzi, Fabio Massimo Fringuelli, Marco Gatti, Angela Gaudiano, Alessia Gimelli, Raffaele Giubbini, Francesca Giuffrida, Salvatore Ialuna, Riccardo Laudicella, Lucia Leccisotti, Lucia Leva, Riccardo Liga, Carlo Liguori, Giampiero Longo, Margherita Maffione, Maria Elisabetta Mancini, Claudio Marcassa, Elisa Milan, Barbara Nardi, Sara Pacella, Giovanna Pepe, Gianluca Pontone, Sabina Pulizzi, Natale Quartuccio, Lucia Rampin, Fabrizio Ricci, Pierluigi Rossini, Giuseppe Rubini, Vincenzo Russo, Gian Mauro Sacchetti, Gianmario Sambuceti, Massimo Scarano, Roberto Sciagrà, Massimiliano Sperandio, Antonella Stefanelli, Guido Ventroni, Stefania Zoboli, Dainia Baugh, Duane Chambers, Ernest Madu, Felix Nunura, Hiroshi Asano, Chimura Misato Chimura, Shinichiro Fujimoto, Koichiro Fujisue, Tomohisa Fukunaga, Yoshimitsu Fukushima, Kae Fukuyama, Jun Hashimoto, Yasutaka Ichikawa, Nobuo Iguchi, Masamichi Imai, Anri Inaki, Hayato Ishimura, Satoshi Isobe, Toshiaki Kadokami, Takao Kato, Shinichiro Kumita, Hirotaka Maruno, Hiroyuki Mataki, Masao Miyagawa, Ryota Morimoto, Masao Moroi, Shigeki Nagamachi, Kenichi Nakajima, Tomoaki Nakata, Ryo Nakazato, Mamoru Nanasato, Masanao Naya, Takashi Norikane, Yasutoshi Ohta, Satoshi Okayama, Atsutaka Okizaki, Yoichi Otomi, Hideki Otsuka, Masaki Saito, Sakata Yasushi Sakata, Masayoshi Sarai, Daisuke Sato, Shinya Shiraishi, Yoshinobu Suwa, Kentaro Takanami, Kazuya Takehana, Junichi Taki, Nagara Tamaki, Yasuyo Taniguchi, Hiroki Teragawa, Nobuo Tomizawa, Kenichi Tsujita, Kyoko Umeji, Yasushi Wakabayashi, Shinichiro Yamada, Shinya Yamazaki, Tatsuya Yoneyama, Mohammad Rawashdeh, Daultai Batyrkhanov, Khalid Makhdomi, Kevin Ombati, Faridah Alkandari, Masoud Garashi, Tchoyoson Lim Coie, Sonexay Rajvong, Artem Kalinin, Marika Kalnina, Mohamad Haidar, Renata Komiagiene, Giedre Kviecinskiene, Mindaugas Mataciunas, Donatas Vajauskas, Christian Picard, Noor Khairiah A. Karim, Luise Reichmuth, Anthony Samuel, Mohammad Aaftaab Allarakha, Ambedhkar Shantaram Naojee, Erick Alexanderson-Rosas, Erika Barragan, Alejandro Becerril González-Montecinos, Manuel Cabada, Daniel Calderon Rodriguez, Isabel Carvajal-Juarez, Violeta Cortés, Filiberto Cortés, Erasmo De La Peña, Manlio Gama-Moreno, Luis González, Nelsy Gonzalez Ramírez, Moisés Jiménez-Santos, Luis Matos, Edgar Monroy, Martha Morelos, Mario Ornelas, Jose Alberto Ortga Ramirez, Andrés Preciado-Anaya, Óscar Ulises Preciado-Gutiérrez, Adriana Puente Barragan, Sandra Graciela Rosales Uvera, Sigelinda Sandoval, Miguel Santaularia Tomas, Lilia M. 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Bayer, Adam Bernheim, Sabha Bhatti, Erik Bieging, Ron Blankstein, Stephen Bloom, Sean Blue, David Bluemke, Andressa Borges, Kelley Branch, Paco Bravo, Jessica Brothers, Matthew Budoff, Renée Bullock-Palmer, Angela Burandt, Floyd W. Burke, Kelvin Bush, Candace Candela, Elizabeth Capasso, Joao Cavalcante, Donald Chang, Saurav Chatterjee, Yiannis Chatzizisis, Michael Cheezum, Tiffany Chen, Jennifer Chen, Marcus Chen, James Clarcq, Ayreen Cordero, Matthew Crim, Sorin Danciu, Bruce Decter, Nimish Dhruva, Neil Doherty, Rami Doukky, Anjori Dunbar, William Duvall, Rachael Edwards, Kerry Esquitin, Husam Farah, Emilio Fentanes, Maros Ferencik, Daniel Fisher, Daniel Fitzpatrick, Cameron Foster, Tony Fuisz, Michael Gannon, Lori Gastner, Myron Gerson, Brian Ghoshhajra, Alan Goldberg, Brian Goldner, Jorge Gonzalez, Rosco Gore, Sandra Gracia-López, Fadi Hage, Agha Haider, Sofia Haider, Yasmin Hamirani, Karen Hassen, Mallory Hatfield, Carolyn Hawkins, Katie Hawthorne, Nicholas Heath, Robert Hendel, Phillip Hernandez, Gregory Hill, Stephen Horgan, Jeff Huffman, Lynne Hurwitz, Ami Iskandrian, Rajesh Janardhanan, Christine Jellis, Scott Jerome, Dinesh Kalra, Summanther Kaviratne, Fernando Kay, Faith Kelly, Omar Khalique, Mona Kinkhabwala, George Kinzfogl Iii, Jacqueline Kircher, Rachael Kirkbride, Michael Kontos, Anupama Kottam, Joseph Krepp, Jay Layer, Steven H. Lee, Jeffrey Leppo, John Lesser, Steve Leung, Howard Lewin, Diana Litmanovich, Yiyan Liu, Kathleen Magurany, Jeremy Markowitz, Amanda Marn, Stephen E. Matis, Michael Mckenna, Tony Mcrae, Fernando Mendoza, Michael Merhige, David Min, Chanan Moffitt, Karen Moncher, Warren Moore, Shamil Morayati, Michael Morris, Mahmud Mossa-Basha, Zorana Mrsic, Venkatesh Murthy, Prashant Nagpal, Kyle Napier, Katarina Nelson, Prabhjot Nijjar, Medhat Osman, Edward Passen, Amit Patel, Pravin Patil, Ryan Paul, Lawrence Phillips, Venkateshwar Polsani, Rajaram Poludasu, Brian Pomerantz, Thomas Porter, Ryan Prentice, Amit Pursnani, Mark Rabbat, Suresh Ramamurti, Florence Rich, Hiram Rivera Luna, Austin Robinson, Kim Robles, Cesar Rodríguez, Mark Rorie, John Rumberger, Raymond Russell, Philip Sabra, Diego Sadler, Mary Schemmer, U. Joseph Schoepf, Samir Shah, Nishant Shah, Sujata Shanbhag, Gaurav Sharma, Steven Shayani, Jamshid Shirani, Pushpa Shivaram, Steven Sigman, Mitch Simon, Ahmad Slim, David Smith, Alexandra Smith, Prem Soman, Aditya Sood, Monvadi Barbara Srichai-Parsia, James Streeter, Albert T, Ahmed Tawakol, Dustin Thomas, Randall Thompson, Tara Torbet, Desiree Trinidad, Shawn Ullery, Samuel Unzek, Seth Uretsky, Srikanth Vallurupalli, Vikas Verma, Alfonso Waller, Ellen Wang, Parker Ward, Gaby Weissman, George Wesbey, Kelly White, David Winchester, David Wolinsky, Sandra Yost, Michael Zgaljardic, Omar Alonso, Mario Beretta, Rodolfo Ferrando, Miguel Kapitan, Fernando Mut, Omoa Djuraev, Gulnora Rozikhodjaeva, Ha Le Ngoc, Son Hong Mai, Xuan Canh Nguyen, Kudo, T, Lahey, R, Hirschfeld, C, Williams, M, Lu, B, Alasnag, M, Bhatia, M, Henry Bom, H, Dautov, T, Fazel, R, Karthikeyan, G, Keng, F, Rubinshtein, R, Better, N, Cerci, R, Dorbala, S, Raggi, P, Shaw, L, Villines, T, Vitola, J, Choi, A, Malkovskiy, E, 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Subjects: medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Heart disease, business.industry, cardiac testing, coronavirus, COVID-19, global health, Disease, medicine.disease_cause, medicine.disease, coronaviru, cardiovascular disease, RC666-701, Emergency medicine, Pandemic, medicine, Global health, Diseases of the circulatory (Cardiovascular) system, business, Coronavirus
Abstract: Background: The coronavirus disease-2019 (COVID-19) pandemic significantly affected management of cardiovascular disease around the world. The effect of the pandemic on volume of cardiovascular diagnostic procedures is not known. Objectives: This study sought to evaluate the effects of the early phase of the COVID-19 pandemic on cardiovascular diagnostic procedures and safety practices in Asia. Methods: The International Atomic Energy Agency conducted a worldwide survey to assess changes in cardiovascular procedure volume and safety practices caused by COVID-19. Testing volumes were reported for March 2020 and April 2020 and were compared to those from March 2019. Data from 180 centers across 33 Asian countries were grouped into 4 subregions for comparison. Results: Procedure volumes decreased by 47% from March 2019 to March 2020, showing recovery from March 2020 to April 2020 in Eastern Asia, particularly in China. The majority of centers cancelled outpatient activities and increased time per study. Practice changes included implementing physical distancing and restricting visitors. Although COVID testing was not commonly performed, it was conducted in one-third of facilities in Eastern Asia. The most severe reductions in procedure volumes were observed in lower-income countries, where volumes decreased 81% from March 2019 to April 2020. Conclusions: The COVID-19 pandemic in Asia caused significant reductions in cardiovascular diagnostic procedures, particularly in low-income countries. Further studies on effects of COVID-19 on cardiovascular outcomes and changes in care delivery are warranted.
Published: 2021

18. Impact of COVID-19 on Diagnostic Cardiac Procedural Volume in Oceania: The IAEA Non-Invasive Cardiology Protocol Survey on COVID-19 (INCAPS COVID)

