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1. Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry

Author

Pontone, Gianluca, Rossi, Alexia, Baggiano, Andrea, Andreini, Daniele, Conte, Edoardo, Fusini, Laura, Gebhard, Chaterine, Rabbat, Mark G., Guaricci, Andrea, Guglielmo, Marco, Muscogiuri, Giuseppe, Mushtaq, Saima, Al-Mallah, Mouaz H., Berman, Daniel S., Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Chun, Eun Ju, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Kim, Yong Jin, Lee, Byoung Kwon, Lee, Sang-Eun, Maffei, Erica, Marques, Hugo, Samady, Habib, Shin, Sanghoon, Sung, Ji Min, van Rosendael, Alexander, Virmani, Renu, Bax, Jeroen J., Leipsic, Jonathon A., Lin, Fay Y., Min, James K., Narula, Jagat, Shaw, Leslee J., and Chang, Hyuk-Jae

Published
2024
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3. Risk factors based vessel‐specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry

Author

Park, Hyung‐Bok, Lee, Jina, Hong, Yongtaek, Byungchang, So, Kim, Wonse, Lee, Byoung K, Lin, Fay Y, Hadamitzky, Martin, Kim, Yong‐Jin, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, de A. Gonçalves, Pedro, Leipsic, Jonathon A, Shin, Sanghoon, Choi, Jung H, Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Shaw, Leslee J, Bax, Jeroen J, Min, James K, Kook, Woong, and Chang, Hyuk‐Jae

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Atherosclerosis, Heart Disease - Coronary Heart Disease, Prevention, Cardiovascular, Heart Disease, Humans, Angina Pectoris, Bayes Theorem, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Machine Learning, Registries, Risk Factors, cardiovascular risk factors, coronary artery disease, machine learning, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

Background and hypothesisThe recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner.MethodsFrom the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model.ResultsThe 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis.ConclusionsThis study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.

Published
2023

4. Author Correction: Optical coherence tomography in coronary atherosclerosis assessment and intervention

Author

Araki, Makoto, Park, Seung-Jung, Dauerman, Harold L., Uemura, Shiro, Kim, Jung-Sun, Di Mario, Carlo, Johnson, Thomas W., Guagliumi, Giulio, Kastrati, Adnan, Joner, Michael, Holm, Niels Ramsing, Alfonso, Fernando, Wijns, William, Adriaenssens, Tom, Nef, Holger, Rioufol, Gilles, Amabile, Nicolas, Souteyrand, Geraud, Meneveau, Nicolas, Gerbaud, Edouard, Opolski, Maksymilian P., Gonzalo, Nieves, Tearney, Guillermo J., Bouma, Brett, Aguirre, Aaron D., Mintz, Gary S., Stone, Gregg W., Bourantas, Christos V., Räber, Lorenz, Gili, Sebastiano, Mizuno, Kyoichi, Kimura, Shigeki, Shinke, Toshiro, Hong, Myeong-Ki, Jang, Yangsoo, Cho, Jin Man, Yan, Bryan P., Porto, Italo, Niccoli, Giampaolo, Montone, Rocco A., Thondapu, Vikas, Papafaklis, Michail I., Michalis, Lampros K., Reynolds, Harmony, Saw, Jacqueline, Libby, Peter, Weisz, Giora, Iannaccone, Mario, Gori, Tommaso, Toutouzas, Konstantinos, Yonetsu, Taishi, Minami, Yoshiyasu, Takano, Masamichi, Raffel, O. Christopher, Kurihara, Osamu, Soeda, Tsunenari, Sugiyama, Tomoyo, Kim, Hyung Oh, Lee, Tetsumin, Higuma, Takumi, Nakajima, Akihiro, Yamamoto, Erika, Bryniarski, Krzysztof L., Di Vito, Luca, Vergallo, Rocco, Fracassi, Francesco, Russo, Michele, Seegers, Lena M., McNulty, Iris, Park, Sangjoon, Feldman, Marc, Escaned, Javier, Prati, Francesco, Arbustini, Eloisa, Pinto, Fausto J., Waksman, Ron, Garcia-Garcia, Hector M., Maehara, Akiko, Ali, Ziad, Finn, Aloke V., Virmani, Renu, Kini, Annapoorna S., Daemen, Joost, Kume, Teruyoshi, Hibi, Kiyoshi, Tanaka, Atsushi, Akasaka, Takashi, Kubo, Takashi, Yasuda, Satoshi, Croce, Kevin, Granada, Juan F., Lerman, Amir, Prasad, Abhiram, Regar, Evelyn, Saito, Yoshihiko, Sankardas, Mullasari Ajit, Subban, Vijayakumar, Weissman, Neil J., Chen, Yundai, Yu, Bo, Nicholls, Stephen J., Barlis, Peter, West, Nick E. J., Arbab-Zadeh, Armin, Ye, Jong Chul, Dijkstra, Jouke, Lee, Hang, Narula, Jagat, Crea, Filippo, Nakamura, Sunao, Kakuta, Tsunekazu, Fujimoto, James, Fuster, Valentin, and Jang, Ik-Kyung

Published
2024
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5. Longitudinal quantitative assessment of coronary atherosclerosis related to normal systolic blood pressure maintenance in the absence of established cardiovascular disease.

Author

Won, Ki-Bum, Park, Hyung-Bok, Heo, Ran, Lee, Byoung Kwon, Lin, Fay Y, Hadamitzky, Martin, Kim, Yong-Jin, Sung, Ji Min, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, Gonçalves, Pedro de Araújo, Leipsic, Jonathon A, Lee, Sang-Eun, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Berman, Daniel S, Narula, Jagat, Bax, Jeroen J, Min, James K, and Chang, Hyuk-Jae

Subjects
Humans, Cardiovascular Diseases, Disease Progression, Polyvinyl Chloride, Coronary Angiography, Risk Factors, Blood Pressure, Female, Male, Coronary Artery Disease, Plaque, Atherosclerotic, Computed Tomography Angiography, atherosclerosis, coronary artery disease, coronary computed tomography angiography, systolic blood pressure, Aging, Clinical Research, Cardiovascular, Heart Disease, Atherosclerosis, Heart Disease - Coronary Heart Disease, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology
Abstract

BackgroundAtherosclerosis-related adverse events are commonly observed even in conditions with low cardiovascular (CV) risk. Longitudinal data regarding the association of normal systolic blood pressure maintenance (SBPmaintain ) with coronary plaque volume changes (PVC) has been limited in adults without traditional CV disease.HypothesisNormal SBPmaintain is important to attenuate coronary atherosclerosis progression in adults without baseline CV disease.MethodsWe analyzed 95 adults (56.7 ± 8.5 years; 40.0% men) without baseline CV disease who underwent serial coronary computed tomographic angiography with mean 3.5 years of follow-up. All participants were divided into two groups of normal SBPmaintain (follow-up SBP

