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5. Worldwide Disparities in Recovery of Cardiac Testing 1 Year Into COVID-19

Author

Einstein, Andrew J., Paez, Diana, Dondi, Maurizio, Better, Nathan, Cerci, Rodrigo, Dorbala, Sharmila, Karthikeyan, Ganesan, Pascual, Thomas N.B., Shaw, Leslee J., Villines, Todd C., Vitola, Joao V., Williams, Michelle C., Pynda, Yaroslav, Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Hirschfeld, Cole B., Cohen, Yosef, Erinne, Ikenna, Malkovskiy, Eli, Randazzo, Michael, Sewanan, Lorenzo, Shetty, Mrinali, Choi, Andrew, Lopez-Mattei, Juan, Parwani, Purvi, Goda, Artan, Shirka, Ervina, Bouyoucef, Salah, Chelghoum, Lydia, Mansouri, Farouk, Medjahedi, Abdelkader, Naili, Qais, Ridouh, Mokhtar, Alasia, Diego, Alberghina, Lucia, Aramayo, Natalia, Buchara, Diego, Busso, Franco Gabriel, Bustos Rivadero, Jose Javier, Camilletti, Jorge, Campanelli, Hugo, Campisi, Roxana, Castro, Ricardo Belisario, Daicz, Mariana, del Riego, Horacio, Dragonetti, Laura, Echazarreta, Diego, Erriest, Juan, Faccio, Fernando, Facello, Adolfo, Gallegos, Hugo, Geronazzo, Ricardo, Glait, Horacio, Hasbani, Victor, Jäger, Victor, Lewkowicz, Julio Manuel, Lotti, Jose, Maciel, Neiva, Masoli, Osvaldo, Mastrovito, Edgardo, Medus, Maria, Merani, Maria Fernanda, Molteni, Susana, Montecinos, Marcos, Parisi, Gustavo, Sueldo, Claudio Pereyra, Perez de Arenaza, Diego, Quintana, Luis, Radzinschi, Alejandro, Redruello, Marcela, Rodríguez, Marina, Rojas, Horacio, Acuña, Arturo Romero, Schere, Daniel, Traverso, Sonia, Vazquez, Gustavo, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Crowley, Michael, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Farouque, Omar, Jasper, Kim, Joshi, Subodh, Lee, Joseph, Lee, Kenneth, Lui, Elaine, Mcconachie, Peter, Meaker, Joanne, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Premaratne, Manuja, Prior, David, Rutherford, Natalie, Saunders, Connor, Taubman, Kim, Tauro, Andrew, Taylor, Andrew, Theuerle, James, Thomas, Paul, Tow, Jonathan, Upton, Anthony, Vamadevan, Shankar, Wayne, Victor, Wegner, Eva Alina, Wong, David, Younger, John, Beitzke, Dietrich, Feuchtner, Gudrun, Sommer, Oliver, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Tserakhau, Uladzimir, Homans, Filip, Van De Heyning, Caroline M., Araujo, Raúl, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Almeida, Augusto, Anselmi, Carlos, Azevedo, Guilherme S.A., Bittencourt, Marcio Sommer, Pianta, Diego Bromfman, Cabeda, Estevan, Carreira, Lara, Coelho, Igor, de Amorim Fernandes, Fernando, de Lorenzo, Andrea, Delgado, Roberta, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, Ferreira de Souza, Thiago, Foppa, Murilo, Matos Alves, Wilson Furlan, Gontijo, Cibele, Gottlieb, Ilan, Grossman, Gabriel, Albernaz Siqueira, Maria Helena, Nomura, Cesar Higa, Koga, Katia Hiromoto, Lima, Ronaldo, Lopes, Rafael, Marçal Filho, Hugo Humberto, Masiero, Paulo, Mastrocola, Luiz, Menezes de Siqueira, Maria Eduarda, Mesquita, Claudio, Naves, Danilo, Penna, Filipe, Pinto, Ibraim, Rocha, Thércio, Rocha, Juliana Leal, Rodrigues, Alfredo, Salioni, Leila, Sanches, Adelina, Santos, Marcelo, Da Silva, Leonardo Sara, Schvartzman, Paulo, Matushita, Cristina Sebastião, Senra, Tiago, Silva, Marcelo, Soares, Carlos