Author: O'Sullivan, P., Younger, J., Van Pelt, N., O'Malley, S., Lenturut-Katal, D., Hirschfeld, C. B., Vitola, J. V., Cerci, R., Williams, M. C., Shaw, L. J., Raggi, P., Villines, T. C., Dorbala, S., Choi, A. D., Cohen, Y., Goebel, B., Malkovskiy, E., Randazzo, M., Pascual, T. N. B., Pynda, Y., Dondi, M., Paez, D., Einstein, A. J., Better, N., Afghanistan: Mohammad Nawaz Nasery Albania: Artan Goda, Ervina Shirka Algeria: Rabie Benlabgaa, Salah, Bouyoucef, Abdelkader, Medjahedi, Qais Nailli Argentina: Mariela Agolti, Roberto Nicolas Aguero, Maria del Carmen Alak, Lucia Graciela Alberguina, Guillermo, Arroñada, Andrea, Astesiano, Alfredo, Astesiano, Carolina Bas Norton, Pablo, Benteo, Juan, Blanco, Juan Manuel Bonelli, Jose Javier Bustos, Raul, Cabrejas, Jorge, Cachero, Roxana, Campisi, Alejandro, Canderoli, Silvia, Carames, Patrícia, Carrascosa, Ricardo, Castro, Oscar, Cendoya, Luciano Martin Cognigni, Carlos, Collaud, Claudia, Cortes, Javier, Courtis, Daniel, Cragnolino, Mariana, Daicz, Alejandro De La Vega, Silvia Teresa De Maria, Horacio Del Riego, Fernando, Dettori, Alejandro, Deviggiano, Laura, Dragonetti, Mario, Embon, Ruben Emilio Enriquez, Jorge, Ensinas, Fernando, Faccio, Adolfo, Facello, Diego, Garofalo, Ricardo, Geronazzo, Natalia, Gonza, Lucas, Gutierrez, Miguel Angel Guzzo, Victor, Hasbani, Melina, Huerin, Victor, Jäger, Julio Manuel Lewkowicz, Maria Nieves, A López De Munaín, Jose Maria Lotti, Alejandra, Marquez, Osvaldo, Masoli, Osvaldo Horacio Masoli, Edgardo, Mastrovito, Matias, Mayoraz, Graciela Eva Melado, Anibal, Mele, Maria Fernanda Merani, Alejandro Horacio Meretta, Susana, Molteni, Marcos, Montecinos, Eduardo, Noguera, Carlos, Novoa, Claudio Pereyra Sueldo, Sebastian Perez Ascani, Pablo, Pollono, Maria Paula Pujol, Alejandro, Radzinschi, Gustavo, Raimondi, Marcela, Redruello, Marina, Rodríguez, Matías, Rodríguez, Romina Lorena Romero, Arturo Romero Acuña, Federico, Rovaletti, Lucas San Miguel, Lucrecia, Solari, Bruno, Strada, Sonia, Traverso, Sonia Simona Traverzo, Maria del Huerto Velazquez Espeche, Juan Sebastian Weihmuller, Juan, Wolcan, Susana Zeffiro Armenia: Mari Sakanyan Australia: Scott Beuzeville, Raef, Boktor, Patrick, Butler, Jennifer, Calcott, Loretta, Carr, Virgil, Chan, Charles, Chao, Woon, Chong, Mark, Dobson, D'Arne, Downie, Girish, Dwivedi, 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Maroz-Vadalazhskaya Belgium: Olivier Gheysens, Filip, Homans, Rodrigo, Moreno-Reyes, Agnès, Pasquet, Veronique, Roelants, Van De Heyning Bolivia: Raúl Araujo Ríos Bosnia - Herzegovina: Valentina Soldat-Stankovic, Caroline M., Sinisa Stankovic Brazil: Maria Helena Albernaz Siqueira, Augusto, Almeida, Paulo Henrique Alves Togni, Jose Henrique Andrade, Luciana, Andrade, Carlos, Anselmi, Roberta, Araújo, Guilherme, Azevedo, Sabbrina, Bezerra, Rodrigo, Biancardi, Gabriel Blacher Grossman, Simone, Brandão, Diego Bromfman Pianta, Lara, Carreira, Bruno, Castro, Tien, Chang, Fernando Cunali, Jr., Roberto, Cury, Roberto, Dantas, Fernando de Amorim Fernandes, Andrea De Lorenzo, Robson De Macedo Filho, Fernanda, Erthal, Fabio, Fernandes, Juliano, Fernandes, Thiago Ferreira De Souza, Wilson Furlan Alves, Bruno, Ghini, Luiz, Goncalves, Ilan, Gottlieb, Marcelo, Hadlich, Vinícius, Kameoka, Ronaldo, Lima, Adna, Lima, Rafael Willain Lopes, Ricardo Machado, e Silva, Tiago, Magalhães, Fábio Martins Silva, Luiz Eduardo Mastrocola, Fábio, Medeiros, José Claudio Meneghetti, Vania, Naue, Danilo, Naves, Roberto, Nolasco, Cesar, Nomura, Joao Bruno Oliveira, Eduardo, Paixao, Filipe Penna De Carvalho, Ibraim, Pinto, Priscila, Possetti, Mayra, Quinta, Rodrigo Rizzo Nogueira Ramos, Ricardo, Rocha, Alfredo, Rodrigues, Carlos, Rodrigues, Leila, Romantini, Adelina, Sanches, Sara, Santana, Leonardo Sara da Silva, Paulo, Schvartzman, Cristina Sebastião Matushita, Tiago, Senra, Afonso, Shiozaki, Maria Eduarda Menezes de Siqueira, Cristiano, Siqueira, Paola, Smanio, Carlos Eduardo Soares, José Soares Junior, Marcio Sommer Bittencourt, Bernardo, Spiro, Cláudio Tinoco Mesquita, Jorge, Torreao, Rafael, Torres, Marly, Uellendahl, Guilherme Urpia Monte, Otávia, Veríssimo, Estevan Vieira Cabeda, Felipe Villela Pedras, Roberto, Waltrick, Marcello Zapparoli Brunei Darussalam: Hamid Naseer Bulgaria: Marina Garcheva-Tsacheva, Irena Kostadinova Cambodia: Youdaline Theng Canada: Gad Abikhzer, Rene, Barette, Benjamin, Chow, Dominique, Dabreo, Matthias, Friedrich, Ria, Garg, Mohammed Nassoh Hafez, Chris, Johnson, Marla, Kiess, Jonathon, Leipsic, Eugene, Leung, Robert, Miller, Anastasia, Oikonomou, Stephan, Probst, Idan, Roifman, Gary, Small, Vikas, Tandon, Adwait, Trivedi, James, White, Katherine Zukotynski Chile: Jose Canessa, Gabriel Castro Muñoz, Carmen, Concha, Pablo, Hidalgo, Cesar, Lovera, Teresa, Massardo, Luis Salazar Vargas Colombia: Pedro Abad, Harold, Arturo, Sandra, Ayala, Luis, Benitez, Alberto, Cadena, Carlos, Caicedo, Antonio Calderón Moncayo, Sharon, Gomez, Gutierrez Villamil, Claudia T., Claudia, Jaimes, Juan, Londoño, Juan Luis Londoño Blair, Luz, Pabon, Mauricio, Pineda, Juan Carlos Rojas, Diego, Ruiz, Manuel Valencia Escobar, Andres, Vasquez, Damiana, Vergel, Alejandro Zuluaga Costa Rica: Isabel Berrocal Gamboa, Gabriel, Castro, Ulises, González, Croatia: Ana Baric, Tonci, Batinic, Maja, Franceschi, Maja Hrabak Paar, Mladen, Jukic, Petar, Medakovic, Viktor, Persic, Marina, Prpic, Ante Punda Cuba: Juan Felipe Batista, Juan Manuel Gómez Lauchy, Yamile Marcos Gutierrez, Rayner, Menéndez, Amalia, Peix, Luis Rochela Cyprus: Christoforos Panagidis, Ioannis Petrou Czech Republic: Vaclav Engelmann, Milan, Kaminek, Vladimír, Kincl, Otto, Lang, Milan Simanek Denmark: Jawdat Abdulla, Morten, Bøttcher, Mette, Christensen, Lars Christian Gormsen, Philip, Hasbak, Søren, Hess, Paw, Holdgaard, Allan, Johansen, Kasper, Kyhl, Bjarne Linde Norgaard, Kristian Altern Øvrehus, Niels Peter Rønnow Sand, Rolf, Steffensen, Anders, Thomassen, Bo Zerahn Dominican Republic: Alfredo Perez Ecuador: Giovanni Alejandro Escorza Velez, Mayra Sanchez Velez Egypt: Islam Shawky Abdel Aziz, Mahasen, Abougabal, Taghreed, Ahmed, Adel, Allam, Ahmed, Asfour, Mona, Hassan, Alia, Hassan, Ahmed, Ibrahim, Sameh, Kaffas, Ahmed, Kandeel, Mohamed Mandour Ali, Ahmad, Mansy, Hany, Maurice, Sherif, Nabil, Mahmoud Shaaban El Salvador: Ana Camila Flores Estonia: Anne Poksi Finland: Juhani Knuuti, Velipekka, Kokkonen, Martti, Larikka, Valtteri Uusitalo France: Matthieu Bailly, Samuel, Burg, Jean-François, Deux, Vincent, Habouzit, Fabien, Hyafil, Olivier, Lairez, Franck, Proffit, Hamza, Regaieg, Laure, Sarda-Mantel, Schneider Ghana: Harold Ayetey Greece: George Angelidis, Vania Tacher Germany: Roman P., Aikaterini, Archontaki, Sofia, Chatziioannou, Ioannis, Datseris, Christina, Fragkaki, Panagiotis, Georgoulias, Sophia, Koukouraki, Maria, Koutelou, Eleni, Kyrozi, Evangelos, Repasos, Petros, Stavrou, Pipitsa Valsamaki Guatemala: Carla Gonzalez, Goleat Gutierrez Honduras: Alejandro Maldonado Hungary: Klara Buga, Ildiko, Garai, Pál, Maurovich-Horvat, Erzsébet, Schmidt, Balint, Szilveszter, Edit Várady India: Nilesh Banthia, Jinendra Kumar Bhagat, Rishi, Bhargava, Vivek, Bhat, Mona, Bhatia, Partha, Choudhury, Vijay Sai Chowdekar, Aparna, Irodi, Shashank, Jain, Elizabeth, Joseph, Sukriti, Kumar, Prof Dr Girijanandan Mahapatra, Deepanjan, Mitra, Bhagwant Rai Mittal, Ahmad, Ozair, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Patel, Sudhir, Saxena, Shantanu, Sengupta, Santosh, Singh, Bhanupriya, Singh, Ashwani, Sood, Atul Verma Indonesia: Erwin Affandi, Padma Savenadia Alam, Edison, Edison, Gani, Gunawan, Habusari, Hapkido, Basuki, Hidayat, Aulia, Huda, Anggoro Praja Mukti, Djoko, Prawiro, Erwin Affandi Soeriadi, Hilman Syawaluddin Iraq: Amjed Albadr Islamic Republic of Iran: Majid Assadi, Farshad, Emami, Golnaz, Houshmand, Majid, Maleki, Maryam Tajik Rostami, Seyed Rasoul Zakavi Israel: Eed Abu Zaid, Svetlana, Agranovich, Yoav, Arnson, Rachel, Bar-Shalom, Alex, Frenkel, Galit, Knafo, Rachel, Lugassi, Israel Shlomo Maor Moalem, Maya, Mor, Noam, Muskal, Sara, Ranser, Aryeh Shalev Italy: Domenico Albano, Pierpaolo, Alongi, Gaspare, Arnone, Elisa, Bagatin, Sergio, Baldari, Matteo, Bauckneht, Paolo, Bertelli, Francesco, Bianco, Rachele, Bonfiglioli, Roberto, Boni, Andrea, Bruno, Isabella, Bruno, Elena, Busnardo, Elena, Califaretti, Luca, Camoni, Aldo, Carnevale, Roberta, Casoni, Armando Ugo Cavallo, Giorgio, Cavenaghi, Franca, Chierichetti, Marcello, Chiocchi, Corrado, Cittanti, Mauro, Colletta, Umberto, Conti, Alberto, Cossu, Alberto, Cuocolo, Marco, Cuzzocrea, Maria Luisa De Rimini, Giuseppe De Vincentis, Eleonora Del Giudice, Alberico Del Torto, Veronica Della Tommasina, Rexhep, Durmo, Erba, PAOLA ANNA, Laura, Evangelista, Riccardo, Faletti, Evelina, Faragasso, Mohsen, Farsad, Paola, Ferro, Luigia, Florimonte, Viviana, Frantellizzi, Fabio Massimo Fringuelli, Marco, Gatti, Angela, Gaudiano, Alessia, Gimelli, Raffaele, Giubbini, Francesca, Giuffrida, Salvatore, Ialuna, Riccardo, Laudicella, Lucia, Leccisotti, Lucia, Leva, Liga, Riccardo, Carlo, Liguori, Giampiero, Longo, Margherita, Maffione, Maria Elisabetta Mancini, Claudio, Marcassa, Elisa, Milan, Barbara, Nardi, Sara, Pacella, Giovanna, Pepe, Gianluca, Pontone, Sabina, Pulizzi, Natale, Quartuccio, Lucia, Rampin, Fabrizio, Ricci, Pierluigi, Rossini, Giuseppe, Rubini, Vincenzo, Russo, Gian Mauro Sacchetti, Gianmario, Sambuceti, Massimo, Scarano, Roberto, Sciagrà, Massimiliano, Sperandio, Antonella, Stefanelli, Guido, Ventroni, Stefania Zoboli Jamaica: Dainia Baugh, Duane, Chambers, Ernest, Madu, Felix Nunura Japan: Hiroshi Asano, Chimura Misato Chimura, Shinichiro, Fujimoto, Koichiro, Fujisue, Tomohisa, Fukunaga, Yoshimitsu, Fukushima, Kae, Fukuyama, Jun, Hashimoto, Yasutaka, Ichikawa, Nobuo, Iguchi, Masamichi, Imai, Anri, Inaki, Hayato, Ishimura, Satoshi, Isobe, Toshiaki, Kadokami, Takao, Kato, Takashi, Kudo, Shinichiro, Kumita, Hirotaka, Maruno, Hiroyuki, Mataki, Masao, Miyagawa, Ryota, Morimoto, Masao, Moroi, Shigeki, Nagamachi, Kenichi, Nakajima, Tomoaki, Nakata, Ryo, Nakazato, Mamoru, Nanasato, Masanao, Naya, Takashi, Norikane, Yasutoshi, Ohta, Satoshi, Okayama, Atsutaka, Okizaki, Yoichi, Otomi, Hideki, Otsuka, Masaki, Saito, Sakata Yasushi Sakata, Masayoshi, Sarai, Daisuke, Sato, Shinya, Shiraishi, Yoshinobu, Suwa, Kentaro, Takanami, Kazuya, Takehana, Junichi, Taki, Nagara, Tamaki, Yasuyo, Taniguchi, Hiroki, Teragawa, Nobuo, Tomizawa, Kenichi, Tsujita, Kyoko, Umeji, Yasushi, Wakabayashi, Shinichiro, Yamada, Shinya, Yamazaki, Tatsuya Yoneyama Jordan: Mohammad Rawashdeh Kazakhstan: Daultai Batyrkhanov, Tairkhan Dautov Kenya: Khalid Makhdomi, Kevin Ombati Kuwait: Faridah Alkandari, Masoud Garashi Lao People's Democratic Republic: Tchoyoson Lim Coie, Sonexay Rajvong Latvia: Artem Kalinin, Marika Kalnina Lebanon: Mohamad Haidar Lithuania: Renata Komiagiene, Giedre, Kviecinskiene, Mindaugas, Mataciunas, Karim Malta: Luise Reichmuth, Donatas Vajauskas Luxembourg: Christian Picard Malaysia: Noor Khairiah A., Anthony Samuel Mauritius: Mohammad Aaftaab Allarakha, Ambedhkar Shantaram Naojee Mexico: Erick Alexanderson-Rosas, Erika, Barragan, Alejandro Becerril González-Montecinos, Manuel, Cabada, Daniel Calderon Rodriguez, Isabel, Carvajal-Juarez, Violeta, Cortés, Filiberto, Cortés, Erasmo De La Peña, Manlio, Gama-Moreno, Luis, González, Nelsy