Published
2022

8. Longitudinal Quantitative Assessment of Coronary Atherosclerotic Plaque Burden Related to Serum Hemoglobin Levels

Author

Won, Ki-Bum, Lee, Byoung Kwon, Heo, Ran, Park, Hyung-Bok, Lin, Fay Y, Hadamitzky, Martin, Kim, Yong-Jin, Sung, Ji Min, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, de Araújo Gonçalves, Pedro, Leipsic, Jonathon A, Lee, Sang-Eun, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Berman, Daniel S, Narula, Jagat, Bax, Jeroen J, Min, James K, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease, Clinical Research, Cardiovascular, Hematology, Atherosclerosis, Heart Disease - Coronary Heart Disease, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, CCTA, coronary computed tomographic angiography, CV, cardiovascular, PVC, plaque volume changes, atherosclerosis, coronary computed tomography angiography, hemoglobin, Δ hemoglobin, hemoglobin level changes
Abstract

BackgroundDespite a potential role of hemoglobin in atherosclerosis, data on coronary plaque volume changes (PVC) related to serum hemoglobin levels are limited.ObjectivesThe authors sought to evaluate coronary atherosclerotic plaque burden changes related to serum hemoglobin levels using serial coronary computed tomographic angiography (CCTA).MethodsA total of 830 subjects (age 61 ± 10 years, 51.9% male) who underwent serial CCTA were analyzed. The median interscan period was 3.2 (IQR: 2.5-4.4) years. Quantitative assessment of coronary plaques was performed at both scans. All participants were stratified into 4 groups based on the quartile of baseline hemoglobin levels. Annualized total PVC (mm3/year) was defined as total PVC divided by the interscan period.ResultsBaseline total plaque volume (mm3) was not different among all groups (group I [lowest]: 34.1 [IQR: 0.0-127.4] vs group II: 28.8 [IQR: 0.0-123.0] vs group III: 49.9 [IQR: 5.6-135.0] vs group IV [highest]: 34.3 [IQR: 0.0-130.7]; P = 0.235). During follow-up, serum hemoglobin level changes (Δ hemoglobin; per 1 g/dL) was related to annualized total PVC (β = -0.114) in overall participants (P < 0.05). After adjusting for age, sex, traditional risk factors, baseline hemoglobin and creatinine levels, baseline total plaque volume, and the use of aspirin, beta-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, and statin, Δ hemoglobin significantly affected annualized total PVC in only the composite of groups I and II (β = -2.401; P = 0.004).ConclusionsSerial CCTA findings suggest that Δ hemoglobin has an independent effect on coronary atherosclerosis. This effect might be influenced by baseline hemoglobin levels. (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411).

Published
2022

9. Mechanisms of Medial Wall Thinning in Chronic Total Occlusion

Author

Konishi, Takao, Kawakami, Rika, Vozenilek, Aimee E., Ghosh, Saikat Kumar B., Xu, Weili, Grogan, Alyssa, Shah, Palak, Tanaka, Takamasa, Sekimoto, Teruo, Shiraki, Tatsuya, Kawai, Kenji, Sato, Yu, Mori, Masayuki, Sakamoto, Atsushi, Hisadome, Hideki, Ashida, Kazuhiro, Bellissard, Arielle, Williams, Desiree, Dryanovski, Dilyan, Kutys, Robert, Cheng, Qi, Romero, Maria, Chahal, Diljon, Virmani, Renu, and Finn, Aloke V.

Published
2024
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11. Prediction of the development of new coronary atherosclerotic plaques with radiomics

Author

Lee, Sang-Eun, Hong, Youngtaek, Hong, Jongsoo, Jung, Juyeong, Sung, Ji Min, Andreini, Daniele, Al-Mallah, Mouaz H., Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Chun, Eun Ju, Conte, Edoardo, Gottlieb, Ilan, Hadamitzky, Martin, Kim, Yong Jin, Lee, Byoung Kwon, Leipsic, Jonathon A., Maffei, Erica, Marques, Hugo, Gonçalves, Pedro de Araújo, Pontone, Gianluca, Shin, Sanghoon, Stone, Peter H., Samady, Habib, Virmani, Renu, Narula, Jagat, Shaw, Leslee J., Bax, Jeroen J., Lin, Fay Y., Min, James K., and Chang, Hyuk-Jae

Published
2024
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13. Glycemic control is independently associated with rapid progression of coronary atherosclerosis in the absence of a baseline coronary plaque burden: a retrospective case–control study from the PARADIGM registry

Author

Won, Ki-Bum, Lee, Byoung Kwon, Lin, Fay Y, Hadamitzky, Martin, Kim, Yong-Jin, Sung, Ji Min, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, de Araújo Gonçalves, Pedro, Leipsic, Jonathon A, Lee, Sang-Eun, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Berman, Daniel S, Narula, Jagat, Shaw, Leslee J, Bax, Jeroen J, Min, James K, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Aging, Heart Disease - Coronary Heart Disease, Atherosclerosis, Cardiovascular, Heart Disease, Biomedical Imaging, Clinical Research, Prevention, Humans, Male, Middle Aged, Aged, Female, Plaque, Atherosclerotic, Coronary Artery Disease, Retrospective Studies, Coronary Angiography, Case-Control Studies, Glycemic Control, Glycated Hemoglobin, Prospective Studies, Disease Progression, Computed Tomography Angiography, Coronary Vessels, Registries, Predictive Value of Tests, Hemoglobin A1c, Coronary artery disease, Progression, Coronary computed tomography angiography, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

The baseline coronary plaque burden is the most important factor for rapid plaque progression (RPP) in the coronary artery. However, data on the independent predictors of RPP in the absence of a baseline coronary plaque burden are limited. Thus, this study aimed to investigate the predictors for RPP in patients without coronary plaques on baseline coronary computed tomography angiography (CCTA) images. A total of 402 patients (mean age: 57.6 ± 10.0 years, 49.3% men) without coronary plaques at baseline who underwent serial coronary CCTA were identified from the Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry and included in this retrospective study. RPP was defined as an annual change of ≥ 1.0%/year in the percentage atheroma volume (PAV). During a median inter-scan period of 3.6 years (interquartile range: 2.7-5.0 years), newly developed coronary plaques and RPP were observed in 35.6% and 4.2% of the patients, respectively. The baseline traditional risk factors, i.e., advanced age (≥ 60 years), male sex, hypertension, diabetes mellitus, hyperlipidemia, obesity, and current smoking status, were not significantly associated with the risk of RPP. Multivariate linear regression analysis showed that the serum hemoglobin A1c level (per 1% increase) measured at follow-up CCTA was independently associated with the annual change in the PAV (β: 0.098, 95% confidence interval [CI]: 0.048-0.149; P