Eduardo, Spiro, Bernardo, Suaide Silva, Carlos Eduardo, Torres, Rafael, Monte, Guilherme Urpia, Vilela, Andrea, Villa, Alexandre Volney, Vitola, Joao, Voss, Themissa, Waltrick, Roberto, Zapparoli, Marcello, Naseer, Hamid, Garcheva-Tsacheva, Marina, Ouattara, Tiémégna Florence, Thou, Sarameth, Varoeun, Soley, Abikhzer, Gad, Beanlands, Rob, Chetrit, Michael, Dabreo, Dominique, Dennie, Carole, Friedrich, Matthias, Hafez, Mohmmed Nassoh, Hanneman, Kate, Miller, Robert, Oikonomou, Anastasia, Roifman, Idan, Small, Gary, Tandon, Vikas, Trivedi, Adwait, White, James, Zukotynski, Katherine, Alay, Rita, Concha, Carmen, Massardo, Teresa, Abad, Pedro, Anzola, Kelly, Arturo, Harold, Benitez, Luis, Cadena, Alberto, Zamudio, Carlos Caicedo, Calderón, Antonio, Gutierrez Villamil, Claudia T., Jaimes, Claudia, Londono, Juan L., Lopez, Nelson, Merlano-Gaitan, Sonia, Murgieitio-Cabrera, Ramon, Valencia, Manuel, Vergel, Damiana, Santamaria, Alejandro Zuluaga, Solis, Felix, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Prpic, Marina, Felipe Batista, Cuba: Juan, Cabrera, Lazaro Omar, Peix, Amalia, Peña, Yamilé, Rochela Vázquez, Luis Manuel, Ntalas, Ioannis, Kaminek, Milan, Kincl, Vladimir, Lang, Otto, Abdulla, Jawdat, Bøttcher, Morten, Busk, Martin, Geisler, Uka, Gormsen, Lars C., Hansson, Nicolaj, Hess, Søren, Hove, Jens, Jensen, Lars Thorbjoern, Jensen, Magnus T., Kragholm, Kristian Hay, Nørgaard, Bjarne L., Øvrehus, Kristian, Rasmussen, Jan, Rønnow Sand, Niels Peter, Sondergaard, Hanne, Zaremba, Tomas, Speckter, Herwin, Amores, Nelson, Velez, Mayra Sanchez, Alrahman, Taghreed Abd, Elsamad, Sherif Abd, Abdelfattah, Alia, Allam, Adel, Elkaffas, Sameh, Hassan, Mona, Hussein, Elshaymaa, Ibrahim, Ahmed, Kandeel, Ahmed, Ali, Mohamed Mandour, Shaaban, Mahmoud, Flores, Camila, Gómez Leiva, Verónica Vanesa, Liiver, Anita, Larikka, Martti, Uusitalo, Valtteri, Agostini, Denis, Berger, Clothilde, Dietz, Matthieu, Hyafil, Fabien, Ohana, Mickaël, Prigent, Kevin, Regaieg, Hamza, Sarda-Mantel, Laure, H-Ici, Darach O., Ayetey, Harold, Angelidis, George, Fragkaki, Christina, Fragkiadaki, Chrysoula, Georgoulias, Panagiotis, Koutelou, Maria, Kyrozi, Elena, Lama, Niki, Prassopoulos, Vassilis, Spartalis, Michael, Zaglavara, Theodora, Gonzalez, Carla, Gutierrez, Goleat, Maldonado, Alejandro, Martinez, Yassine, Kovács, Attila, Szilveszter, Bálint, Banthia, Nilesh, Bhat, Vivek, Bhatia, Mona, Choudhury, Partha, Chowdekar, Vijay Sai, Christopher, Johann, Garg, Tushar, Goyal, Naresh Kumar, Gupta, Ripen Kumar, Gupta, Abhishek, Hephzibah, Julie, Jain, Shashank, Krupa, Jesu, Kumar, Parveen, Kumar, Sukriti, Lalchandani, Arati, Mishra, Animesh, Mishra, Vivaswan Dutt, Mohan, Parul, Ozair, Ahmad, Pandey, Shivani, Parameswaran, Ramanathapuram, Patel, Chetan, Patel, Tapan, Patel, Shivani, Vimala, Leena Robinson, Kumar Sarangi, Dr Pradosh, Sengupta, Shantanu, Sethi, Arvind, Sharma, Amit, Sharma, Awadhesh Kumar, Sharma, Punit, Shrigiriwar, Apurva, Singh, Santosh, Singh, Harpreet, Sood, Ashwani, Verma, Atul, Vyas, Ajay, Soeriadi, Erwin