Gonzalez Ramírez, Moisés, Jiménez-Santos, Luis, Matos, Edgar, Monroy, Martha, Morelos, Mario, Ornelas, Jose Alberto Ortga Ramirez, Andrés, Preciado-Anaya, Óscar Ulises Preciado-Gutiérrez, Adriana Puente Barragan, Sandra Graciela Rosales Uvera, Sigelinda, Sandoval, Miguel Santaularia Tomas, Sierra-Galan, Lilia M., Silvia, Siu, Enrique, Vallejo, Mario Valles Monaco: Marc Faraggi Mongolia: Erdenechimeg Sereegotov Montenegro: Srdja Ilic Morocco: Nozha Ben-Rais, Nadia Ismaili Alaoui, Sara Taleb Myanmar: Khin Pa Pa Myo, Phyo Si Thu Nepal: Ram Kumar Ghimire, Bijoy Rajbanshi Netherlands: Peter Barneveld, Andor, Glaudemans, Jesse, Habets, Klaas Pieter Koopmans, Jeroen, Manders, Stefan, Pool, Arthur, Scholte, Asbjørn, Scholtens, Riemer, Slart, Paul, Thimister, Erik-Jan Van Asperen, Niels, Veltman, Derk, Verschure, Nils Wagenaar New Zealand: John Edmond, Chris, Ellis, Kerryanne, Johnson, Ross, Keenan, Shaw Hua (Anthony) Kueh, Christopher, Occleshaw, Alexander, Sasse, Andrew, To, Niels Van Pelt, Calum Young Nicaragua: Teresa Cuadra, Hector Bladimir Roque Vanegas Niger: Idrissa Adamou Soli, Djibrillou Moussa Issoufou Nigeria: Tolulope Ayodele, Chibuzo, Madu, Yetunde Onimode Norway: Elen Efros-Monsen, Signe Helene Forsdahl, Jenni-Mari Hildre Dimmen, Arve, Jørgensen, Isabel, Krohn, Pål, Løvhaugen, Anders Tjellaug Bråten Oman: Humoud Al Dhuhli, Faiza Al Kindi, Naeema, Al-Bulushi, Zabah, Jawa, Naima Tag Pakistan: Muhammad Shehzad Afzal, Shazia, Fatima, Muhammad Numair Younis, Musab, Riaz, Mohammad Saadullah Panama: Yariela Herrera Papua New Guinea: Dora Lenturut-Katal Paraguay: Manuel Castillo Vázquez, José Ortellado People's Republic of Bangladesh: Afroza Akhter People's Republic of China: Dianbo Cao, Stephen, Cheung, Dai, Xu, Lianggeng, Gong, Dan, Han, Yang, Hou, Caiying, Li, Tao, Li, Dong, Li, Sijin, Li, Jinkang, Liu, Hui, Liu, Bin, Lu, Ming Yen Ng, Kai, Sun, Gongshun, Tang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wang, Jiang, Wu, Zhifang, Wu, Liming, Xia, Jiangxi, Xiao, Lei, Xu, Youyou, Yang, Yin, Wu, Jianqun, Yu, Yuan, Li, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhang, Li Zhu Peru: Ana Alfaro Philippines: Paz Abrihan, Asela, Barroso, Eric, Cruz, Marie Rhiamar Gomez, Vincent Peter Magboo, John Michael Medina, Jerry, Obaldo, Davidson, Pastrana, Christian Michael Pawhay, Alvin, Quinon, Jeanelle Margareth Tang, Bettina, Tecson, Kristine Joy Uson, Mila Uy Poland: Magdalena Kostkiewicz, Jolanta Kunikowska Portugal: Nuno Bettencourt, Guilhermina, Cantinho, Antonio Ferreira Qatar: Ghulam Syed Republic of Ireland: Samer Arnous, Said, Atyani, Angela, Byrne, Tadhg, Gleeson, David, Kerins, Conor, Meehan, David, Murphy, Mark, Murphy, John, Murray, Julie O'Brien Republic of Korea: Ji-In Bang, Henry, Bom, Sang-Geon, Cho, Chae Moon Hong, Su Jin Jang, Yong Hyu Jeong, Won Jun Kang, Ji-Young, Kim, Jaetae, Lee, Chang Kyeong Namgung, Young, So, Kyoung Sook Won Republic of North Macedonia: Venjamin Majstorov, Marija Vavlukis Republic of Slovenia: Barbara Gužic Salobir, Monika Štalc Romania: Theodora Benedek, Imre, Benedek, Raluca, Mititelu, Claudiu Adrian Stan Russian Federation: Alexey Ansheles, Olga, Dariy, Olga, Drozdova, Nina, Gagarina, Vsevolod Milyevich Gulyaev, Irina, Itskovich, Anatoly, Karalkin, Alexander, Kokov, Ekaterina, Migunova, Viktor, Pospelov, Daria, Ryzhkova, Guzaliya, Saifullina, Svetlana, Sazonova, Vladimir, Sergienko, Irina, Shurupova, Tatjana, Trifonova, Wladimir Yurievich Ussov, Margarita, Vakhromeeva, Nailya, Valiullina, Konstantin, Zavadovsky, Kirill Zhuravlev Saudi Arabia: Mirvat Alasnag, Subhani Okarvi Serbia: Dragana Sobic Saranovic Singapore: Felix Keng, Jia Hao Jason See, Ramkumar, Sekar, Min Sen Yew Slovak Republic: Andrej Vondrak South Africa: Shereen Bejai, George, Bennie, Ria, Bester, Gerrit, Engelbrecht, Osayande, Evbuomwan, Harlem, Gongxeka, Magritha Jv Vuuren, Mitchell, Kaplan, Purbhoo, Khushica, Hoosen, Lakhi, Lizette, Louw, Nico, Malan, Katarina, Milos, Moshe, Modiselle, Stuart, More, Mathava, Naidoo, Leonie, Scholtz, Mboyo Vangu Spain: Santiago Aguadé-Bruix, Isabel, Blanco, Antonio, Cabrera, Alicia, Camarero, Irene, Casáns-Tormo, Hug, Cuellar-Calabria, Albert, Flotats, Maria Eugenia Fuentes Cañamero, María Elia García, Amelia, Jimenez-Heffernan, Rubén, Leta, Javier Lopez Diaz, Luis, Lumbreras, Juan Javier Marquez-Cabeza, Francisco, Martin, Anxo Martinez de Alegria, Francisco, Medina, Maria Pedrera Canal, Virginia, Peiro, Virginia, Pubul-Nuñez, Juan Ignacio Rayo Madrid, Cristina Rodríguez Rey, Ricardo Ruano Perez, Joaquín, Ruiz, Gertrudis Sabatel Hernández, Ana, Sevilla, Nahla Zeidán Sri Lanka: Damayanthi Nanayakkara, Chandraguptha Udugama Sweden: Magnus Simonsson Switzerland: Hatem Alkadhi, Ronny Ralf Buechel, Peter, Burger, Luca, Ceriani, Bart De Boeck, Christoph, Gräni, Alix Juillet de Saint Lager Lucas, Kamani, Christel H., Nadine, Kawel-Boehm, Robert, Manka, Prior, John O., Axel, Rominger, Jean-Paul Vallée Thailand: Benjapa Khiewvan, Teerapon, Premprabha, Tanyaluck Thientunyakit Tunisia: Ali Sellem Turkey: Kemal Metin Kir, Haluk Sayman Uganda: Mugisha Julius Sebikali, Zerida Muyinda Ukraine: Yaroslav Kmetyuk, Pavlo, Korol, Olena, Mykhalchenko, Volodymyr, Pliatsek, Maryna Satyr United Arab Emirates: Batool Albalooshi, Mohamed Ismail Ahmed Hassan United Kingdom: Jill Anderson, Punit, Bedi, Thomas, Biggans, Anda, Bularga, Russell, Bull, Rajesh, Burgul, John-Paul, Carpenter, Duncan, Coles, David, Cusack, Aparna, Deshpande, John, Dougan, Timothy, Fairbairn, Alexia, Farrugia, Deepa, Gopalan, Alistair, Gummow, Prasad Guntur Ramkumar, Mark, Hamilton, Mark, Harbinson, Thomas, Hartley, Benjamin, Hudson, Nikhil, Joshi, Michael, Kay, Andrew, Kelion, Azhar, Khokhar, Jamie, Kitt, Ken, Lee, Chen, Low, Sze Mun Mak, Ntouskou, Marousa, Jon, Martin, Elisa, Mcalindon, Leon, Menezes, Gareth, Morgan-Hughes, Alastair, Moss, Anthony, Murray, Edward, Nicol, Dilip, Patel, Charles, Peebles, Francesca, Pugliese, Jonathan Carl Luis Rodrigues, Christopher, Rofe, Nikant, Sabharwal, Rebecca, Schofield, Thomas, Semple, Naveen, Sharma, Peter, Strouhal, Deepak, Subedi, William, Topping, Katharine, Tweed, Jonathan Weir-Mccall United States of America: Suhny Abbara, Taimur, Abbasi, Brian, Abbott, Shady, Abohashem, Sandra, Abramson, Tarek, Al-Abboud, Mouaz, Al-Mallah, Omar, Almousalli, Karthikeyan, Ananthasubramaniam, Mohan Ashok Kumar, Jeffrey, Askew, Lea, Attanasio, Mallory, Balmer-Swain, Bayer, Richard R., Adam, Bernheim, Sabha, Bhatti, Erik, Bieging, Ron, Blankstein, Stephen, Bloom, Sean, Blue, David, Bluemke, Andressa, Borges, Kelley, Branch, Paco, Bravo, Jessica, Brothers, Matthew, Budoff, Renée, Bullock-Palmer, Angela, Burandt, Burke, Floyd W., Kelvin, Bush, Candace, Candela, Elizabeth, Capasso, Joao, Cavalcante, Donald, Chang, Saurav, Chatterjee, Yiannis, Chatzizisis, Michael, Cheezum, Tiffany, Chen, Jennifer, Chen, Marcus, Chen, Andrew, Choi, James, Clarcq, Ayreen, Cordero, Matthew, Crim, Sorin, Danciu, Bruce, Decter, Nimish, Dhruva, Neil, Doherty, Rami, Doukky, Anjori, Dunbar, William, Duvall, Rachael, Edwards, Kerry, Esquitin, Husam, Farah, Emilio, Fentanes, Maros, Ferencik, Daniel, Fisher, Daniel, Fitzpatrick, Cameron, Foster, Tony, Fuisz, Michael, Gannon, Lori, Gastner, Myron, Gerson, Brian, Ghoshhajra, Alan, Goldberg, Brian, Goldner, Jorge, Gonzalez, Rosco, Gore, Sandra, Gracia-López, Fadi, Hage, Agha, Haider, Sofia, Haider, Yasmin, Hamirani, Karen, Hassen, Mallory, Hatfield, Carolyn, Hawkins, Katie, Hawthorne, Nicholas, Heath, Robert, Hendel, Phillip, Hernandez, Gregory, Hill, Stephen, Horgan, Jeff, Huffman, Lynne, Hurwitz, Ami, Iskandrian, Rajesh, Janardhanan, Christine, Jellis, Scott, Jerome, Dinesh, Kalra, Summanther, Kaviratne, Fernando, Kay, Faith, Kelly, Omar, Khalique, Mona, Kinkhabwala, George Kinzfogl Iii, Jacqueline, Kircher, Rachael, Kirkbride, Michael, Kontos, Anupama, Kottam, Joseph, Krepp, Jay, Layer, Steven, H Lee, Jeffrey, Leppo, John, Lesser, Steve, Leung, Howard, Lewin, Diana, Litmanovich, Yiyan, Liu, Juan, Lopez-Mattei, Kathleen, Magurany, Jeremy, Markowitz, Amanda, Marn, Stephen, E Matis, Michael, Mckenna, Tony, Mcrae, Fernando, Mendoza, Michael, Merhige, David, Min, Chanan, Moffitt, Karen, Moncher, Warren, Moore, Shamil, Morayati, Michael, Morris, Mahmud, Mossa-Basha, Zorana, Mrsic, Venkatesh, Murthy, Prashant, Nagpal, Kyle, Napier, Jagat, Narula, Katarina, Nelson, Prabhjot, Nijjar, Medhat, Osman, Purvi, Parwani, Edward, Passen, Amit, Patel, Pravin, Patil, Ryan, Paul, Lawrence, Phillips, Venkateshwar, Polsani, Rajaram, Poludasu, Brian, Pomerantz, Thomas, Porter, Ryan, Prentice, Amit, Pursnani, Mark, Rabbat, Suresh, Ramamurti, Florence, Rich, Hiram Rivera Luna, Austin, Robinson, Kim, Robles, Cesar, Rodríguez, Mark, Rorie, John, Rumberger, Raymond, Russell, Philip, Sabra, Diego, Sadler, Mary, Schemmer, Joseph Schoepf, U., Samir, Shah, Nishant, Shah, Sujata, Shanbhag, Gaurav, Sharma, Steven, Shayani, Jamshid, Shirani, Pushpa, Shivaram, Steven, Sigman, Mitch, Simon, Ahmad, Slim, David, Smith, Alexandra, Smith, Prem, Soman, Aditya, Sood, Monvadi Barbara Srichai-Parsia, James, Streeter, Albert, T, Ahmed, Tawakol, Dustin, Thomas, Randall, Thompson, Tara, Torbet, Desiree, Trinidad, Shawn, Ullery, Samuel, Unzek, Seth, Uretsky, Srikanth, Vallurupalli, Vikas, Verma, Alfonso, Waller, Ellen, Wang, Parker, Ward, Gaby, Weissman, George, Wesbey, Kelly, White, David, Winchester, David, Wolinsky, Sandra, Yost, Michael Zgaljardic Uruguay: Omar Alonso, Mario, Beretta, Rodolfo, Ferrando, Miguel, Kapitan, Fernando Mut Uzbekistan: Omoa Djuraev, Gulnora Rozikhodjaeva Vietnam: Ha Le Ngoc, Son Hong Mai, and Xuan Canh Nguyen
Subjects: Pulmonary and Respiratory Medicine, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Cardiology, coronavirus, 030204 cardiovascular system & hematology, Transoesophageal echocardiography, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Health care, Stress Echocardiography, Humans, Medicine, 030212 general & internal medicine, cardiac investigations, Pandemics, Cardiac imaging, Retrospective Studies, Cardiac investigations, Coronavirus, COVID-19, medicine.diagnostic_test, SARS-CoV-2, business.industry, Non invasive, cardiac imaging, humans, pandemics, retrospective studies, tomography, x-ray computed, cardiology, Positron emission tomography, Original Article, Tomography, X-Ray Computed, Cardiology and Cardiovascular Medicine, business, Cardiac Diagnostic Procedure
Abstract: OBJECTIVES: The INCAPS COVID Oceania study aimed to assess the impact caused by the COVID-19 pandemic on cardiac procedure volume provided in the Oceania region. METHODS: A retrospective survey was performed comparing procedure volumes within March 2019 (pre-COVID-19) with April 2020 (during first wave of COVID-19 pandemic). Sixty-three (63) health care facilities within Oceania that perform cardiac diagnostic procedures were surveyed, including a mixture of metropolitan and regional, hospital and outpatient, public and private sites, and 846 facilities outside of Oceania. The percentage change in procedure volume was measured between March 2019 and April 2020, compared by test type and by facility. RESULTS: In Oceania, the total cardiac diagnostic procedure volume was reduced by 52.2% from March 2019 to April 2020, compared to a reduction of 75.9% seen in the rest of the world (p
Published: 2021