Published
2022

15. Polygenic Risk Score Associates With Atherosclerotic Plaque Characteristics at Autopsy

Author

Cornelissen, Anne, Gadhoke, Neel V., Ryan, Kathleen, Hodonsky, Chani J., Mitchell, Rebecca, Bihlmeyer, Nathan, Duong, ThuyVy, Chen, Zhifen, Dikongue, Armelle, Sakamoto, Atsushi, Sato, Yu, Kawakami, Rika, Mori, Masayuki, Kawai, Kenji, Fernandez, Raquel, Ghosh, Saikat Kumar B., Braumann, Ryan, Abebe, Biniyam, Kutys, Robert, Kutyna, Matthew, Romero, Maria E., Kolodgie, Frank D., Miller, Clint L., Hong, Charles C., Grove, Megan L., Brody, Jennifer A., Sotoodehnia, Nona, Arking, Dan E., Schunkert, Heribert, Mitchell, Braxton D., Guo, Liang, Virmani, Renu, and Finn, Aloke V.

Published
2023
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16. Carotid Plaque-RADS: A Novel Stroke Risk Classification System

Author

Saba, Luca, Cau, Riccardo, Murgia, Alessandro, Nicolaides, Andrew N., Wintermark, Max, Castillo, Mauricio, Staub, Daniel, Kakkos, Stavros K., Yang, Qi, Paraskevas, Kosmas I., Yuan, Chun, Edjlali, Myriam, Sanfilippo, Roberto, Hendrikse, Jeroen, Johansson, Elias, Mossa-Basha, Mahmud, Balu, Niranjan, Dichgans, Martin, Saloner, David, Bos, Daniel, Jager, H. Rolf, Naylor, Ross, Faa, Gavino, Suri, Jasjit S., Costello, Justin, Auer, Dorothee P., Mcnally, J. Scott, Bonati, Leo H., Nardi, Valentina, van der Lugt, Aad, Griffin, Maura, Wasserman, Bruce A., Kooi, M. Eline, Gillard, Jonathan, Lanzino, Giuseppe, Mikhailidis, Dimitri P., Mandell, Daniel M., Benson, John C., van Dam-Nolen, Dianne H.K., Kopczak, Anna, Song, Jae W., Gupta, Ajay, DeMarco, J. Kevin, Chaturvedi, Seemant, Virmani, Renu, Hatsukami, Thomas S., Brown, Martin, Moody, Alan R., Libby, Peter, Schindler, Andreas, and Saam, Tobias

Published
2024
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17. Topological Data Analysis of Coronary Plaques Demonstrates the Natural History of Coronary Atherosclerosis

Author

Hwang, Doyeon, Kim, Haneol J, Lee, Seung-Pyo, Lim, Seonhee, Koo, Bon-Kwon, Kim, Yong-Jin, Kook, Woong, Andreini, Daniele, Al-Mallah, Mouaz H, Budoff, Matthew J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Leipsic, Jonathon A, Maffei, Erica, Pontone, Gianluca, Raff, Gilbert L, Shin, Sanghoon, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Lee, Sang-Eun, Berman, Daniel S, Lin, Fay Y, Virmani, Renu, Samady, Habib, Stone, Peter H, Narula, Jagat, Bax, Jeroen J, Shaw, Leslee J, Min, James K, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Atherosclerosis, Cardiovascular, Heart Disease, Biomedical Imaging, Heart Disease - Coronary Heart Disease, Clinical Research, Coronary Artery Disease, Data Analysis, Exercise, Humans, Predictive Value of Tests, coronary computed tomography angiography, coronary plaque, topological data analysis, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThis study sought to identify distinct patient groups and their association with outcome based on the patient similarity network using quantitative coronary plaque characteristics from coronary computed tomography angiography (CTA).BackgroundCoronary CTA can noninvasively assess coronary plaques quantitatively.MethodsPatients who underwent 2 coronary CTAs at a minimum of 24 months' interval were analyzed (n = 1,264). A similarity Mapper network of patients was built by topological data analysis (TDA) based on the whole-heart quantitative coronary plaque analysis on coronary CTA to identify distinct patient groups and their association with outcome.ResultsThree distinct patient groups were identified by TDA, and the patient similarity network by TDA showed a closed loop, demonstrating a continuous trend of coronary plaque progression. Group A had the least coronary plaque amount (median 12.4 mm3 [interquartile range (IQR): 0.0 to 39.6 mm3]) in the entire coronary tree. Group B had a moderate coronary plaque amount (31.7 mm3 [IQR: 0.0 to 127.4 mm3]) with relative enrichment of fibrofatty and necrotic core (32.6% [IQR: 16.7% to 46.2%] and 2.7% [IQR: 0.1% to 6.9%] of the total plaque, respectively) components. Group C had the largest coronary plaque amount (187.0 mm3 [IQR: 96.7 to 306.4 mm3]) and was enriched for dense calcium component (46.8% [IQR: 32.0% to 63.7%] of the total plaque). At follow-up, total plaque volume, fibrous, and dense calcium volumes increased in all groups, but the proportion of fibrofatty component decreased in groups B and C, whereas the necrotic core portion decreased in only group B (all p

Published
2021

19. Radiation-Induced Vascular Disease--A State-of-the-Art Review

Author

Yang, Eric H, Marmagkiolis, Konstantinos, Balanescu, Dinu V, Hakeem, Abdul, Donisan, Teodora, Finch, William, Virmani, Renu, Herrman, Joerg, Cilingiroglu, Mehmet, Grines, Cindy L, Toutouzas, Konstantinos, and Iliescu, Cezar

Published
2021

21. Effects of renin-angiotensin-aldosterone-system inhibitors on coronary atherosclerotic plaques: The PARADIGM registry

Author

Williams, Curtis, Han, Donghee, Takagi, Hidenobu, Fordyce, Christopher B., Sellers, Stephanie, Blanke, Philipp, Lin, Fay Y., Shaw, Leslee J., Lee, Sang-Eun, Andreini, Daniele, Al-Mallah, Mouaz H., Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Maffei, Erica, Pontone, Gianluca, Shin, Sanghoon, Kim, Yong-Jin, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Virmani, Renu, Samady, Habib, Stone, Peter H., Berman, Daniel S., Narula, Jagat, Bax, Jeroen J., Leipsic, Jonathon A., and Chang, Hyuk-Jae

Published
2023
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25. The Relationship Between Coronary Calcification and the Natural History of Coronary Artery Disease