Affandi, Bun, Edison, Hutomo, Febby, Syawaluddin, Hilman, Yudistiro, Ryan, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Emami-Ardekani, Alireza, Farzanehfar, Saeed, Jafari, Ramezan, Manafi-Farid, Reyhaneh, Tajik, Maryam, Arnson, Yoav, Fuchs, Shmuel, Goldkorn, Ronen, Kennedy, John, Leitman, Marina, Shalev, Aryeh, Acampa, Wanda, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Assante, Roberta, Baritussio, Anna, Bauckneht, Matteo, Bianco, Francesco, Bonfiglioli, Rachele, Bovenzi, Francesco, Bruno, Isabella, Bruno, Andrea, Busnardo, Elena, Califaretti, Elena, Casoni, Roberta, Censullo, Vittorio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Clemente, Alberto, Cuocolo, Alberto, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Della Tommasina, Veronica, Dellegrottaglie, Santo, Erba, Paola Anna, Evangelista, Laura, Faggi, Lara, Faragasso, Evelina, Florimonte, Luigia, Frantellizzi, Viviana, Gatti, Marco, Gaudiano, Angela, Gelardi, Fabrizia, Gerali, Alberto, Gimelli, Alessia, Guglielmo, Marco, Leccisotti, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Marcassa, Claudio, Matassa, Giovanni, Mele, Donato, Milan, Elisa, Mircoli, Luca, Paccagnella, Andrea, Pacella, Sara, Padovano, Federica, Pellegrini, Dario, Pergola, Valeria, Pugliese, Luca, Quartuccio, Natale, Rampin, Lucia, Ricci, Fabrizio, Rubini, Giuseppe, Russo, Vincenzo, Sambuceti, Gianmario, Scatteia, Alessandra, Sciagrà, Roberto, Spidalieri, Gianluca, Stefanelli, Antonella, Tedeschi, Carlo, Ventroni, Guido, Baugh, Dainia, Madu, Ernest, Aikawa, Tadao, Asano, Hiroshi, Fujimoto, Shinichiro, Fujise, Koichiro, Fukushima, Yoshimitsu, Fukuyama, Kae, Ichikawa, Yasutaka, Ideguchi, Reiko, Iguchi, Nobuo, Imai, Masamichi, Ishimura, Hayato, Isobe, Satoshi, Ito, Kimiteru, Izawa, Yu, Kadokami, Toshiaki, Kasai, Tokuo, Kato, Takao, Kawamoto, Takashi, Kiryu, Shigeru, Kumita, Shinichiro, Manabe, Osamu, Maruno, Hirotaka, Matsumoto, Naoya, Miyagawa, Masao, Moroi, Masao, Nagamachi, Shigeki, Nakajima, Kenichi, Nakazato, Ryo, Nanasato, Mamoru, Naya, Masanao, Norikane, Takashi, Ohta, Yasutoshi, Otomi, Yoichi, Otsuka, Hideki, Oyama-Manabe, Noriko, Saito, Masaki, Sarai, Masayoshi, Sato, Junichi, Sato, Daisuke, Shiraishi, Shinya, Takanami, Kentaro, Takehana, Kazuya, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Dautov, Tairkhan, Makhdomi, Khalid, Abass, Mostafa, Garashi, Masoud, Siraj, Qaisar, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Vajauskas, Donatas, Karim, Noor Khairiah A., Doucoure, Mady, Reichmuth, Luise, Samuel, Anthony, Dieng, Mohamed Lemine, Naojee, Ambedhkar Shantaram, Hernandez, Estrella Aguilera, Alducin Tellez, Cesar Rene, Alexánderson-Rosas, Erick, Barragan, Erika, Cabada, Manuel, Calderón, Daniel, Carvajal-Juarez, Isabel, Esparza, José, Gama-Moreno, Manlio Gerardo, Quinto, Virginia Garcia, Gonzalez, Nelsy Coromoto, Herrera-Zarza, Mary Carmen, Meave, Aloha, Medina Verdugo, Jesus Gregorio, Melendez, Gabriela, Morales Murguia, Rafael Humberto, Navarro Quiroz, Carlos Salvador, Ornelas, Mario, Preciado-Anaya, Andres, Preciado-Gutiérrez, Oscar Ulises, Puente, Adriana, Salazar, Aristóteles Ramírez, Rosales Uvera, Sandra Graciela, Rosales-Uvera, Sandra, Serna Macias, Jose Antonio, Sierra-Galan, Lilia, Sierra-Galan, Lilia M., Tirado Alderete, Juan Carlos, Vallejo, Enrique, Faraggi, Marc, Sereegotov, Erdenechimeg, Ben Rais, Nouzha, Alaoui, Nadia Ismaili, Kyiphyu, Thiri, Oo, Su Thet, Win, Soe