19. Comparison Of On-site Clinician-operated Computational Fluid Dynamic 3Rd Generation Cffr For The Detection Of Lesion-specific Ischemia Compared To Invasive Ffr

Author: N. Gaikwad, C. Raffel, Christian Hamilton-Craig, C. Lynch, R. O'Rourke, S. Quadrelli, and M. Savage
Subjects: Lesion, medicine.medical_specialty, business.industry, medicine, Ischemia, Radiology, Nuclear Medicine and imaging, Radiology, medicine.symptom, Cardiology and Cardiovascular Medicine, medicine.disease, business
Published: 2021

20. E Machine learning wall thickness measurement in hypertrophic cardiomyopathy exceeds performance of world experts

Author: Chiara Bucciarelli-Ducci, Gianluca Pontone, Hunain Shiwani, Anish N Bhuva, Christian Hamilton Craig, Ntobeko A B Ntusi, João B Augusto, Luis R. Lopes, Steffen E. Petersen, Charlotte Manisty, Clement Lau, Peter P Swoboda, Rhodri H Davies, João L. Cavalcante, John P Greenwood, Gabriella Captur, Bernhard Gerber, Kristopher D Knott, Rebecca K. Hughes, Milind Y. Desai, Mashael Alfarih, Erik B. Schelbert, James C. Moon, and Andreas Seraphim
Subjects: Short axis, medicine.diagnostic_test, business.industry, Hypertrophic cardiomyopathy, Magnetic resonance imaging, Dilated cardiomyopathy, Repeatability, Machine learning, computer.software_genre, medicine.disease, Sample size determination, medicine, Artificial intelligence, business, Wall thickness, computer, Biological variability
Abstract: Background Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy (HCM), but measurement has variation. Objectives We developed a fully automated machine learning (ML) algorithm for MWT measurement and compared it to international experts using precision (repeatability) on a dataset of HCM patients scanned twice with cardiovascular magnetic resonance (CMR). Methods Training dataset: Endo- and epicardial end-diastolic contours were derived using a fully-automated convolutional neural network trained on 1,923 independent multi-centre multi-disease cases (14 centres from 3 countries, 10 scanner models, 2 field strengths, with balanced pathologies - health, athletes, myocardial infarction, aortic stenosis, HCM, dilated cardiomyopathy, infiltrative diseases) all segmented by a single expert. Patients: 60 HCM patients were scanned twice (scan:rescan) in the same session (no biological variability) at different field strengths and vendors (Siemens, GE, Philips) in 3 centres to allow generalizability. The protocol consisted of long axis cines and a short axis (SAX) bSSFP cine stack. Between scans, patients were brought out of the bore, repositioned on the table and re-isocentered. Wall thickness: MWT was measured in the SAX cine stack in end-diastole (scans A and B) by 11 experts (from 4 continents, 6 countries, 9 centers). For ML performance, the contours were based on a repurposed algorithm used for brain cortical thickness measurement, applying the Laplace equation for all contour points – effectively creating nested smoothly deforming surfaces from endo- to epicardium. We created orthogonal field lines to connect endo-and epicardial points, measured these distances and took the maximum as MWT. Results 1320 MWT measurements by experts were analyzed. Mean MWT varied significantly from 14.9 mm to 19.0 mm (Δ4.1 mm, p Conclusions ML MWT measurement in HCM is superior to all international experts studied with implications for risk stratification and sample sizes for clinical trials.
Published: 2020

21. Prognostic Value of Cardiac Magnetic Resonance Imaging in Acute Coronary Syndrome Patients With Troponin Elevation and Nonobstructive Coronary Arteries

Author: Owen Christopher Raffel, Tahlia C. Gadowski, Myo T. Lwin, Sushil Allen Luis, Christian Hamilton-Craig, Chris R. Luis, M. Habibian, and Jonathan Chan
Subjects: Male, Acute coronary syndrome, medicine.medical_specialty, Myocardial Infarction, Magnetic Resonance Imaging, Cine, Kaplan-Meier Estimate, Coronary Angiography, Risk Assessment, Cardiac magnetic resonance imaging, Predictive Value of Tests, Internal medicine, Medicine, Humans, cardiovascular diseases, Myocardial infarction, Acute Coronary Syndrome, Mortality, Heart Failure, biology, medicine.diagnostic_test, business.industry, Magnetic resonance imaging, General Medicine, Middle Aged, medicine.disease, Prognosis, Troponin, Coronary Vessels, Coronary arteries, medicine.anatomical_structure, Heart failure, cardiovascular system, biology.protein, Cardiology, Female, Myocardial infarction diagnosis, business, Cardiomyopathies, Follow-Up Studies
Abstract: Objective: To define the diagnostic yield of cardiac magnetic resonance (CMR) in differentiating the underlying causes of myocardial infarction with nonobstructive coronary arteries (MINOCA) and to determine the long-term prognostic implications of such diagnoses. Methods: Cardiac magnetic resonance evaluation was performed in 227 patients (mean age, 56.4±14.9 years; 120 [53%] female) with a “working diagnosis” of MINOCA as defined by presentation with a troponin-positive acute coronary syndrome (troponin I >0.04 μg/L) and nonobstructed coronary arteries between January 1, 2007, and February 28, 2013. Follow-up was performed to assess the primary composite end point of myocardial infarction, heart failure, and all-cause mortality. Results: Cardiac magnetic resonance identified nonstructural cardiomyopathies in 97 (43%) patients, myocardial infarction in 55 (24%) patients, structural cardiomyopathies in 27 (12%) patients, and pulmonary embolism in 1 patient. No CMR abnormalities were identified in the remaining patients. Kaplan-Meier analysis demonstrated the ability of a CMR diagnosis to predict the risk of the primary composite end point (P=.005) at 5-year follow-up. Worse outcomes were seen among patients with “true” MINOCA and a normal CMR image compared with those with CMR-confirmed myocardial infarction (P=.02). Use of antiplatelets (78% [37/45] vs 95% [52/55]; P=.01), beta blockers (56% [25/45] vs 82% [45/55]; P=.004), and statins (64% [29/45] vs 85% [47/55]; P=.01) was significantly lower in patients with true MINOCA with normal CMR imaging compared with those with CMR-confirmed myocardial infarction. Conclusions: Cardiac magnetic resonance carries a high diagnostic yield in patients with MINOCA and predicts long-term prognosis. Patients with MINOCA with normal CMR imaging had an increased rate of major adverse cardiac events and lower use of guideline-recommended myocardial infarction therapy compared with those with CMR-confirmed myocardial infarction.
Published: 2020

22. Left ventricular non-compaction in patients with single ventricle heart disease

Author: Rajesh Puranik, Wendy Strugnell, Shelby Kutty, Preeti Choudhary, David S. Celermajer, and Christian Hamilton-Craig
Subjects: Adult, Male, medicine.medical_specialty, Heart disease, Adolescent, Systole, Magnetic Resonance Imaging, Cine, 030204 cardiovascular system & hematology, Univentricular Heart, Ventricular Function, Left, 03 medical and health sciences, Basal (phylogenetics), Young Adult, 0302 clinical medicine, Predictive Value of Tests, Ventricular morphology, Internal medicine, medicine, Humans, In patient, 030212 general & internal medicine, Retrospective Studies, Ejection fraction, Isolated Noncompaction of the Ventricular Myocardium, Ventricular function, business.industry, Stroke Volume, General Medicine, medicine.disease, medicine.anatomical_structure, Ventricle, Heart failure, Pediatrics, Perinatology and Child Health, Cardiology, Female, Cardiology and Cardiovascular Medicine, business
Abstract: Objective:Left ventricular non-compaction is an architectural abnormality of the myocardium, associated with heart failure, systemic thromboembolism, and arrhythmia. We sought to assess the prevalence of left ventricular non-compaction in patients with single ventricle heart disease and its effects on ventricular function.Methods:Cardiac MRI of 93 patients with single ventricle heart disease (mean age 24 ± 8 years; 55% male) from three tertiary congenital centres was retrospectively reviewed; 65 of these had left ventricular morphology and are the subject of this report. The presence of left ventricular non-compaction was defined as having a non-compacted:compacted (NC:C) myocardial thickness ratio >2.3:1. The distribution of left ventricular non-compaction, ventricular volumes, and function was correlated with clinical data.Results:The prevalence of left ventricular non-compaction was 37% (24 of 65 patients) with a mean of 4 ± 2 affected segments. The distribution was apical in 100%, mid-ventricular in 29%, and basal in 17% of patients. Patients with left ventricular non-compaction had significantly higher end-diastolic (128 ± 44 versus 104 ± 46 mL/m2, p = 0.047) and end-systolic left ventricular volumes (74 ± 35 versus 56 ± 35 mL/m2, p = 0.039) with lower left ventricular ejection fraction (44 ± 11 versus 50 ± 9%, p = 0.039) compared to those with normal compaction. The number of segments involved did not correlate with ventricular function (p = 0.71).Conclusions:Left ventricular non-compaction is frequently observed in patients with left ventricle-type univentricular hearts, with predominantly apical and mid-ventricular involvement. The presence of non-compaction is associated with increased indexed end-diastolic volumes and impaired systolic function.
Published: 2020