Author

Jin, Han-Young, Weir-McCall, Jonathan R, Leipsic, Jonathon A, Son, Jang-Won, Sellers, Stephanie L, Shao, Michael, Blanke, Philipp, Ahmadi, Amir, Hadamitzky, Martin, Kim, Yong-Jin, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Lee, Byoung Kwon, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, de Araujo Goncalves, Pedio, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Shaw, Leslee J, Bax, Jeroen J, Chinnaiyan, Kavitha, Raff, Gilbert, Al-Mallah, Mouaz H, Lin, Fay Y, Min, James K, Sung, Ji Min, Lee, Sang-Eun, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Biomedical Imaging, Heart Disease, Cardiovascular, Heart Disease - Coronary Heart Disease, Atherosclerosis, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Disease Progression, Humans, Plaque, Atherosclerotic, Predictive Value of Tests, Risk Factors, Vascular Calcification, atherosclerosis, coronary artery calcium, coronary artery disease, coronary computed tomography angiography, statins, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThe aim of the current study was to explore the impact of plaque calcification in terms of absolute calcified plaque volume (CPV) and in the context of its percentage of the total plaque volume at a lesion and patient level on the progression of coronary artery disease.BackgroundCoronary artery calcification is an established marker of risk of future cardiovascular events. Despite this, plaque calcification is also considered a marker of plaque stability, and it increases in response to medical therapy.MethodsThis analysis included 925 patients with 2,568 lesions from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry, in which patients underwent clinically indicated serial coronary computed tomography angiography. Plaque calcification was examined by using CPV and percent CPV (PCPV), calculated as (CPV/plaque volume) × 100 at a per-plaque and per-patient level (summation of all individual plaques).ResultsCPV was strongly correlated with plaque volume (r = 0.780; p

Published
2021

26. Age- and sex-related features of atherosclerosis from coronary computed tomography angiography in patients prior to acute coronary syndrome: results from the ICONIC study

Author

Conte, Edoardo, Dwivedi, Aeshita, Mushtaq, Saima, Pontone, Gianluca, Lin, Fay Y, Hollenberg, Emma J, Lee, Sang-Eun, Bax, Jeroen, Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin JW, Cury, Ricardo C, Feuchtner, Gudrun, Hadamitzky, Martin, Kim, Yong-Jin, Baggiano, Andrea, Leipsic, Jonathon, Maffei, Erica, Marques, Hugo, Plank, Fabian, Raff, Gilbert L, van Rosendael, Alexander R, Villines, Todd C, Weirich, Harald G, Al’Aref, Subhi J, Baskaran, Lohendran, Cho, Iksung, Danad, Ibrahim, Han, Donghee, Heo, Ran, Lee, Ji Hyun, Stuijfzand, Wijnand J, Gransar, Heidi, Lu, Yao, Sung, Ji Min, Park, Hyung-Bok, Al-Mallah, Mouaz H, de Araújo Gonçalves, Pedro, Berman, Daniel S, Budoff, Matthew J, Samady, Habib, Shaw, Leslee J, Stone, Peter H, Virmani, Renu, Narula, Jagat, Min, James K, Chang, Hyuk-Jae, and Andreini, Daniele

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease, Atherosclerosis, Biomedical Imaging, Aging, Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, Acute Coronary Syndrome, Aged, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Female, Humans, Male, Plaque, Atherosclerotic, atherosclerosis, gender medicine, cardiac CT, high-risk plaque features, CCTA, Cardiovascular medicine and haematology
Abstract

AimsAlthough there is increasing evidence supporting coronary atherosclerosis evaluation by coronary computed tomography angiography (CCTA), no data are available on age and sex differences for quantitative plaque features. The aim of this study was to investigate sex and age differences in both qualitative and quantitative atherosclerotic features from CCTA prior to acute coronary syndrome (ACS).Methods and resultsWithin the ICONIC study, in which 234 patients with subsequent ACS were propensity matched 1:1 with 234 non-event controls, our current subanalysis included only the ACS cases. Both qualitative and quantitative advance plaque analysis by CCTA were performed by a core laboratory. In 129 cases, culprit lesions identified by invasive coronary angiography at the time of ACS were co-registered to baseline CCTA precursor lesions. The study population was then divided into subgroups according to sex and age (

Published
2021

27. Quantitative assessment of coronary plaque volume change related to triglyceride glucose index: The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry

Author

Won, Ki-Bum, Lee, Byoung Kwon, Park, Hyung-Bok, Heo, Ran, Lee, Sang-Eun, Rizvi, Asim, Lin, Fay Y, Kumar, Amit, Hadamitzky, Martin, Kim, Yong-Jin, Sung, Ji Min, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, de Araújo Gonçalves, Pedro, Leipsic, Jonathon A, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Chinnaiyan, Kavitha, Raff, Gilbert L, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Shaw, Leslee J, Bax, Jeroen J, Min, James K, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease - Coronary Heart Disease, Clinical Research, Biomedical Imaging, Cardiovascular, Aging, Atherosclerosis, Heart Disease, Aged, Biomarkers, Blood Glucose, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Disease Progression, Female, Humans, Male, Middle Aged, Multidetector Computed Tomography, Plaque, Atherosclerotic, Predictive Value of Tests, Registries, Time Factors, Triglycerides, Triglyceride glucose index, Coronary artery disease, Coronary computed tomography angiography, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundThe association between triglyceride glucose (TyG) index and coronary atherosclerotic change remains unclear. We aimed to evaluate the association between TyG index and coronary plaque progression (PP) using serial coronary computed tomography angiography (CCTA).MethodsA total of 1143 subjects (aged 60.7 ± 9.3 years, 54.6% male) who underwent serial CCTA with available data on TyG index and diabetic status were analyzed from The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry. PP was defined as plaque volume (PV) (mm3) at follow-up minus PV at index > 0. Annual change of PV (mm3/year) was defined as PV change divided by inter-scan period. Rapid PP was defined as the progression of percent atheroma volume (PV divided by vessel volume multiplied by 100) ≥ 1.0%/year.ResultsThe median inter-scan period was 3.2 (range 2.6-4.4) years. All participants were stratified into three groups based on TyG index tertiles. The overall incidence of PP was 77.3%. Baseline total PV (group I [lowest]: 30.8 (0.0-117.7), group II: 47.2 (6.2-160.4), and group III [highest]: 57.5 (8.4-154.3); P

Published
2020

28. Transcriptomic-based clustering of human atherosclerotic plaques identifies subgroups with different underlying biology and clinical presentation