Myat, Zar, Htin, Ghimire, Ram, Neupane, Madhu, Glaudemans, Andor, Slart, Riemer, Verschure, Derk, Allen, Berry, Edmond, John, Mckenzie, Clare, Tie, Stuart, Van Pelt, Niels, Worthington, Kirsten, Young, Calum, Soli, Idrissa Adamou, Kana, Shehu, Onubogu, Uchenna, Sani, Mahmoud, Bråten, Anders Tjellaug, Jørgensen, Arve, Vassbotn, Hanne-Elin, Al Dhuhli, Humoud, Jawa, Zabah, Tag, Naima, Fatima, Shazia, Imran, Muhammad Babar, Younis, Muhammad Numair, Saadullah, Mohammad, Malo, Yariela Herrera, Lenturut-Katal, Dora, Castillo, Manuel, Ortellado, José, Akhter, Afroza, Cader, F. Aaysha, Hussain, Raihan, Khan, Saidur Rahman, Mandal, Tapati, Nasreen, Faria, An, Yunqiang, Cao, Dianbo, Gong, Lianggeng, Hou, Yang, Jia, Chongfu, Li, Tao, Li, Caiying, Liu, Hui, Liu, Wenya, Liu, Jinkang, Lu, Bin, Ng, Ming-Yen, Shi, Heshui, Tang, Chunxiang, Wang, Ximing, Wang, Zhaoqian, Wang, Yining, Wu, Jiang, Yi, Yan, Yuan, Li, Zhang, Tong, Zhang, Longjiang, Chavez, Edith, Cruz, Carlos, Llontop, Christian, Morales, Rosanna, Abrihan, Paz, Bustos-Barroso, Asela, Duldulao-Ogbac, Michele, Eduarte, Christopher, Obaldo, Jerry, Quinon, Alvin, San Juan, Belinda, San Juan, Carlo Joe, Sauler-Gomez, Marie Rhiamar, Uy, Mila, Kostkiewicz, Magdalena, Kunikowska, Jolanta, Teresinska, Anna, Urbanik, Tomasz, Bettencourt, Nuno, Fontes-Carvalho, Ricardo, Gavina, Cristina, Gonçalves, Lino, Macedo, Filipe, Moreno, Nuno, Sousa, Carla, Timoteo, Ana Teresa, Vidigal, Maria João, Al Heidous, Mahmoud, Ramanathan, Subramaniyan, Arnous, Samer, Aytani, Said, Byrne, Angela, Gleeson, Tadhg, Kerins, David, O'Brien, Julie, Bang, Ji-In, Bom, Henry, Cheon, Miju, Cheon, Gi Jeong, Cho, Sang-Geon, Hong, Chae Moon, Jeong, Yong Hyu, Kang, Won Jun, Kang, Yeon-Koo, Kim, Ji-Young, Oh, So Won, So, Young, Song, Ho-Chun, Won, Kyoung Sook, Yoo, Soo Woong, Mitevska, Irena, Vavlukis, Marija, Salobir, Barbara Gužic, Štalc, Monika, Benedek, Theodora, Pop, Marian, Stan, Claudiu, Ansheles, Alexey, Dariy, Olga, Gagarina, Nina, Itskovich, Irina, Karalkin, Anatoliy, Kokov, Alexander, Marina, Gulya, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Sayfullina, Guzaliya, Sergienko, Vladimir, Shurupova, Irina, Sinitsyn, Valentin, Vakhromeeva, Margarita, Valiullina, Nailia, Zavadovsky, Konstantin, Zhuravlev, Kirill, Abazid, Rami, Al Garni, Turki, Alasnag, Mirvat, Aljizeeri, Ahmed, Amer, Hamid, Amro, Ahmad, Hamdy, Hesham, Smettei, Osama, Saranovic, Dragana Sobic, Vlajkovic, Marina, Keng, Felix, See, Jason, Berecova, Zuzana, Mistinova, Jana Polakova, Evbuomwan, Osayande, Govender, Nerisha, Hack, Jonathan, Hadebe, Bawinile, Hlongwa, Khanyisile, Kaplan, Mitchell, Lakhi, Hoosen, Milos, Katarina, Modiselle, Moshe, More, Stuart, Muambadzi, Ntanganedzeni, Scholtz, Leonie, Barreiro-Perez, Manuel, Blanco, Isabel, Broncano, Jordi, Camarero, Alicia, Casáns-Tormo, Irene, De Haro, Javier, Flotats, Albert, García, Elia, Mendiguchia, Ceferino Gutierrez, Jimenez-Heffernan, Amelia, Leta, Ruben, Diaz, Javier Lopez, Vega, Luis Lumbreras, Manovel-Sánchez, Ana, Monzonis, Amparo Martinez, Patrut, Bianca, Pubul, Virginia, Perez, Ricardo Ruano, Zeidan, Nahla, Nanayakkara, Damayanthi, Suliman, Ahmed, Engblom, Henrik, Murtadha, Mustafa, Ostenfeld, Ellen, Simonsson, Magnus, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Gräni, Christoph, Kamani, Christel, Kawel-Böhm, Nadine, Klaeser, Bernd, Manka, Robert, Prior, John, Kaewchur, Tawika, Khiewvan, Benjapa, Kositwattanarerk, Arpakorn, Namwongprom, Sirianong, Thientunyakit, Tanyaluck, Sayman, Haluk