23. Quantification of biventricular strain and assessment of ventriculo-ventricular interaction in pulmonary arterial hypertension using exercise cardiac magnetic resonance imaging and myocardial feature tracking

Author: Helen Seale, W. Strugnell, Aaron C.W. Lin, Christian Hamilton-Craig, and Norman R. Morris
Subjects: Pressure overload, Reproducibility, medicine.medical_specialty, education.field_of_study, Ejection fraction, medicine.diagnostic_test, business.industry, Population, Repeated measures design, Strain (injury), medicine.disease, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Cardiac magnetic resonance imaging, Internal medicine, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, education, business, Subclinical infection
Abstract: BACKGROUND Right ventricular (RV) failure is the main cause of mortality in pulmonary arterial hypertension (PAH). Exercise testing helps identify early RV maladaptation and systolic dysfunction and facilitates therapy. Myocardial strain has been shown to be more sensitive than ejection fraction (EF) in detecting subclinical ventricular contractile dysfunction. Chronic pressure overload in PAH had been associated with changes in left ventricular (LV) filling. PURPOSE To compare biventricular strains and ventriculo-ventricular interaction in PAH and controls using cardiac magnetic resonance feature tracking (cMRI-FT) and to determine the reproducibility of strain analysis. STUDY TYPE Prospective. POPULATION Nine PAH and nine control subjects. FIELD STRENGTH/SEQUENCE 1.5T MRI balanced steady state free precession. ASSESSMENT RV and LV longitudinal strain (EllRV and EllLV ) were derived using the mid-axial images. Radial (ErrLV ) and circumferential strain (EccLV ) were derived using the mid-ventricular short-axis images. Relationships between strain and volumetric parameters were assessed at rest and during submaximal in-magnet exercise. STATISTICAL TESTS Comparison of rest-to-exercise data between PAH and controls was analyzed using two-way repeated measures analysis of variance. The relationship between volumetric parameters and cMRI-FT were assessed using Pearson's correlation. Reproducibility was assessed by using Bland-Altman plots. RESULTS PAH had significantly lower EllRV at rest (-16.6 ± 2.7 vs. -20.1 ± 3.6, P = 0.03) despite normal RVEF. During exercise, RV systolic contractile reserve measured by EllRV was significantly reduced in PAH (PInteraction = 0.02). In PAH, indexed RV end-systolic volume (ESVi) significantly correlated with EccLV and ErrLV at rest (r = -0.65 and r = -0.70, P < 0.05) and with ErrLV during exercise (r = -0.43, P < 0.05). High observer agreement was demonstrated. DATA CONCLUSION Despite normal resting RVEF, RV systolic function and contractile reserve as measured by EllRV was significantly reduced in PAH. The close relation between RVESVi with EccLV and ErrLV provides evidence of systolic ventriculo-ventricular interaction in PAH. Exercise cMRI-FT may provide a quantitative metric for detection of subclinical RV dysfunction in PAH. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1427-1436.
Published: 2018

24. Coronary CT in Australia has high positive predictive value unaffected by site volume: An analysis of 510 positive CTCA scans with invasive angiographic correlation

Author: Darren L. Walters, Christian Hamilton-Craig, Michael P. Fletcher, Rachael O'Rourke, and N. Gaikwad
Subjects: Positive predictive value, lcsh:Diseases of the circulatory (Cardiovascular) system, Diagnostic accuracy, 030204 cardiovascular system & hematology, Correlation, 03 medical and health sciences, 0302 clinical medicine, medicine, Cardiac CT, 030212 general & internal medicine, Coronary CT angiography, Accuracy, Original Paper, medicine.diagnostic_test, business.industry, Coronary ct, Significant difference, CCTA, Coronary ct angiography, CTCA, Predictive value, lcsh:RC666-701, Angiography, Cohort, Cardiology and Cardiovascular Medicine, business, Nuclear medicine
Abstract: Background: It was hypothesized that the accuracy of coronary CT angiography would be affected by case volume of the referring sites. Methods: The positive predictive value (PPV) of CTCA performed at a tertiary hospital specialising in cardiothoracic medicine and services with lower case-volumes were calculated. The tertiary hospital used as the high case-volume reference centre was The Prince Charles Hospital, which performed >1500 CTCA scans per annum over the study period. The low case-volume services used in the study were suburban radiology services, each with
Published: 2018

25. Cost-Effectiveness of Cardiovascular Magnetic Resonance in Diagnosing Coronary Artery Disease in the Australian Health Care System

Author: John F. Younger, Joseph B. Selvanayagam, Christian Hamilton-Craig, Rebecca Kozor, Simon Walker, John P Greenwood, Bonny Parkinson, and Andrew J. Taylor
Subjects: Pulmonary and Respiratory Medicine, Male, medicine.medical_specialty, Cost effectiveness, Cost-Benefit Analysis, Stress testing, Magnetic Resonance Imaging, Cine, Coronary Artery Disease, 030204 cardiovascular system & hematology, Chest pain, Coronary artery disease, Angina, 03 medical and health sciences, 0302 clinical medicine, Health care, medicine, Perindopril, Humans, 030212 general & internal medicine, Intensive care medicine, Aged, medicine.diagnostic_test, business.industry, Australia, Magnetic resonance imaging, Middle Aged, medicine.disease, Models, Economic, Female, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Delivery of Health Care, medicine.drug
Abstract: Background Coronary artery disease (CAD) remains a major public health problem in Australia and globally. A variety of imaging techniques allow for both anatomical and functional assessment of CAD and selection of the optimal investigation pathway is challenging. Cardiovascular magnetic resonance (CMR) is not widely used in Australia, partly due to perceived cost and lack of Federal Government reimbursement compared to the alternative techniques. The aim of this study was to estimate the cost-effectiveness of different diagnostic strategies in identifying significant CAD in patients with chest pain suggestive of angina using the evidence gathered in the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease 2 (CE-MARC trial), analysed from the Australian health care perspective. Methods A decision analytic model coupled with three distinct Markov models allowed eight potential clinical investigation strategies to be considered; combinations of exercise electrocardiogram stress testing (EST), single-photon emission computed tomography (SPECT), stress CMR, and invasive coronary angiography (ICA). Costs were from the Australian health care system in Australian dollars, and outcomes were measured in terms of quality-adjusted life-years. Parameter estimates were derived from the CE-MARC and EUropean trial on Reduction Of cardiac events with Perindopril in patients with stable coronary Artery disease (EUROPA) trials, and from reviews of the published literature. Results The most cost-effective diagnostic strategy, based on a cost-effectiveness threshold of $45,000 to $75,000 per QALY gained, was EST, followed by stress CMR if the EST was positive or inconclusive, followed by ICA if the stress CMR was positive or inconclusive; this held true in the base case and the majority of scenario analyses. Conclusions This economic evaluation shows that an investigative strategy of stress CMR if EST is inconclusive or positive is the most cost-effective approach for diagnosing significant coronary disease in chest pain patients within the Australian health care system.
Published: 2019

26. Catheter ablation of papillary muscle arrhythmias: Implications of mitral valve prolapse and systolic dysfunction

Author: Haris M. Haqqani, R. Denman, Christian Hamilton-Craig, and Adam Lee
Subjects: Adult, Male, medicine.medical_specialty, Systole, medicine.medical_treatment, Cardiomyopathy, Catheter ablation, 030204 cardiovascular system & hematology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Mitral valve, medicine, Humans, Mitral valve prolapse, In patient, 030212 general & internal medicine, Papillary muscle, Aged, Mitral Valve Prolapse, Ejection fraction, business.industry, Arrhythmias, Cardiac, General Medicine, Middle Aged, Papillary Muscles, medicine.disease, Ablation, medicine.anatomical_structure, Catheter Ablation, Cardiology, Female, Cardiology and Cardiovascular Medicine, business
Abstract: BACKGROUND The left ventricular (LV) papillary muscles are important components of the mitral valve apparatus. Catheter ablation of ventricular arrhythmias from these sites is challenging. We aim to describe the association between LV papillary muscle ventricular arrhythmias (VAs) and mitral valve prolapse (MVP), and to determine the outcomes of ablation in these patients with a focus on those with MVP and cardiomyopathy. METHODS A total of 152 patients underwent 170 consecutive procedures for ablation of focal VAs. MVP and cardiomyopathy were diagnosed by echocardiography. Outcomes following ablation were assessed in three groups: (1) LV papillary muscle VAs versus other sites, (2) LV papillary muscle VAs by the presence of MVP, and (3) LV papillary muscle VAs in the setting of cardiomyopathy. RESULTS Nine of 23 (39%) patients undergoing ablation of LV papillary muscle VAs had MVP compared to none of 129 (0%) patients at other sites (P
Published: 2018

27. Coronary artery disease reporting and data system (CAD-RADS TM ): Inter-observer agreement for assessment categories and modifiers

Author: James Lee, Michelle A. Williams, Yanshu Guo, Ricardo C. Cury, Dustin M. Thomas, Ronen Rubinshtein, Pál Maurovich-Horvat, Roberto Caldeira Cury, Kelley R. Branch, Christopher D. Maroules, and Christian Hamilton-Craig
Subjects: medicine.medical_specialty, business.industry, Image quality, Inter observer agreement, medicine.medical_treatment, Stent, 030204 cardiovascular system & hematology, medicine.disease, 030218 nuclear medicine & medical imaging, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Medicine, Radiology, Nuclear Medicine and imaging, Medical history, Radiology, Early career, Cardiology and Cardiovascular Medicine, business, Cardiac imaging, Kappa
Abstract: Background: The Coronary Artery Disease Reporting and Data System (CAD-RADS) provides a lexicon and standardized reporting system for coronary CT angiography. Objectives: To evaluate inter-observer agreement of the CAD-RADS among an panel of early career and expert readers. Methods: Four early career and four expert cardiac imaging readers prospectively and independently evaluated 50 coronary CT angiography cases using the CAD-RADS lexicon. All readers assessed image quality using a five-point Likert scale, with mean Likert score ≥4 designating high image quality, and
Published: 2018

28. Cardiac Society of Australia and New Zealand Position Statement: Coronary Artery Calcium Scoring

Author: John F. Younger, Gary Liew, Jonathan Chan, Clara K Chow, Christian Hamilton-Craig, Michael Jelinek, and Niels van Pelt
Subjects: Male, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Cost effectiveness, Cardiology, Coronary Artery Disease, 030204 cardiovascular system & hematology, Risk Assessment, Electron beam tomography, law.invention, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Internal medicine, medicine, Humans, cardiovascular diseases, 030212 general & internal medicine, Myocardial infarction, Societies, Medical, Aged, Aspirin, Framingham Risk Score, medicine.diagnostic_test, business.industry, Australia, nutritional and metabolic diseases, Middle Aged, medicine.disease, Coronary Vessels, Plaque, Atherosclerotic, Surgery, cardiovascular system, Calcium, Female, Cardiology and Cardiovascular Medicine, Risk assessment, business, New Zealand, medicine.drug
Abstract: Coronary Artery Calcium Scoring (CAC) is a non-invasive quantitation of coronary artery calcification using computed tomography (CT). It is a marker of atherosclerotic plaque burden and an independent predictor of future myocardial infarction and mortality. Coronary Artery Calcium Scoring provides incremental risk information beyond traditional risk calculators (eg. Framingham Risk Score). Its use for risk stratification is confined to primary prevention of cardiovascular events, and can be considered as "individualised coronary risk scoring" for those not considered to be of high or low risk. Medical practitioners should carefully counsel patients prior to CAC. Coronary Artery Calcium Scoring should only be undertaken if an alteration in therapy including embarking on pharmacotherapy is being considered based on the test result. Patient Groups to Consider Coronary Calcium Scoring: Patient Groups in Whom Coronary Calcium Scoring Should Not be Considered: Coronary Artery Calcium Scoring is not recommended for patients who are: Interpretation of CAC CAC=0 A zero score confers a very low risk of death,1% at 10 years. CAC=1-100 Low risk,10% CAC=101-400 Intermediate risk, 10-20% CAC=101-40075th centile. Moderately high risk, 15-20% CAC400 High risk,20% Management Recommendations Based on CAC Optimal diet and lifestyle measures are encouraged in all risk groups and form the basis of primary prevention strategies. Patients with moderately-high or high risk based on CAC score are recommended to receive preventative medical therapy such as aspirin and statins. The evidence for pharmacotherapy is less robust in patients at intermediate levels of CAC 100-400, with modest benefit for aspirin use; though statins may be reasonable if they are above 75th centile. Aspirin and statins are generally not recommended in patients with CAC100. Repeat CAC Testing In patients with a CAC of 0, a repeat CAC may be considered in 5 years but not sooner. In patients with positive calcium score, routine re-scanning is not currently recommended. However, an annual increase in CAC of15% or annual increase of CAC100 units are predictive of future myocardial infarction and mortality. Cost Effectiveness of CAC Based Primary Prevention Recommendations: There is currently no data in Australia and New Zealand that CAC is cost-effective in informing primary prevention decisions. Given the cost of testing is currently borne entirely by the patient, discussion regarding the implications of CAC results should occur before CAC is recommended and undertaken.
Published: 2017