Author

Mokry, Michal, Boltjes, Arjan, Slenders, Lotte, Bel-Bordes, Gemma, Cui, Kai, Brouwer, Eli, Mekke, Joost M., Depuydt, Marie A. C., Timmerman, Nathalie, Waissi, Farahnaz, Verwer, Maarten C., Turner, Adam W., Khan, Mohammad Daud, Hodonsky, Chani J., Diez Benavente, Ernest, Hartman, Robin J. G., van den Dungen, Noortje A. M., Lansu, Nico, Nagyova, Emilia, Prange, Koen H. M., Kovacic, Jason C., Björkegren, Johan L. M., Pavlos, Eleftherios, Andreakos, Evangelos, Schunkert, Heribert, Owens, Gary K., Monaco, Claudia, Finn, Aloke V., Virmani, Renu, Leeper, Nicholas J., de Winther, Menno P. J., Kuiper, Johan, de Borst, Gert J., Stroes, Erik S. G., Civelek, Mete, de Kleijn, Dominique P. V., den Ruijter, Hester M., Asselbergs, Folkert W., van der Laan, Sander W., Miller, Clint L., and Pasterkamp, Gerard

Published
2022
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30. A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA

Author

Al'Aref, Subhi J, Singh, Gurpreet, Choi, Jeong W, Xu, Zhuoran, Maliakal, Gabriel, van Rosendael, Alexander R, Lee, Benjamin C, Fatima, Zahra, Andreini, Daniele, Bax, Jeroen J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin JW, Conte, Edoardo, Cury, Ricardo C, Feuchtner, Gudruf, Hadamitzky, Martin, Kim, Yong-Jin, Lee, Sang-Eun, Leipsic, Jonathon A, Maffei, Erica, Marques, Hugo, Plank, Fabian, Pontone, Gianluca, Raff, Gilbert L, Villines, Todd C, Weirich, Harald G, Cho, Iksung, Danad, Ibrahim, Han, Donghee, Heo, Ran, Lee, Ji Hyun, Rizvi, Asim, Stuijfzand, Wijnand J, Gransar, Heidi, Lu, Yao, Sung, Ji Min, Park, Hyung-Bok, Berman, Daniel S, Budoff, Matthew J, Samady, Habib, Stone, Peter H, Virmani, Renu, Narula, Jagat, Chang, Hyuk-Jae, Lin, Fay Y, Baskaran, Lohendran, Shaw, Leslee J, and Min, James K

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Cardiovascular, Clinical Research, Heart Disease, Heart Disease - Coronary Heart Disease, Atherosclerosis, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Algorithms, Case-Control Studies, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Stenosis, Humans, Plaque, Atherosclerotic, Predictive Value of Tests, Severity of Illness Index, acute coronary syndrome, coronary computed tomography angiography, diameter stenosis, machine learning, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThis study sought to identify culprit lesion (CL) precursors among acute coronary syndrome (ACS) patients based on qualitative and quantitative computed tomography-based plaque characteristics.BackgroundCoronary computed tomography angiography (CTA) has been validated for patient-level prediction of ACS. However, the applicability of coronary CTA to CL assessment is not known.MethodsUtilizing the ICONIC (Incident COroNary Syndromes Identified by Computed Tomography) study, a nested case-control study of 468 patients with baseline coronary CTA, the study included ACS patients with invasive coronary angiography-adjudicated CLs that could be aligned to CL precursors on baseline coronary CTA. Separate blinded core laboratories adjudicated CLs and performed atherosclerotic plaque evaluation. Thereafter, the study used a boosted ensemble algorithm (XGBoost) to develop a predictive model of CLs. Data were randomly split into a training set (80%) and a test set (20%). The area under the receiver-operating characteristic curve of this model was compared with that of diameter stenosis (model 1), high-risk plaque features (model 2), and lesion-level features of CL precursors from the ICONIC study (model 3). Thereafter, the machine learning (ML) model was applied to 234 non-ACS patients with 864 lesions to determine model performance for CL exclusion.ResultsCL precursors were identified by both coronary angiography and baseline coronary CTA in 124 of 234 (53.0%) patients, with a total of 582 lesions (containing 124 CLs) included in the analysis. The ML model demonstrated significantly higher area under the receiver-operating characteristic curve for discriminating CL precursors (0.774; 95% confidence interval [CI]: 0.758 to 0.790) compared with model 1 (0.599; 95% CI: 0.599 to 0.599; p

Published
2020

31. Non-obstructive high-risk plaques increase the risk of future culprit lesions comparable to obstructive plaques without high-risk features: the ICONIC study

Author

Ferraro, Richard A, van Rosendael, Alexander R, Lu, Yao, Andreini, Daniele, Al-Mallah, Mouaz H, Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin JW, Conte, Edoardo, Cury, Ricardo C, Feuchtner, Gudrun, de Araújo Gonçalves, Pedro, Hadamitzky, Martin, Kim, Yong-Jin, Leipsic, Jonathon, Maffei, Erica, Marques, Hugo, Plank, Fabian, Pontone, Gianluca, Raff, Gilbert L, Villines, Todd C, Lee, Sang-Eun, Al’Aref, Subhi J, Baskaran, Lohendran, Cho, Iksung, Danad, Ibrahim, Gransar, Heidi, Budoff, Matthew J, Samady, Habib, Stone, Peter H, Virmani, Renu, Narula, Jagat, Berman, Daniel S, Chang, Hyuk-Jae, Bax, Jeroen J, Min, James K, Shaw, Leslee J, and Lin, Fay Y

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Research, Heart Disease - Coronary Heart Disease, Heart Disease, Atherosclerosis, Cardiovascular, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Acute Coronary Syndrome, Aged, Case-Control Studies, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Female, Humans, Male, Middle Aged, Plaque, Atherosclerotic, Predictive Value of Tests, Retrospective Studies, Risk Factors, Coronary computed tomographic angiography, coronary artery disease, myocardial infarction, Cardiovascular medicine and haematology
Abstract

AimsHigh-risk plaque (HRP) and non-obstructive coronary artery disease independently predict adverse events, but their importance to future culprit lesions has not been resolved. We sought to determine in patients prior to confirmed acute coronary syndrome (ACS) the association between lesion percent diameter stenosis (%DS), and the absolute number and prevalence of HRP. The secondary objective was to examine the relative importance of non-obstructive HRP in future culprit lesions.Methods and resultsWithin the ICONIC study, a nested case-control study of patients undergoing coronary computed tomographic angiography (coronary CT), we included ACS cases with culprit lesions confirmed by invasive coronary angiography and coregistered to baseline coronary CT. Quantitative CT was used to evaluate obstructive (≥50%) and non-obstructive (

Published
2020

32. Coronary Computed Tomography Angiography From Clinical Uses to Emerging Technologies JACC State-of-the-Art Review

Author

Abdelrahman, Khaled M, Chen, Marcus Y, Dey, Amit K, Virmani, Renu, Finn, Aloke V, Khamis, Ramzi Y, Choi, Andrew D, Min, James K, Williams, Michelle C, Buckler, Andrew J, Taylor, Charles A, Rogers, Campbell, Samady, Habib, Antoniades, Charalambos, Shaw, Leslee J, Budoff, Matthew J, Hoffmann, Udo, Blankstein, Ron, Narula, Jagat, and Mehta, Nehal N