Burcak, Yüksel, Mahmut, Sebikali, Mugisha Julius, Okello, Emmy, Korol, Pavlo, Noverko, Iryna, Satyr, Maryna, Ahmad, Tahir, Alfakih, Khaled, Andrade, Ivo, Buckingham, Susan, Bularga, Anda, Carpenter, John-Paul, Cole, Graham, Cusack, David, David, Sarojini, Davis, Patrick, Fairbairn, Timothy, Ghosh, Arjun, Ramkumar, Prasad Guntur, Hamilton, Mark, Haque, Faisal, Hudson, Benjamin, Johnstone, Annette, Karthikeyan, V.J., Kay, Mike, Khan, Mohammad Ali, Kitt, Jamie, Low, Chen Sheng, Mcalindon, Elisa, Mccreavy, David, Morrissey, Brian, Motwani, Manish, Na, Dilip, Nicol, Edward, Patel, Dilip, Rodrigues, Jonathan, Rofe, Chris, Schofield, Rebecca, Semple, Thomas, Sheikh, Azeem, Sinha, Apurva, Subedi, Deepak, Topping, William, Tweed, Katherine, Underwood, Stephen Richard, Weir-Mccall, Jonathan, Zuhairy, Hamed, Abbasi, Taimur, Abohashem, Shady, Abramson, Sandra, Al-Mallah, Mouaz, Kumar, Mohan Ashok, Balmer-Swain, Mallory, Berman, Daniel, Bernheim, Adam, Bhatti, Sabha, Biederman, Robert, Bieging, Erik, Bingham, Scott, Bloom, Stephen, Blue, Sean, Borges, Andressa, Branch, Kelley, Bravo, Paco, Buddhe, Sujatha, Budoff, Matthew, Bullock-Palmer, Renée, Cahill, Michael, Candela, Candace, Cao, Jane, Chatterjee, Saurav, Chatzizisis, Yiannis, Chaudhuri, Nita Ray, Cheezum, Michael, Chelliah, Anjali, Chen, Tiffany, Chen, Marcus, Chen, Lu, Chokshi, Aalap, Chung, Jina, Danciu, Sorin, DeSisto, William, Dilorenzo, Michael, Doukky, Rami, Duvall, William, Ferencik, Maros, Foster, Cameron, Fuisz, Anthon, Gannon, Michael, German, David, Gerson, Myron, Geske, Jeffrey, Hage, Fadi, Haider, Agha, Haider, Sofia, Hamirani, Yasmin, Hassen, Karen, Hendel, Robert, Henkel, Jacqueline, Horgan, Stephen, Hyun, Mark, Janardhanan, Rajesh, Jerome, Scott, Kalra, Dinesh, Kassop, David, Kinkhabwala, Mona, Kinzfogl, George, Koch, Bernard, Koweek, Lynne, Krepp, Joseph, Kwon, Younghoon, Layer, Jay, Lesser, John, Leung, Steve, Lisske, Bernadette, Magurany, Kathleen, Markowitz, Jeremy, Mccullough, Brenda, Moalemi, Azita, Moffitt, Chanan, Montanez, Juan, Moore, Warren, Morayati, Shamil, Mossa-Basha, Mahmud, Mrsic, Zorana, Murthy, Venkatesh, Nagpal, Prashant, Nelson, Katarina, Nijjar, Prabhjot, O’Quinn, Rupal, Passen, Edward, Patel, Toral, Patil, Pravin, Pursnani, Amit, Quachang, Nancy, Rabbat, Mark, Ranjan, Pragya, Lozano, Patricia Rodriguez, Schemmer, Mary, Seifried, Rebecca, Shah, Nishant, Shah, Amee, Shanbhag, Sujata, Sharma, Gaurav, Skotnicki, Robert, Sobczak, Michael, Soman, Prem, Sorrell, Vincent, Srichai, Monvadi, Streeter, Jim, Strickland, Leah, Suliman, Suliman, Tebyanian, Naghmeh, Thomas, Dustin, Thompson, Randall, Uretsky, Seth, Vallurupalli, Srikanth, Vandyck-Acquah, Marian, Verma, Vikas, Villines, Todd, Weinstein, Joseph, Wolinsky, David, Zareba, Karolina, Zgaljardic, Michael, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Vera, Luisa, Duc, Binh Duong, Nguyen, Xuan Canh, Hiep Nguyen, Phuoc Minh, Hirschfeld, Cole, Choi, Andrew D., Ansheles, Alexey A., Kudo, Takashi, Bucciarelli-Ducci, Chiara, Nørgaard, Bjarne Linde, Maurovich-Horvat, Pál, Louw, Lizette, Allam, Adel H., and Narula, Jagat