29. Left Ventricular Global Strain Analysis by Two-Dimensional Speckle-Tracking Echocardiography: The Learning Curve

Author: José Luis Zamorano, Andrew Small, W. Scalia, Akira Yamada, Gregory M. Scalia, R. Chamberlain, Nchafatso G. Obonyo, Christian Hamilton-Craig, J. Hanna, Kenji Shiino, Jonathan Chan, and Isabel G. Scalia
Subjects: Male, medicine.medical_specialty, Intraclass correlation, Heart Ventricles, education, Cardiology, Speckle tracking echocardiography, 030204 cardiovascular system & hematology, Ventricular Function, Left, Correlation, Ventricular Dysfunction, Left, 03 medical and health sciences, 0302 clinical medicine, Region of interest, medicine, Humans, Radiology, Nuclear Medicine and imaging, Medical physics, 030212 general & internal medicine, Societies, Medical, Retrospective Studies, Ejection fraction, business.industry, Middle Aged, United States, Global strain, Surgery, Quartile, Echocardiography, Education, Medical, Graduate, Learning curve, Female, Cardiology and Cardiovascular Medicine, business, Learning Curve, Follow-Up Studies
Abstract: Background The application of left ventricular (LV) global strain by speckle-tracking is becoming more widespread, with the potential for incorporation into routine clinical echocardiography in selected patients. There are no guidelines or recommendations for the training requirements to achieve competency. The aim of this study was to determine the learning curve for global strain analysis and determine the number of studies that are required for independent reporting. Methods Three groups of novice observers (cardiology fellows, cardiac sonographers, medical students) received the same standardized training module prior to undertaking retrospective global strain analysis on 100 patients over a period of 3 months. To assess the effect of learning, quartiles of 25 patients were read successively by each blinded observer, and the results were compared to expert for correlation. Results Global longitudinal strain (GLS) had uniform learning curves and was the easiest to learn, requiring a minimum of 50 patients to achieve expert competency (intraclass correlation coefficient > 0.9) in all three groups over a period of 3 months. Prior background knowledge in echocardiography is an influential factor affecting the learning for interobserver reproducibility and time efficiency. Short-axis strain analysis using global circumferential stain and global radial strain did not yield a comprehensive learning curve, and expert level was not achieved by the end of the study. Conclusions There is a significant learning curve associated with LV strain analysis. We recommend a minimum of 50 studies for training to achieve competency in GLS analysis.
Published: 2017

30. MRI measurements of the thoracic aorta and pulmonary artery

Author: Viviana Rodriguez, Abdi-Aziz Mohamed, Harry Bartlett, Richard Slaughter, Leyla Beck, Christian Hamilton-Craig, and Wendy Strugnell
Subjects: Adult, Male, Aortic arch, Cardiac-Gated Imaging Techniques, Aorta, Thoracic, Pulmonary Artery, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Imaging, Three-Dimensional, 0302 clinical medicine, Reference Values, medicine.artery, Ascending aorta, medicine, Humans, Thoracic aorta, Radiology, Nuclear Medicine and imaging, Prospective Studies, Cardiac skeleton, Mean diameter, business.industry, Steady-state free precession imaging, Middle Aged, Magnetic Resonance Imaging, Healthy Volunteers, Clinical Practice, Oncology, Pulmonary artery, cardiovascular system, Female, business, Nuclear medicine
Abstract: The purpose of this study was to obtain a range of normal measurements of the adult thoracic aorta and main pulmonary artery using cardiac MRI, and to assess agreement between measurements made on ECG-gated two-dimensional (2D) breath held steady-state-free precession (SSFP), and three-dimensional (3D) breath held SSFP image acquisitions. Forty-nine normal volunteers underwent cardiac MRI using a 1.5T system. Two independent examiners measured the ascending aorta, aortic arch, descending thoracic aorta and main pulmonary artery in pre-defined locations. Overall, inter-observer agreement for all measurements was excellent. Close agreement was observed in aortic diameters obtained from the 2D and 3D SSFP methods in six of the nine aortic measurement sites. There was a tendency for the 3D measurements to be smaller than the 2D measurements but this was only significant at two sites, the aortic annulus, and the ascending aorta. There was a significance difference in aortic measurements between the left carotid artery (LC) and the left subclavian artery (LSC). Normal values for transverse diameters of the thoracic aorta and main pulmonary artery were established using 2D and 3D non-contrast MR sequences in healthy adults. Overall both inter-observer agreement, and agreement between 2D and 3D techniques was good. Mean diameter differences demonstrated at the aortic annulus, ascending aorta and aortic arch between LC and LSC although significant were less than one millimetre and unlikely to be important in clinical practice.
Published: 2017

31. Evaluation Of Left Atrium Indices Among High Heart Rate And Atrial Fibrillation Patients With Advancement In Computed Tomography Technology: The Converge Registry

Author: S. Dahal, R. O'Rourke, Divya Birudaraju, Edoardo Conte, Songshou Mao, Mathew Budoff, Ferdinand Flores, Christian Hamilton-Craig, A. Onuegbu, P. Haroun, Daniele Andreini, R. Pozon, S. Pidikiti, A. Pozon, Suvasini Lakshmanan, Gianluca Pontone, Christopher Dailing, Sion K. Roy, Sajad Hamal, Rine Nakanishi, Lavanya Cherukuri, Khurram Nasir, B. Chaganti, and April Kinninger
Subjects: medicine.medical_specialty, medicine.diagnostic_test, business.industry, Left atrium, Atrial fibrillation, Computed tomography, medicine.disease, medicine.anatomical_structure, High heart rate, Internal medicine, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, Cardiology and Cardiovascular Medicine, business
Published: 2020

32. Lower Utilization Of Contrast Media And Beta-blocker In 256-detector Ge Revolution Ct Scanner: The Converge Registry

Author: Rine Nakanishi, Ahmed Ghanem, Sion K. Roy, S. Dahal, Ilana Golub, Suvasini Lakshmanan, Daniele Andreini, Gianluca Pontone, Matthew J. Budoff, A. Cai, A. Onuegbu, Negin Nezarat, Edoardo Conte, April Kinninger, Christian Hamilton-Craig, Khadije Ahmad, Vahid Rezvanizadeh, Divya Birudaraju, and R. O'Rourke
Subjects: Scanner, business.industry, medicine.drug_class, media_common.quotation_subject, Detector, Medicine, Contrast (vision), Radiology, Nuclear Medicine and imaging, Cardiology and Cardiovascular Medicine, business, Nuclear medicine, Beta blocker, media_common
Published: 2020

33. The Dye Don’t Lie But May Not Tell the Truth

Author: Christian Hamilton-Craig and Kelley R. Branch
Subjects: Gene isoform, Messenger RNA, medicine.medical_specialty, medicine.diagnostic_test, business.industry, Coronary computed tomography angiography, RNA, Computational biology, 030204 cardiovascular system & hematology, 03 medical and health sciences, Myocardial perfusion imaging, 0302 clinical medicine, Transcription (biology), Cell culture, Internal medicine, Cardiology, Medicine, Radiology, Nuclear Medicine and imaging, 030212 general & internal medicine, Cardiology and Cardiovascular Medicine, business, Gene
Abstract: The steady state expression of each gene is the result of a dynamic transcription and degradation of that gene. While regular RNA-seq methods only measure steady state expression levels, RNA-seq of metabolically labeled RNA identifies transcripts that were transcribed during the window of metabolic labeling. Whereas short-read RNA sequencing can identify metabolically labeled RNA at the gene level, long-read sequencing provides much better resolution of isoform-level transcription. Here we combine thiouridine-to-cytosine conversion (TUC) with PacBio long-read sequencing to study the dynamics of mRNA transcription in the GM12878 cell line. We show that using long-TUC-seq, we can detect metabolically labeled mRNA of distinct isoforms more reliably than using short reads. Long-TUC-seq holds the promise of capturing isoform dynamics robustly and without the need for enrichment.
Published: 2018

34. P443Simplified Splenic Switch Off - an easy method for determining adequacy of vasodilation during adenosine stress CMR

Author: P Lymburner, Christian Hamilton-Craig, W. Strugnell, M Webber, and J. Neill
Subjects: medicine.medical_specialty, business.industry, Adenosine stress, Spleen, Vasodilation, General Medicine, Adenosine, medicine.anatomical_structure, Internal medicine, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, Cardiology and Cardiovascular Medicine, business, medicine.drug
Published: 2019

35. P4167-Tesla Cardiac MRI with vector-ECG gating despite the magnetohydrodynamic effect in healthy volunteers

Author: D. Staeb, Christian Hamilton-Craig, Markus Barth, Graham J. Galloway, and Kieran O'Brien
Subjects: medicine.medical_specialty, business.industry, Internal medicine, Ecg gating, Healthy volunteers, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, General Medicine, Magnetohydrodynamic drive, Cardiology and Cardiovascular Medicine, business
Published: 2019

36. Lower Radiation Dosing in Cardiac CT Angiography: The CONVERGE Registry

Author: Dong Li, Manojna Nimmagadda, Paul Madaj, Matthew J. Budoff, Edoardo Conte, Nicholas Kim, Rine Nakanishi, Badiha Fatima, Christopher Dailing, Rachael O’Rourke Franzcr, Gianluca Pontone, Christian Hamilton-Craig, and Daniele Andreini
Subjects: Male, Computed Tomography Angiography, Contrast Media, Diagnostic accuracy, Coronary Artery Disease, Coronary Angiography, Radiation Dosage, Risk Assessment, 030218 nuclear medicine & medical imaging, Body Mass Index, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, medicine, Humans, Radiology, Nuclear Medicine and imaging, Dosing, Registries, Aged, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Radiation dose, Coronary ct angiography, Heart, General Medicine, Middle Aged, medicine.disease, Radiation exposure, Angiography, Female, Nuclear medicine, business, Body mass index
Abstract: Coronary artery disease is the leading cause of morbidity and mortality. Tools have been developed to accurately diagnose and evaluate coronary artery disease. Coronary CT angiography (CCTA) provides detailed imaging to deliver precise analysis and prognostic information. We sought to compare the radiation dose from a 256-detector-row CT scanner with that from a 64-detector-row CT scanner across a similar profile of patients. Methods: Consecutive patients were screened for the Converge Registry study and, after consenting to be included, were enrolled in accordance with an Institutional Review Board-approved protocol. A control group who underwent 64-row CCTA were matched by age, sex, and body mass index (BMI) with a group who underwent 256-row CCTA. Results: We compared 110 patients in each group. We found that mean dose-length product (DLP) was significantly lower in the 256-row group than in the 64-row group (P < 0.05). The radiation dose was reduced by 32% with use of the 256-row scanner for BMIs of 18.5-24.9 (DLP, 111.2 vs. 76.1 mGy-cm [1.56 vs. 1.07 mSv]; P < 0.05). For each BMI subgroup, there was a significant decrease in dose. Regression analysis found that with increasing BMIs, DLP significantly increased for both scanners. Conclusion: The 256-row scanner provided CCTA scans at significantly lower radiation doses than the 64-row scanner in different BMI groups, with all other variables accounted for. Lower radiation exposure along with lower contrast requirements can provide images with high diagnostic accuracy and less risk to the patient.
Published: 2019