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease, Biomedical Imaging, Cardiovascular, Atherosclerosis, Heart Disease - Coronary Heart Disease, 4.1 Discovery and preclinical testing of markers and technologies, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Biomedical Technology, Chest Pain, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Humans, Review Literature as Topic, Risk Assessment, Vascular Calcification, atherosclerosis, coronary artery disease, coronary computed tomography angiography, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

Evaluation of coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) has seen a paradigm shift in the last decade. Evidence increasingly supports the clinical utility of CCTA across various stages of CAD, from the detection of early subclinical disease to the assessment of acute chest pain. Additionally, CCTA can be used to noninvasively quantify plaque burden and identify high-risk plaque, aiding in diagnosis, prognosis, and treatment. This is especially important in the evaluation of CAD in immune-driven conditions with increased cardiovascular disease prevalence. Emerging applications of CCTA based on hemodynamic indices and plaque characterization may provide personalized risk assessment, affect disease detection, and further guide therapy. This review provides an update on the evidence, clinical applications, and emerging technologies surrounding CCTA as highlighted at the 2019 National Heart, Lung and Blood Institute CCTA Summit.

Published
2020

33. Percent atheroma volume: Optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study

Author

van Rosendael, Alexander R, Lin, Fay Y, Ma, Xiaoyue, van den Hoogen, Inge J, Gianni, Umberto, Al Hussein, Omar, Al'Aref, Subhi J, Peña, Jessica M, Andreini, Daniele, Al-Mallah, Mouaz H, Budoff, Matthew J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Leipsic, Jonathon A, Maffei, Erica, Pontone, Gianluca, Raff, Gilbert L, Shin, Sanghoon, Kim, Yong-Jin, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Lee, Sang-Eun, Berman, Daniel S, Virmani, Renu, Samady, Habib, Stone, Peter H, Narula, Jagat, Bax, Jeroen J, Shaw, Leslee J, Min, James K, and Chang, Hyuk-Jae

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Cardiovascular, Atherosclerosis, Heart Disease - Coronary Heart Disease, Aging, Biomedical Imaging, Clinical Research, Heart Disease, Aged, Body Surface Area, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Disease Progression, Female, Humans, Male, Middle Aged, Plaque, Atherosclerotic, Predictive Value of Tests, Prospective Studies, Registries, Severity of Illness Index, Sex Factors, Time Factors, Imaging, Percent atheroma volume, Coronary CTA, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Applied computing
Abstract

BACKGROUND AND AIMS:Different methodologies to report whole-heart atherosclerotic plaque on coronary computed tomography angiography (CCTA) have been utilized. We examined which of the three commonly used plaque burden definitions was least affected by differences in body surface area (BSA) and sex. METHODS:The PARADIGM study includes symptomatic patients with suspected coronary atherosclerosis who underwent serial CCTA >2 years apart. Coronary lumen, vessel, and plaque were quantified from the coronary tree on a 0.5 mm cross-sectional basis by a core-lab, and summed to per-patient. Three quantitative methods of plaque burden were employed: (1) total plaque volume (PV) in mm3, (2) percent atheroma volume (PAV) in % [which equaled: PV/vessel volume * 100%], and (3) normalized total atheroma volume (TAVnorm) in mm3 [which equaled: PV/vessel length * mean population vessel length]. Only data from the baseline CCTA were used. PV, PAV, and TAVnorm were compared between patients in the top quartile of BSA vs the remaining, and between sexes. Associations between vessel volume, BSA, and the three plaque burden methodologies were assessed. RESULTS:The study population comprised 1479 patients (age 60.7 ± 9.3 years, 58.4% male) who underwent CCTA. A total of 17,649 coronary artery segments were evaluated with a median of 12 (IQR 11-13) segments per-patient (from a 16-segment coronary tree). Patients with a large BSA (top quartile), compared with the remaining patients, had a larger PV and TAVnorm, but similar PAV. The relation between larger BSA and larger absolute plaque volume (PV and TAVnorm) was mediated by the coronary vessel volume. Independent from the atherosclerotic cardiovascular disease risk (ASCVD) score, vessel volume correlated with PV (P

Published
2020

34. Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry

Author

Han, Donghee, Kolli, Kranthi K, Al'Aref, Subhi J, Baskaran, Lohendran, van Rosendael, Alexander R, Gransar, Heidi, Andreini, Daniele, Budoff, Matthew J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Leipsic, Jonathon A, Maffei, Erica, Pontone, Gianluca, Raff, Gilbert L, Shin, Sangshoon, Kim, Yong‐Jin, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Lee, Sang‐Eun, Virmani, Renu, Samady, Habib, Stone, Peter, Narula, Jagat, Berman, Daniel S, Bax, Jeroen J, Shaw, Leslee J, Lin, Fay Y, Min, James K, and Chang, Hyuk‐Jae

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Atherosclerosis, Heart Disease, Aging, Heart Disease - Coronary Heart Disease, Cardiovascular, Biomedical Imaging, Clinical Research, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Aged, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Diagnosis, Computer-Assisted, Disease Progression, Female, Humans, Machine Learning, Male, Middle Aged, Multidetector Computed Tomography, Plaque, Atherosclerotic, Predictive Value of Tests, Prospective Studies, Radiographic Image Interpretation, Computer-Assisted, Registries, Time Factors, coronary artery disease, coronary computed tomography angiography, machine learning, plaque progression, risk prediction, Cardiorespiratory Medicine and Haematology, Cardiovascular medicine and haematology
Abstract

Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P

Published
2020

35. Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning

Author

Baskaran, Lohendran, Al’Aref, Subhi J, Maliakal, Gabriel, Lee, Benjamin C, Xu, Zhuoran, Choi, Jeong W, Lee, Sang-Eun, Sung, Ji Min, Lin, Fay Y, Dunham, Simon, Mosadegh, Bobak, Kim, Yong-Jin, Gottlieb, Ilan, Lee, Byoung Kwon, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, Shin, Sanghoon, Choi, Jung Hyun, Chinnaiyan, Kavitha, Hadamitzky, Martin, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Leipsic, Jonathon A, Raff, Gilbert L, Virmani, Renu, Samady, Habib, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Bax, Jeroen J, Chang, Hyuk-Jae, Min, James K, and Shaw, Leslee J

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Biomedical Imaging, Heart Disease, Cardiovascular, Aged, Computed Tomography Angiography, Coronary Vessels, Deep Learning, Female, Heart, Heart Atria, Heart Ventricles, Humans, Male, Middle Aged, General Science & Technology
Abstract

OBJECTIVES:To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND:Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS:Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS:The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS:An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.