Published
2022
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7. Quantitative evaluation of 67Ga-citrate scintigraphy in the management of nephritis.

Author

Matsuda, Noritake, Otsuka, Hideki, Kasai, Ryosuke, Otani, Tamaki, Bollos, Leah Anne Christine Locsin, Azane, Shota, Kunikane, Yamato, Otomi, Yoichi, Ueki, Yuya, Okabe, Mana, Amano, Masafumi, Tamaki, Masanori, Wakino, Shu, Takao, Shoichiro, and Harada, Masafumi

Abstract

In 67Ga-citrate scintigraphy (Ga-S), visual assessment is used by evaluating renal-uptake comparison with liver and spine and is simple and objective. We adopted the standardized uptake value (SUV) for 67Ga-citrate and proposed two quantitative indices, active nephritis volume (ANV) and total nephritis uptake (TNU). This study clarified the utility of new Ga-S-based quantitative indices in nephritis management. Before SUV measurement, the Becquerel calibration factor of 67Ga-citrate was obtained using a phantom experiment. Seventy patients who underwent SPECT/CT imaging were studied. SUV, ANV, and TNU were calculated using a quantitative analysis software for bone SPECT. SUVmean, ANV, and TNU were analyzed using the (1) threshold method (set 40%) and constant-value method for (2) vertebral SUVmax, and (3) vertebral SUVmean. ROC analysis was used to evaluate SUV, ANV, and TNU diagnostic abilities to distinguish nephritis presence and absence as well as interstitial nephritis (IN) and non-IN. The area under the curve (AUC) for nephritis presence or absence had a good value (0.80) for SUVmean (1), ANV (3), and TNU (3). The AUC for differentiation between IN and non-IN groups had a good value (0.80) for SUVmean (1). Thus, the new Ga-S-based quantitative indices were useful to evaluate nephritis and distinguish IN and non-IN. [ABSTRACT FROM AUTHOR]

Published
2024
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15. New quantitative indices of cardiac amyloidosis with 99mTc-pyrophosphate scintigraphy

Author

Matsuda, Noritake, Otsuka, Hideki, Otani, Tamaki, Azane, Shota, Kunikane, Yamato, Otomi, Yoichi, Ueki, Yuya, Kubota, Masahiro, Amano, Masafumi, Yagi, Shusuke, Sata, Masataka, Harada, Masafumi, Matsuda, Noritake, Otsuka, Hideki, Otani, Tamaki, Azane, Shota, Kunikane, Yamato, Otomi, Yoichi, Ueki, Yuya, Kubota, Masahiro, Amano, Masafumi, Yagi, Shusuke, Sata, Masataka, and Harada, Masafumi

Abstract

Purpose: Amyloid light chain (AL) and transthyretin (ATTR) are the major subtypes of cardiac amyloidosis (CA). 99mTc-pyrophosphate (PYP) scintigraphy is used to differentiate ATTR from other CA subtypes. We adapted the standardized uptake value (SUV) for 99mTc-PYP and proposed two quantitative indices, amyloid deposition volume (AmyDV) and total amyloid uptake (TAU). This study aimed to evaluate the utility of these quantitative indices in differentiating ATTR from non-ATTRs. Materials and methods: Before the SUV measurement, the Becquerel calibration factor (BCF) of 99mTc was obtained by a phantom experiment. Thirty-two patients who had undergone hybrid SPECT/CT imaging 3 h after injection of 99mTc-PYP (370 MBq) were studied. CT attenuation correction for image reconstruction was applied in all. We calculated SUV, AmyDV, and TAU using a quantitative analysis software program for bone SPECT (GI-BONE) and analyzed AmyDV using two methods: Threshold method (set 40%); and constant value method (average SUVmax of ribs). We assessed the diagnostic ability of heart-to-contralateral lung (H/CL) ratio, SUV, AmyDV, and TAU to differentiate ATTR from non-ATTR using receiver operating characteristic (ROC) analysis. Results: Statistically significant differences in all quantitative indices were observed between ATTR and non-ATTR. The area under the curve of each quantitative index for discriminating between ATTR and non-ATTR were as follows: H/CL, 0.997; SUVmax, 0.953; SUVmean (M1), 0.964; SUVmean (M2), 0.969; AmyDV (M1), 0.875; AmyDV (M2), 0.974; and TAU, 0.974. The AmyDV (M2) had higher diagnostic ability than AmyDV (M1). Thus, TAU was calculated as AmyDV (M2) × SUVmean (M2). In the ROC curve, SUV, AmyDV, and TAU had almost the same diagnostic ability as H/CL in distinguishing ATTR from non-ATTRs. Conclusions: We propose two novel 3D-based quantitative parameters (AmyDV and TAU) that have almost equal ability to discriminate ATTR from non-ATTR.

Published
2022

16. Imaging features of a myoepithelial carcinoma of the nasal cavity : A case report and literature review

Author

Shinya, Takayoshi, Matsushita, Tomoki, Hiroshima, Yuka, Otomi, Yoichi, Kanematsu, Yasuhisa, Bando, Yoshimi, Uehara, Hisanori, Kitamura, Yoshiaki, Harada, Masafumi, Shinya, Takayoshi, Matsushita, Tomoki, Hiroshima, Yuka, Otomi, Yoichi, Kanematsu, Yasuhisa, Bando, Yoshimi, Uehara, Hisanori, Kitamura, Yoshiaki, and Harada, Masafumi