37. Lower Radiation Dosing in Cardiac Computed Tomographic Angiography: the CONVERGE Registry

Author: Rine Nakanishi, Rachael O'Rourke, Gianluca Pontone, Paul Madaj, Manojna Nimmagadda, Christian Hamilton-Craig, Christopher Dailing, Edoardo Conte, Matthew J. Budoff, Badiha Fatima, Nicholas Kim, Dong Li, and Daniele Andreini
Subjects: Scanner, 64 slice ct, Radiological and Ultrasound Technology, business.industry, General Medicine, Institutional review board, medicine.disease, Sievert, 030218 nuclear medicine & medical imaging, Computed tomographic angiography, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Medicine, Radiology, Nuclear Medicine and imaging, Dosing, Nuclear medicine, business, Body mass index
Abstract: Intro: Coronary artery disease is the leading cause for morbidity and mortality. Tools have been developed to accurately diagnose and evaluate coronary artery disease. Coronary computed tomographic angiography (CCTA) scans provide detailed imaging along with analysis to in order to deliver precise analysis and prognostic information. We sought to evaluate the radiation doses of the 256 detector CT scanner to a 64 slice scanner across a similar profile of patients. Methods: Consecutive patients were screened, enrolled, and consented for the Converge Registry study, in accordance with the Institutional Review Board (IRB) approved protocol. 110 patients underwent CCTA using the GE Revolution 256 detector CT scanner. We matched patients by age, gender and body mass index (BMI) who underwent 64 slice CT scanning. Results: We compared 110 patients in each group. We found that mean dose length product (DLP, presented also in the tables below in millisieverts (mSv)) was significantly lower in the Revolution 256 detector group compared to the 64 slice control group (p
Published: 2019

38. Higher resolution cine imaging with compressed sensing for accelerated clinical left ventricular evaluation

Author: Robyn Riley, Michaela Schmidt, W. Strugnell, Norman R. Morris, Benjamin Schmitt, Aaron C.W. Lin, Michael Zenge, and Christian Hamilton-Craig
Subjects: Ejection fraction, medicine.diagnostic_test, Image quality, business.industry, Limits of agreement, Resolution (electron density), Magnetic resonance imaging, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Cine imaging, medicine, Radiology, Nuclear Medicine and imaging, Wall motion, Nuclear medicine, business, Myocardial mass
Abstract: Purpose: To assess the clinical feasibility of a compressed sensing cine magnetic resonance imaging (MRI) sequence of both high temporal and spatial resolution (CS_bSSFP) in comparison to a balanced steady-state free precession cine (bSSFP) sequence for reliable quantification of left ventricular (LV) volumes and mass. Materials and Methods: Segmented MRI cine images were acquired on a 1.5T scanner in 50 patients in the LV short-axis stack orientation using a retrospectively gated conventional bSSFP sequence (generalized autocalibrating partially parallel acquisition [GRAPPA] acceleration factor 2), followed by a prospectively triggered CS_bSSFP sequence with net acceleration factor of 8. Image quality was assessed by published criteria. Comparison of sequences was made in LV volumes and mass, image quality score, quantitative regional myocardial wall motion, and imaging time using Pearson's correlation, Bland–Altman and paired 2-tailed Student's t-test. Results: Differences (bSSFP minus CS_bSSFP, mean ± SD) and Pearson's correlations were 14.8 ± 16.3 (P = 0.31) and r = 0.98 (P < 0.0001) for end-diastolic volume (EDV), 8.4 ± 11.3 (P = 0.54) and r = 0.99 (P < 0.0001) for end-systolic volume (ESV), –0.4 ± 2.5 (P = 0.87) and r = 0.97 (P < 0.0001) for EF, and –0.9 ± 11.8 (P = 0.92) and r = 0.97 (P < 0.0001) for LV mass. Bland–Altman analyses [bias and (limits of agreement)] revealed strong agreement in LVEDV [8.7 ml, (–12.1, 29.6)], LVESV [4.3 ml, (–11.9, 20.6)], LVEF [-0.02%, (–5.37, 5.33)], and myocardial mass [-6.1 g, (–14.7, 26.9)]. Image quality was comparable with a similar mean score (P = 0.42), with a good correlation in image quality observed (r = 0.68, P < 0.0001). Quantitative regional myocardial wall motion demonstrated strong correlation between the sequences (r = 0.87, P < 0.0001). Imaging time was significantly shorter for the CS_bSSFP sequence (1.1 ± 0.5 versus 5.6 ± 1.6 min, P < 0.0001). Conclusion: The novel high-resolution cine CS_bSSFP accurately and reliably quantitates LV volumes and mass, shortens acquisition times, and is clinically feasible. Level of Evidence: 1. Technical Efficacy: Stage 2. J. MAGN. RESON. IMAGING 2017;45:1693–1699.
Published: 2016

39. Quantitation of mitral regurgitation with cardiac magnetic resonance imaging: a systematic review

Author: Eric V. Krieger, Christian Hamilton-Craig, James Chun-I Lee, and Kelley R. Branch
Subjects: medicine.medical_specialty, 030204 cardiovascular system & hematology, Severity of Illness Index, Original research, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Predictive Value of Tests, Cardiac magnetic resonance imaging, Internal medicine, medicine, Humans, cardiovascular diseases, Observer Variation, Reproducibility, Mitral regurgitation, medicine.diagnostic_test, business.industry, Hemodynamics, Mitral Valve Insufficiency, Reproducibility of Results, Magnetic resonance imaging, Prognosis, Magnetic Resonance Imaging, Systematic review, Echocardiography, Predictive value of tests, cardiovascular system, Cardiology, Mitral Valve, Cardiology and Cardiovascular Medicine, Cardiac magnetic resonance, business
Abstract: In this review discuss the application of cardiac magnetic resonance (CMR) to the evaluation and quantification of mitral regurgitation and provide a systematic literature review for comparisons with echocardiography. Using the 2015 Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology, we searched Medline and PubMed for original research articles published since 2000 that provided data on the quantification of mitral regurgitation by CMR. We identified 220 articles of which 33 were included. Four main techniques of mitral regurgitation quantification were identified. Reproducibility varied substantially between papers but was high overall for all techniques. However, quantification differed between the techniques studied. When compared with two-dimensional echocardiography, mitral regurgitation fraction and regurgitant volume measured by CMR were comparable but typically lower. CMR has high reproducibility for the quantification of mitral regurgitation in experienced centres, but further technological refinement is needed. An integrated and standardised approach that combines multiple techniques is recommended for optimal reproducibility and precise mitral regurgitation quantification. Definitive outcome studies using CMR as a basis for treatment are lacking but needed.
Published: 2016

40. Accuracy of quantitative echocardiographic measures of right ventricular function as compared to cardiovascular magnetic resonance

Author: Bonita Anderson, Christian Hamilton-Craig, Akira Yamada, Ryan Maxwell, Tony Stanton, Jonathan Chan, Kathy Stedman, Gregory M. Scalia, and Darryl J. Burstow
Subjects: medicine.medical_specialty, lcsh:Diseases of the circulatory (Cardiovascular) system, Cardiac & Cardiovascular Systems, MPI, myocardial performance index, TR, tricuspid regurgitation, CMR, cardiovascular magnetic resonance, ε, strain, 030204 cardiovascular system & hematology, RVSm, s prime: right ventricular peak systolic myocardial velocity, RVOT, right ventricular outflow tract, SR, strain rate, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, RVSm, peak systolic myocardial velocity, Magnetic resonance imaging, TAPSE, tricuspid annular peak systolic excursion, Internal medicine, 3DE-RV, three-dimensional echo right ventricular ejection fraction, Linear regression, 3DE, three dimensional echocardiography, medicine, EF, ejection fraction, cardiovascular diseases, IVCT, isovolumic contraction time, Myocardial Performance Index, TOF, tetralogy of Fallot, Tetralogy of Fallot, Doppler tissue imaging, Ejection fraction, Ventricular function, medicine.diagnostic_test, business.industry, medicine.disease, Right ventricular function, LV, left ventricle, Echocardiography, lcsh:RC666-701, IVRT, isovolumic relaxation time, Cardiology, cardiovascular system, DTI, Doppler tissue imaging, Right ventricle, Cardiology and Cardiovascular Medicine, Isovolumic relaxation time, business, RV, right ventricular
Abstract: Background: Many echocardiographic parameters have been proposed to evaluate right ventricular (RV) systolic function. We comprehensively assessed a wide range of quantitative echocardiographic parameters in a single cohort compared with same-day cardiovascular magnetic resonance (CMR). Methods and results: 92 subjects were examined prospectively: Group 1 consisted of 46 healthy controls (21 males, 33.4 ± 11.4 years), Group 2 consisted of 46 patients (20 males, 38.5 ± 18.9 years) undergoing RV functional assessment by CMR (1.5 T). Echocardiography was performed on the same day as CMR; fractional area change (RVFAC), myocardial performance index via spectral Doppler (RVMPI), RVMPI via Doppler tissue imaging (RVMPI-DTI), peak systolic myocardial velocity by DTI (RVSm), tricuspid annular plane systolic excursion (TAPSE), speckle tracking strain, and three dimensional right ventricular ejection fraction (3DE-RV). Linear regression, Bland-Altman and receiver-operator-characteristic (ROC) analyses were performed. At ROC analysis, the most predictive echocardiographic methods were; RVFAC (AUC = 0.892), RVMPI (AUC 0.785), TAPSE (AUC 0.849) and 3DE-RV (AUC 0.909). 3DE-RV appeared the most accurate compared to CMR, although underestimated true RV volumes. Conclusion: As compared to CMR; 3DE-RV, RVFAC, TAPSE and RVMPI were the most reliable predictors of RV function. These parameters can be recommended for clinical use.
Published: 2016

41. ECG Triggering in Ultra-High Field Cardiovascular MRI

Author: Kieran O'Brien, Daniel Stäb, Markus Barth, Juergen Roessler, and Christian Hamilton-Craig
Subjects: medicine.diagnostic_test, Cardiac cycle, ECG, cardiac, Computer science, Blood flow, Magnetostatics, magnetohydrodynamic effect, Synchronization, Ecg triggering, Cardiac magnetic resonance imaging, Ultra high field, medicine, ultra-high field, Radiology, Nuclear Medicine and imaging, Advances in Brief, Cardiac imaging, MRI, Biomedical engineering
Abstract: Cardiac magnetic resonance imaging at ultra-high field (B0 ≥ 7 T) potentially provides improved resolution and new opportunities for tissue characterization. Although an accurate synchronization of the acquisition to the cardiac cycle is essential, electrocardiogram (ECG) triggering at ultra-high field can be significantly impacted by the magnetohydrodynamic (MHD) effect. Blood flow within a static magnetic field induces a voltage, which superimposes the ECG and often affects the recognition of the R-wave. The MHD effect scales with B0 and is particularly pronounced at ultra-high field creating triggering-related image artifacts. Here, we investigated the performance of a conventional 3-lead ECG trigger device and a state-of-the-art trigger algorithm for cardiac ECG synchronization at 7 T. We show that by appropriate subject preparation and by including a learning phase for the R-wave detection outside of the magnetic field, reliable ECG triggering is feasible in healthy subjects at 7 T without additional equipment. Ultra-high field cardiac imaging was performed with the ECG signal and the trigger events recorded in 8 healthy subjects. Despite severe ECG signal distortions, synchronized imaging was successfully performed. Recorded ECG signals, vectorcardiograms, and large consistency in trigger event spacing indicate high accuracy for R-wave detection.
Published: 2016

42. Coronary computed tomography angiography and its increasing application in day to day cardiology practice

Author: Ryan Markham, Darren L. Walters, Dale Murdoch, and Christian Hamilton-Craig
Subjects: medicine.medical_specialty, business.industry, Functional testing, Coronary computed tomography angiography, 030204 cardiovascular system & hematology, medicine.disease, Chest pain, Coronary artery disease, Pre- and post-test probability, Angina, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Internal Medicine, medicine, Cardiology, 030212 general & internal medicine, Myocardial infarction, Radiology, medicine.symptom, business, Cause of death
Abstract: Coronary artery disease (CAD) is the leading single cause of death in Australia affecting around 1.4 million people. Coronary computed tomography angiography has an established role in the assessment of patients with low to intermediate pretest probability for CAD who have chest pain and is typically used with the aim to rule out significant coronary artery stenosis. Use was initially limited because of concerns over radiation exposure, a Medicare rebate restricted to specialist referrals and an absence of data supporting its use as an alternative to functional testing in patients with chest pain. Recent advances in scanner technology and image sequencing, along with data from randomised control trials, have addressed these issues and indicate that coronary computed tomography angiography will play a greater role in the assessment of CAD in the coming years.
Published: 2016