Published
2020

36. Differential association between the progression of coronary artery calcium score and coronary plaque volume progression according to statins: the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (PARADIGM) study

Author

Lee, Sang-Eun, Sung, Ji Min, Andreini, Daniele, Budoff, Matthew J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Chun, Eun Ju, Conte, Edoardo, Gottlieb, Ilan, Hadamitzky, Martin, Kim, Yong Jin, Kumar, Amit, Lee, Byoung Kwon, Leipsic, Jonathon A, Maffei, Erica, Marques, Hugo, Pontone, Gianluca, Raff, Gilbert, Shin, Sanghoon, Stone, Peter H, Samady, Habib, Virmani, Renu, Narula, Jagat, Berman, Daniel S, Shaw, Leslee J, Bax, Jeroen J, Lin, Fay Y, Min, James K, and Chang, Hyuk-Jae

Subjects
Atherosclerosis, Biomedical Imaging, Cardiovascular, Heart Disease, Heart Disease - Coronary Heart Disease, Clinical Research, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Disease Progression, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Middle Aged, Plaque, Atherosclerotic, Prospective Studies, Registries, Vascular Calcification, coronary artery atherosclerosis, statins, coronary computed tomography angiography, coronary artery calcium score, coronary artery calcification, Agatston score, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology
Abstract

AimsCoronary artery calcium score (CACS) is a strong predictor of major adverse cardiac events (MACE). Conversely, statins, which markedly reduce MACE risk, increase CACS. We explored whether CACS progression represents compositional plaque volume (PV) progression differently according to statin use.Methods and resultsFrom a prospective multinational registry of consecutive patients (n = 2252) who underwent serial coronary computed tomography angiography (CCTA) at a ≥ 2-year interval, 654 patients (61 ± 10 years, 56% men, inter-scan interval 3.9 ± 1.5 years) with information regarding the use of statins and having a serial CACS were included. Patients were divided into non-statin (n = 246) and statin-taking (n = 408) groups. Coronary PVs (total, calcified, and non-calcified; sum of fibrous, fibro-fatty, and lipid-rich) were quantitatively analysed, and CACS was measured from both CCTAs. Multivariate linear regression models were constructed for both statin-taking and non-statin group to assess the association between compositional PV change and change in CACS. In multivariate linear regression analysis, in the non-statin group, CACS increase was positively associated with both non-calcified (β = 0.369, P = 0.004) and calcified PV increase (β = 1.579, P

Published
2019

37. Clinical and Coronary Plaque Predictors of Atherosclerotic Nonresponse to Statin Therapy

Author

van Rosendael, Sophie E., van den Hoogen, Inge J., Lin, Fay Y., Andreini, Daniele, Al-Mallah, Mouaz H., Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Conte, Edoardo, Marques, Hugo, de Araújo Gonçalves, Pedro, Gottlieb, Ilan, Hadamitzky, Martin, Leipsic, Jonathon A., Maffei, Erica, Pontone, Gianluca, Raff, Gilbert L., Shin, Sanghoon, Kim, Yong-Jin, Lee, Byoung Kwon, Chun, Eun Ju, Sung, Ji Min, Lee, Sang-Eun, Virmani, Renu, Samady, Habib, Stone, Peter H., Min, James K., Narula, Jagat, Shaw, Leslee J., Chang, Hyuk-Jae, van Rosendael, Alexander R., and Bax, Jeroen J.

Published
2023
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39. Relationships between neighborhood disadvantage and cardiovascular findings at autopsy in subjects with sudden death

Author

Cornelissen, Anne, Guo, Liang, Neally, Sam J., Kleinberg, Leah, Forster, Ashley, Nair, Rajeev, Gadhoke, Neel, Ghosh, Saikat Kumar B., Sakamoto, Atsushi, Sato, Yu, Kawakami, Rika, Mori, Masayuki, Kawai, Kenji, Fernandez, Raquel, Dikongue, Armelle, Abebe, Biniyam, Kutys, Robert, Romero, Maria E., Kolodgie, Frank D., Baumer, Yvonne, Powell-Wiley, Tiffany M., Virmani, Renu, and Finn, Aloke V.

Published
2023
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40. Optical coherence tomography in coronary atherosclerosis assessment and intervention

Author

Araki, Makoto, Park, Seung-Jung, Dauerman, Harold L., Uemura, Shiro, Kim, Jung-Sun, Di Mario, Carlo, Johnson, Thomas W., Guagliumi, Giulio, Kastrati, Adnan, Joner, Michael, Holm, Niels Ramsing, Alfonso, Fernando, Wijns, William, Adriaenssens, Tom, Nef, Holger, Rioufol, Gilles, Amabile, Nicolas, Souteyrand, Geraud, Meneveau, Nicolas, Gerbaud, Edouard, Opolski, Maksymilian P., Gonzalo, Nieves, Tearney, Guillermo J., Bouma, Brett, Aguirre, Aaron D., Mintz, Gary S., Stone, Gregg W., Bourantas, Christos V., Räber, Lorenz, Gili, Sebastiano, Mizuno, Kyoichi, Kimura, Shigeki, Shinke, Toshiro, Hong, Myeong-Ki, Jang, Yangsoo, Cho, Jin Man, Yan, Bryan P., Porto, Italo, Niccoli, Giampaolo, Montone, Rocco A., Thondapu, Vikas, Papafaklis, Michail I., Michalis, Lampros K., Reynolds, Harmony, Saw, Jacqueline, Libby, Peter, Weisz, Giora, Iannaccone, Mario, Gori, Tommaso, Toutouzas, Konstantinos, Yonetsu, Taishi, Minami, Yoshiyasu, Takano, Masamichi, Raffel, O. Christopher, Kurihara, Osamu, Soeda, Tsunenari, Sugiyama, Tomoyo, Kim, Hyung Oh, Lee, Tetsumin, Higuma, Takumi, Nakajima, Akihiro, Yamamoto, Erika, Bryniarski, Krzysztof L., Di Vito, Luca, Vergallo, Rocco, Fracassi, Francesco, Russo, Michele, Seegers, Lena M., McNulty, Iris, Park, Sangjoon, Feldman, Marc, Escaned, Javier, Prati, Francesco, Arbustini, Eloisa, Pinto, Fausto J., Waksman, Ron, Garcia-Garcia, Hector M., Maehara, Akiko, Ali, Ziad, Finn, Aloke V., Virmani, Renu, Kini, Annapoorna S., Daemen, Joost, Kume, Teruyoshi, Hibi, Kiyoshi, Tanaka, Atsushi, Akasaka, Takashi, Kubo, Takashi, Yasuda, Satoshi, Croce, Kevin, Granada, Juan F., Lerman, Amir, Prasad, Abhiram, Regar, Evelyn, Saito, Yoshihiko, Sankardas, Mullasari Ajit, Subban, Vijayakumar, Weissman, Neil J., Chen, Yundai, Yu, Bo, Nicholls, Stephen J., Barlis, Peter, West, Nick E. J., Arbab-Zadeh, Armin, Ye, Jong Chul, Dijkstra, Jouke, Lee, Hang, Narula, Jagat, Crea, Filippo, Nakamura, Sunao, Kakuta, Tsunekazu, Fujimoto, James, Fuster, Valentin, and Jang, Ik-Kyung