Abstract

Myoepithelial carcinoma of the nasal cavity is extremely rare. We report the case of a 66-year-old man with myoepithelial carcinoma of the nasal cavity. Computed tomography (CT) and magnetic resonance imaging revealed a lobulated soft tissue mass with central necrosis and hemorrhage, as well as an invasion of the skull base and left orbit. The patient presented with continuous nasal congestion and heavy head and had no elevated level of squamous cell carcinoma-related antigen. CT, magnetic resonance imaging, or 18F-fluorodeoxyglucose (FDG) positron emission tomography/CT revealed no evidence of a metastatic lesion. 18F-FDG accumulation in the tumor was inhomogeneous and moderate. Histopathological examination of the resected specimen confirmed a well-circumscribed solid tumor with septa, a small area of hemorrhage, and necrosis. The subsequent diagnosis was a myoepithelial carcinoma of the left nasal cavity. This case shows that nasal myoepithelial carcinoma might appear as a well-defined lobulated mass with hemorrhagic necrosis and intense contrast enhancement in the solid component. We conjecture that hemorrhagic necrosis and intense enhancement values may be potential markers of nasal myoepithelial carcinoma.

Published
2022

17. New quantitative indices of cardiac amyloidosis with 99mTc-pyrophosphate scintigraphy.

Author

Matsuda, Noritake, Otsuka, Hideki, Otani, Tamaki, Azane, Shota, Kunikane, Yamato, Otomi, Yoichi, Ueki, Yuya, Kubota, Masahiro, Amano, Masafumi, Yagi, Shusuke, Sata, Masataka, and Harada, Masafumi

Abstract

Purpose: Amyloid light chain (AL) and transthyretin (ATTR) are the major subtypes of cardiac amyloidosis (CA). 99mTc-pyrophosphate (PYP) scintigraphy is used to differentiate ATTR from other CA subtypes. We adapted the standardized uptake value (SUV) for 99mTc-PYP and proposed two quantitative indices, amyloid deposition volume (AmyDV) and total amyloid uptake (TAU). This study aimed to evaluate the utility of these quantitative indices in differentiating ATTR from non-ATTRs. Materials and methods: Before the SUV measurement, the Becquerel calibration factor (BCF) of 99mTc was obtained by a phantom experiment. Thirty-two patients who had undergone hybrid SPECT/CT imaging 3 h after injection of 99mTc-PYP (370 MBq) were studied. CT attenuation correction for image reconstruction was applied in all. We calculated SUV, AmyDV, and TAU using a quantitative analysis software program for bone SPECT (GI-BONE) and analyzed AmyDV using two methods: threshold method (set 40%); and constant value method (average SUVmax of ribs). We assessed the diagnostic ability of heart-to-contralateral lung (H/CL) ratio, SUV, AmyDV, and TAU to differentiate ATTR from non-ATTR using receiver operating characteristic (ROC) analysis. Results: Statistically significant differences in all quantitative indices were observed between ATTR and non-ATTR. The area under the curve of each quantitative index for discriminating between ATTR and non-ATTR were as follows: H/CL, 0.997; SUVmax, 0.953; SUVmean (M1), 0.964; SUVmean (M2), 0.969; AmyDV (M1), 0.875; AmyDV (M2), 0.974; and TAU, 0.974. The AmyDV (M2) had higher diagnostic ability than AmyDV (M1). Thus, TAU was calculated as AmyDV (M2) × SUVmean (M2). In the ROC curve, SUV, AmyDV, and TAU had almost the same diagnostic ability as H/CL in distinguishing ATTR from non-ATTRs. Conclusions: We propose two novel 3D-based quantitative parameters (AmyDV and TAU) that have almost equal ability to discriminate ATTR from non-ATTR. [ABSTRACT FROM AUTHOR]

Published
2023
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18. Axillary Lymph Node Uptake on 18F-FDG PET/CT after COVID-19 Vaccination: A Direct Comparison Study with Influenza Vaccination.

Author

Otomi, Yoichi, Shinya, Takayoshi, Kasai, Hiroto, Okada, Naoko, Matsushita, Tomoki, Higashi, Kohei, Matsuzaki, Saya, Hiroshima, Yuka, Kubo, Michiko, Otsuka, Hideki, and Harada, Masafumi

Subjects
*COVID-19 vaccines, *INFLUENZA vaccines, *LYMPH nodes, *POSITRON emission tomography, *COVID-19
Abstract