43. A 61-Year-Old Woman with Muscle Fatigue and Increased Cardiac Troponin

Author: Christian Hamilton-Craig, William A. Parsonage, Jane E. Mikli, George A. Marshall, and Janelle Nisbet
Subjects: medicine.medical_specialty, Clinical Biochemistry, Osteoarthritis, 030204 cardiovascular system & hematology, Chest pain, Sitting, Lipid Metabolism, Inborn Errors, Muscular Dystrophies, Necrosis, 03 medical and health sciences, 0302 clinical medicine, Troponin T, Carnitine, medicine, Humans, Amisulpride, Multiple Acyl Coenzyme A Dehydrogenase Deficiency, Muscle, Skeletal, Creatine Kinase, Depression (differential diagnoses), Muscle fatigue, business.industry, Troponin I, Biochemistry (medical), Middle Aged, medicine.disease, Rash, Muscle Fatigue, Diverticular disease, Physical therapy, Female, medicine.symptom, business, 030217 neurology & neurosurgery, medicine.drug
Abstract: A 61-year-old woman presented with a 12-month history of progressive muscle weakness, especially involving the proximal limb muscles. Her symptoms were associated with muscular fatigue such that she was compelled to sit and rest after walking only 30–50 m. She reported difficulty climbing stairs and standing from a sitting position. There was no rash or Raynaud phenomenon but she did report some episodes of feeling hot and perspiring. She denied any paresthesia, headache, or chest pain. Her past history included sigmoid diverticular disease, osteoarthritis of the cervical spine, and depression for over 20 years with psychotic features in the last 2–3 years. Her medications were aripiprazole 5 mg daily, irbesartan 150 mg daily, amisulpride 150 mg daily, imipramine 50 mg nocte, lercanidipine 10 mg daily, and sertraline 300 mg daily. She had also recently started replacement therapies for B12 and vitamin D deficiencies. Salient examination findings included a general reduction in muscle power, proximal greater than distal, with intact reflexes and sensation.
Published: 2017

44. Effect Of Low Tube Voltage On The Radiation Dosage And Image Quality Using Coronary Computed Tomography Angiography

Author: Daniele Andreini, Matthew J. Budoff, J. Wu, A. Onuegbu, Edoardo Conte, S. Dahal, Vahid Rezvanizadeh, Sion K. Roy, Khurram Nasir, Rine Nakanishi, Christian Hamilton-Craig, I. Rudenko, April Kinninger, R. O'Rourke, S. Lakshmananan, Gianluca Pontone, and A. Cai
Subjects: business.industry, Image quality, Coronary computed tomography angiography, Medicine, Low tube voltage, Radiology, Nuclear Medicine and imaging, Radiation, Cardiology and Cardiovascular Medicine, business, Nuclear medicine
Published: 2020

45. 296 Cardiac MRI of Patients with Implanted Devices - Diagnostic Improvement Using Wide Band Late Gadolinium Enhancement Imaging

Author: Haris M. Haqqani, P. Kellman, J. Jin, Christian Hamilton-Craig, W. Stugnell, J. Neill, and X. Bi
Subjects: Pulmonary and Respiratory Medicine, business.industry, Late gadolinium enhancement, Medicine, Wide band, Cardiology and Cardiovascular Medicine, Nuclear medicine, business
Published: 2020

46. 408 Stress Cardiac Magnetic Resonance With In-Line AI Quantitative Perfusion Mapping; Clinical Experience for Ischaemia and Microvascular Dyfunction

Author: P. Kellman, J. Neill, M. Fletcher, Christian Hamilton-Craig, and W. Strugnell
Subjects: Pulmonary and Respiratory Medicine, medicine.medical_specialty, business.industry, Ischemia, medicine.disease, Quantitative perfusion, Stress (mechanics), Internal medicine, Cardiology, medicine, Line (text file), Cardiology and Cardiovascular Medicine, Cardiac magnetic resonance, business
Published: 2020

47. 4.8 Reference Values for Submaximal Exercise Blood Pressure: the EXERcise Stress Test CollaboratION (EXERTION)

Author: Tony Stanton, Andrew Maiorana, Sudir Wahi, James L. Hare, Alison Venn, Ann-Marie Kovacevic, Joseph B. Selvanayagam, James E. Sharman, Schultz Martin, Philip Roberts-Thomson, and Christian Hamilton-Craig
Subjects: medicine.medical_specialty, business.industry, Specialties of internal medicine, Submaximal exercise, Exercise stress, General Medicine, Test (assessment), Blood pressure, RC581-951, RC666-701, Reference values, Physical therapy, Diseases of the circulatory (Cardiovascular) system, Medicine, Exertion, business
Abstract: Background: Exaggerated blood pressure (BP) during submaximal exercise independently predicts cardiovascular mortality and identifies uncontrolled high BP not detected at rest. However, thresholds for submaximal exercise BP during clinical exercise testing have never been defined from a large representative sample, which was the aim of this study. Methods: Records from 13,949 people referred for a clinical exercise stress test (aged 52 ± 13 years, 61% male) using the Bruce treadmill protocol (stages 1 to 4 plus peak) were extracted from 4 Australian hospitals over the years 2000–2018. Exercise records were linked to administrative health datasets (hospital admissions and emergency presentations) to define clinical characteristics, including cardiovascular disease history. Thresholds denoting exaggerated BP were defined as > 90th centile at each exercise stage. Results: SBP and DBP thresholds across all stages were higher in males vs. females (stage-1: 180/90 vs 175/90 mmHg; stage-2: 196/94 vs 190/90 mmHg; stage-3: 204/97 vs 196/91 mmHg; stage-4: 210/100 vs 196/92 mmHg; peak: 215/100 vs 206/95 mmHg). SBP at all stages increased stepwise from the 1st to 4th age quartile (p < 0.05), whilst DBP remained similar (stage-1: 163/90 to 185/92 mmHg; stage-2: 180/90 to 204/95 mmHg; stage-3: 193/90 to 210/95 mmHg, stage-4: 200/91, to 210/96 mmHg; peak: 201/95 to 217/100 mmHg). Results were similar irrespective of cardiovascular disease history. Conclusions: This is the first study to define submaximal exercise BP thresholds during clinical exercise testing. Thresholds were higher in males compared to females and increased with age. These thresholds may help clinicians to identify people at increased high BP-related risk.
Published: 2020

48. Comparison of Whole Heart Computed Tomography Scanners for Image Quality Lower Radiation Dosing in Coronary Computed Tomography Angiography: The CONVERGE Registry

Author: Edoardo Conte, Rachael O'Rourke, Manojna Nimmagadda, Badiha Fatima, Daniele Andreini, Eranthi Jayawardena, Nirali Patel, Matthew J. Budoff, Dong Li, Gianluca Pontone, Rine Nakanishi, and Christian Hamilton-Craig
Subjects: Male, Scanner, Tomography Scanners, X-Ray Computed, Image quality, Computed Tomography Angiography, Coronary Artery Disease, Radiation, Coronary Angiography, Radiation Dosage, 030218 nuclear medicine & medical imaging, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Hounsfield scale, medicine.artery, Image noise, medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Registries, business.industry, Coronary computed tomography angiography, Middle Aged, Radiation Exposure, medicine.disease, 030220 oncology & carcinogenesis, Descending aorta, Female, Nuclear medicine, business, Artifacts, Follow-Up Studies
Abstract: Rationale and Objectives: Novel technology in coronary computed tomographic angiography allows assessment of coronary artery disease with high image quality (IQ). There are currently two wide detector “whole heart” coverage scanners available, which avoid misregistration artifacts. However, there are no data directly comparing IQ between the two scanners. The aim of the current study is to investigate if IQ is different between the most current scanners of GE and Toshiba broad detector scanners. Materials and Methods: Prospective, observational, multicenter international cohort study comparing 236 consecutive patients who underwent coronary computed tomographic angiography using whole-heart scanners; 126 patients on scanner S1 (Aquilion ONE, Toshiba), and 110 patients on scanner S2 (Revolution CT, GE Healthcare). Hounsfield units were measured using regions of interest in the descending aorta at 6 points (cranial slice, level of the visualized first, second, third, and fourth spines, and the caudal slice). We also compared the coverage length (z-axis) of the full width field of view between a single rotation of the two scanners. Results: Evaluating mean CT attenuation values Hounsfield units through the scan range, are progressively reduced across the descending aorta in the S1 group, resulting in the larger difference of contrast brightness between the cranial and caudal slices compared to the S2 group (absolute difference: S2 13.0 ± 4.4 vs S1 141.9 ± 16.4, p < 0.0001; Percent difference: 19.3 ± 2.1 vs −3.4 ± 1.2
Published: 2018

49. 11637-Tesla Cardiac MRI for Ventricular and Valvular quantitation in healthy volunteers

Author: Markus Barth, Kieran O'Brien, D. Staeb, Graham J. Galloway, and Christian Hamilton-Craig
Subjects: Ejection fraction, medicine.diagnostic_test, business.industry, Image quality, Magnetic resonance imaging, Pulse oximetry, Healthy volunteers, Ecg gating, cardiovascular system, medicine, Pulmonary blood flow, cardiovascular diseases, Cardiology and Cardiovascular Medicine, Nuclear medicine, business, Cardiac imaging
Abstract: Background: Ultra-high-field (B0 ≥7 Tesla) cardiovascular magnetic resonance (CMR) offers increased resolution, but cardiac imaging requiring ECG gating is significantly impacted from the magneto-hydrodynamic (MHD) effect, distorts the ECG trace (1–3). Previously, 7T CMR was constrained to using pulse oximetry for triggering, We explored the technical feasbility of a 7 T research MR scanner using of-the-art ECG trigger algorithm to assess left and right ventricular volumes, aortic and pulmonary valve flow. Methods: 7T CMR scans were performed on 10 healthy volunteers on whole-body research MRI scanner (Siemens Healthcare, Erlangen, Germany) with 8 channel Tx/32 channel Rx cardiac coil (MRI Tools GmbH, Berlin, Germany) under institutional review board approval. Vectorcardiogram ECG was successfully performed using a learning phase outside of the magnetic field, with a trigger algorithm with sufficient accuracy for CMR despite severe ECG signal distortions from the 7T field. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented two-dimensional spoiled gradient echo sequence, and 2-dimensional phase contrast flow imaging. Analysis was performed using Cmr42 software (Circle CVi, Calgary). Results: Successful 7T CMR scans were acquired in all patients (100%) using the Vectorcardiogram 3-lead ECG method. Image quality was sufficient to quantitate both left and right ventricular volumes, ejection fraction, aortic and pulmonary blood flow and regurgitant fractions in 9/10 (90%) of volunteers (figure 1), with one volunteer having difficulty with breath-holding and ventricular ectopy causing gating artefacts.
Published: 2018

50. Improving the echocardiographic assessment of pulmonary pressure using the tricuspid regurgitant signal-The 'chin' vs the 'beard'

Author: Darryl J. Burstow, Christian Hamilton-Craig, J. Latona, Michael P. Savage, David Platts, Gregory M. Scalia, Martin Brown, S. Kyranis, and N. Kelly
Subjects: Male, medicine.medical_specialty, Cardiac Catheterization, Hypertension, Pulmonary, 030204 cardiovascular system & hematology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine.artery, medicine, Ventricular Pressure, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Pulmonary Wedge Pressure, Receiver operating characteristic, business.industry, Reproducibility of Results, Middle Aged, medicine.disease, Pulmonary hypertension, Chin, Echocardiography, Doppler, Tricuspid Valve Insufficiency, Pulmonary pressure, medicine.anatomical_structure, Blood pressure, 030228 respiratory system, Pulmonary artery, Ventricular pressure, Vascular resistance, Cardiology, Ventricular Function, Right, Female, Vascular Resistance, Tricuspid Valve, Cardiology and Cardiovascular Medicine, business, Follow-Up Studies
Abstract: AIM Transthoracic echocardiography (TTE) is a fundamental investigation for the noninvasive assessment of pulmonary hemodynamics and right heart function. The aim of this study was to assess the correlation and agreement of Doppler calculation of right ventricular systolic pressure (RVSP) and pulmonary vascular resistance (PVR) using "chin" and "beard" measurements of tricuspid regurgitant velocity (TRVmax ), with invasive pulmonary artery systolic pressure (PASP) and PVR. METHODS One hundred patients undergoing right heart catheterisation (RHC) and near simultaneous transthoracic echocardiography were studied. TRVmax was recorded for "chin" measurement (distinct peak TRVmax signal) and where available (63 patients), "beard" measurement (higher indistinct peak TRVmax signal). RESULTS Measurable TRV signal was obtained in 96 patients. Mean RVSPchin 54.7 ± 22.7 mm Hg and RVSPbeard 68.6 = 23 ± 26.3 mm Hg (P
Published: 2018

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