Published
2022
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46. Age related compositional plaque burden by CT in patients with future ACS

Author

van Rosendael, Alexander R., van den Hoogen, Inge J., Lin, Fay Y., Gianni, Umberto, Lu, Yao, Andreini, Daniele, Al-Mallah, Mouaz H., Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin J.W., Conte, Edoardo, Cury, Ricardo C., Feuchtner, Gudrun, de Araújo Gonçalves, Pedro, Hadamitzky, Martin, Kim, Yong-Jin, Leipsic, Jonathon A., Maffei, Erica, Marques, Hugo, Plank, Fabian, Pontone, Gianluca, Raff, Gilbert L., Villines, Todd C., Lee, Sang-Eun, Al’Aref, Subhi J., Baskaran, Lohendran, Cho, Iksung, Danad, Ibrahim, Gransar, Heidi, Budoff, Matthew J., Samady, Habib, Virmani, Renu, Min, James K., Narula, Jagat, Berman, Daniel S., Chang, Hyuk-Jae, Shaw, Leslee J., and Bax, Jeroen J.

Published
2022
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47. Longitudinal quantitative assessment of coronary plaque progression related to body mass index using serial coronary computed tomography angiography.

Author

Won, Ki-Bum, Lee, Sang-Eun, Lee, Byoung Kwon, Park, Hyung-Bok, Heo, Ran, Rizvi, Asim, Hadamitzky, Martin, Kim, Yong-Jin, Sung, Ji Min, Conte, Edoardo, Andreini, Daniele, Pontone, Gianluca, Budoff, Matthew J, Gottlieb, Ilan, Chun, Eun Ju, Cademartiri, Filippo, Maffei, Erica, Marques, Hugo, Leipsic, Jonathon A, Shin, Sanghoon, Choi, Jung Hyun, Virmani, Renu, Samady, Habib, Stone, Peter H, Berman, Daniel S, Narula, Jagat, Shaw, Leslee J, Bax, Jeroen J, Min, James K, and Chang, Hyuk-Jae

Subjects
Clinical Research, Obesity, Heart Disease - Coronary Heart Disease, Nutrition, Cardiovascular, Biomedical Imaging, Heart Disease, Aged, Body Mass Index, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Disease Progression, Female, Humans, Longitudinal Studies, Male, Middle Aged, Plaque, Atherosclerotic, Prospective Studies, Radiographic Image Interpretation, Computer-Assisted, Registries, atherosclerosis, coronary computed tomography angiography, body mass index, obesity, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology
Abstract

AimsThis study explored the coronary plaque volume change (PVC) according to the change of percent body mass index (BMI) and categorical BMI group using serial coronary computed tomography angiography (CCTA).Methods and resultsA total of 1568 subjects who underwent serial CCTA with available BMI at baseline (CCTA1) and follow-up (CCTA2) were included. Median inter-scan period was 3.3 (interquartile range: 2.6-4.6) years. Quantitative assessment of coronary plaque was performed at both scans. All participants were categorized into three BMI (kg/m2) groups: normal:

Published
2019

48. A comprehensive evaluation of the genetic architecture of sudden cardiac arrest

Author

Ashar, Foram N, Mitchell, Rebecca N, Albert, Christine M, Newton-Cheh, Christopher, Brody, Jennifer A, Müller-Nurasyid, Martina, Moes, Anna, Meitinger, Thomas, Mak, Angel, Huikuri, Heikki, Junttila, M Juhani, Goyette, Philippe, Pulit, Sara L, Pazoki, Raha, Tanck, Michael W, Blom, Marieke T, Zhao, XiaoQing, Havulinna, Aki S, Jabbari, Reza, Glinge, Charlotte, Tragante, Vinicius, Escher, Stefan A, Chakravarti, Aravinda, Ehret, Georg, Coresh, Josef, Li, Man, Prineas, Ronald J, Franco, Oscar H, Kwok, Pui-Yan, Lumley, Thomas, Dumas, Florence, McKnight, Barbara, Rotter, Jerome I, Lemaitre, Rozenn N, Heckbert, Susan R, O’Donnell, Christopher J, Hwang, Shih-Jen, Tardif, Jean-Claude, VanDenburgh, Martin, Uitterlinden, André G, Hofman, Albert, Stricker, Bruno HC, de Bakker, Paul IW, Franks, Paul W, Jansson, Jan-Hakan, Asselbergs, Folkert W, Halushka, Marc K, Maleszewski, Joseph J, Tfelt-Hansen, Jacob, Engstrøm, Thomas, Salomaa, Veikko, Virmani, Renu, Kolodgie, Frank, Wilde, Arthur AM, Tan, Hanno L, Bezzina, Connie R, Eijgelsheim, Mark, Rioux, John D, Jouven, Xavier, Kääb, Stefan, Psaty, Bruce M, Siscovick, David S, Arking, Dan E, and Sotoodehnia, Nona

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Prevention, Heart Disease, Human Genome, Genetics, Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Arrhythmias, Cardiac, Body Mass Index, Coronary Artery Disease, Death, Sudden, Cardiac, Female, Genome-Wide Association Study, Heart Conduction System, Humans, Male, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Sex Factors, Sudden cardiac arrest, Genome-wide association study, Mendelian randomization, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

AimsSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA.Methods and resultsWe carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25 989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk.ConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.

Published
2018

50. Association Between Changes in Perivascular Adipose Tissue Density and Plaque Progression

Author

Lee, Sang-Eun, Sung, Ji Min, Andreini, Daniele, Al-Mallah, Mouaz H., Budoff, Matthew J., Cademartiri, Filippo, Chinnaiyan, Kavitha, Choi, Jung Hyun, Chun, Eun Ju, Conte, Edoardo, Gottlieb, Ilan, Hadamitzky, Martin, Kim, Yong Jin, Lee, Byoung Kwon, Leipsic, Jonathon A., Maffei, Erica, Marques, Hugo, de Araújo Gonçalves, Pedro, Pontone, Gianluca, Shin, Sanghoon, Kitslaar, Pieter H., Reiber, Johan H.C., Stone, Peter H., Samady, Habib, Virmani, Renu, Narula, Jagat, Berman, Daniel S., Shaw, Leslee J., Bax, Jeroen J., Lin, Fay Y., Min, James K., and Chang, Hyuk-Jae

Published
2022
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