Objectives: To compare vaccinated-side axillary lymph node uptake on 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) after coronavirus disease-2019 (COVID-19) and influenza vaccination. Methods: We retrospectively analyzed 177 patients who underwent 18F-FDG PET/CT after COVID-19 or influenza vaccination. We compared the uptake of the vaccinated-side axillary lymph nodes of 109 COVID-19 vaccinated patients with those of a lot of influenza-vaccinated patients. We also compared the uptake between 66 patients who received the first COVID-19 vaccination with 43 who received the second COVID-19 vaccination. Results: 18F-FDG-avid axillary lymph nodes on the vaccinated side were significantly more frequently observed in the COVID-19 group (45%) than in the influenza group (19%) (p<0.001). When the interval between vaccination to PET/CT was within 7 days, there was no significant difference in the frequency of 18F-FDG-avid vaccinated-side axillary lymph nodes between the groups (COVID-19 group: 41% vs. influenza group: 45%, p=0.724). When the interval was over 7 days, 18F-FDG-avid lymph nodes were much more frequent in the COVID-19 group (47%) than in the influenza group (7%) (p<0.001). Comparing the first and second COVID-19 groups, 18F-FDG-avid lymph nodes were more frequent in the second vaccination group than in the first vaccination group, but the difference was not significant. Conclusion: 18F-FDG-avid vaccinated-side axillary lymph nodes were more frequently observed in the COVID-19 group than in the influenza group. In the case of the COVID-19 vaccine, a delay of 18F-FDG PET/CT examination is recommended by a longer interval from vaccination than in the influenza vaccine. [ABSTRACT FROM AUTHOR]

Published
2023
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19. 11C-Methionine PET/CT and 18F-FDG PET/CT in the Evaluation of Adult Alveolar Rhabdomyosarcoma.

Author

Hiroshima, Yuka, Otomi, Yoichi, Shinya, Takayoshi, Otsuka, Hideki, and Harada, Masafumi

Subjects
*METHIONINE, *MAGNETIC resonance imaging, *RHABDOMYOSARCOMA, *NASAL tumors, *LYMPHATIC metastasis, *PARANASAL sinuses, *POSITRON emission tomography
Abstract

A 70-year-old man with a tumor in the nasal and paranasal space, was pathologically diagnosed with an alveolar rhabdomyosarcoma, with right cervical lymph node metastasis. Magnetic resonance imaging revealed a primary tumor in the nasal and paranasal sinuses, with associated intracranial infiltration. 11C-methionine positron emission tomography/computed tomography (PET/CT) revealed increased uptake in the primary tumor and right cervical lymph node metastasis. 18F-fluorodeoxyglucose PET/CT also revealed increased uptake in the primary tumor and right cervical lymph node. However, the physiological brain uptake overlapped with the primary tumor uptake. Our case suggests the usefulness of 11C-methionine PET/CT for accurately assessing the extent of alveolar rhabdomyosarcoma, especially in cases with intracranial infiltration or those approximating the brain. [ABSTRACT FROM AUTHOR]

Published
2023
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21. 177 Lu-DOTATATE Uptake in the Lungs of a Patient With COVID-19 Pneumonia.

Author

Matsushita T, Otomi Y, Okada N, Kawanaka T, and Otsuka H

Subjects
Humans, Aged, Female, Pandemics, Single Photon Emission Computed Tomography Computed Tomography, Coronavirus Infections diagnostic imaging, Coronavirus Infections complications, Neuroendocrine Tumors diagnostic imaging, Neuroendocrine Tumors radiotherapy, COVID-19 diagnostic imaging, COVID-19 complications, Organometallic Compounds, Lung diagnostic imaging, Octreotide analogs & derivatives, Octreotide therapeutic use, Pneumonia, Viral diagnostic imaging, Pneumonia, Viral complications
Abstract

Abstract: A 76-year-old woman with liver and bone metastasis of a duodenal neuroendocrine tumor received peptide receptor radionuclide therapy with 177 Lu-DOTATATE. Scintigraphy with SPECT/CT performed 4 days after the treatment demonstrated 177 Lu-DOTATATE uptake as multifocal ground glass opacities in the bilateral lungs. This uptake was considered to be due to COVID-19 pneumonia because the patient was infected with the virus 7 days prior to the treatment. The lung opacities became smaller, showing a decreased uptake, 2 months later, after the second treatment. 177 Lu-DOTATATE may be taken up during the active phase of COVID-19 pneumonia., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Published
2024
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22. Quantitative evaluation of 67 Ga-citrate scintigraphy in the management of nephritis.

Author

Matsuda N, Otsuka H, Kasai R, Otani T, Bollos LACL, Azane S, Kunikane Y, Otomi Y, Ueki Y, Okabe M, Amano M, Tamaki M, Wakino S, Takao S, and Harada M

Subjects
Humans, Male, Female, Middle Aged, Aged, Adult, Nephritis diagnostic imaging, Citrates, ROC Curve, Aged, 80 and over, Radiopharmaceuticals, Single Photon Emission Computed Tomography Computed Tomography methods, Gallium Radioisotopes, Gallium
Abstract

In 67 Ga-citrate scintigraphy (Ga-S), visual assessment is used by evaluating renal-uptake comparison with liver and spine and is simple and objective. We adopted the standardized uptake value (SUV) for 67 Ga-citrate and proposed two quantitative indices, active nephritis volume (ANV) and total nephritis uptake (TNU). This study clarified the utility of new Ga-S-based quantitative indices in nephritis management. Before SUV measurement, the Becquerel calibration factor of 67 Ga-citrate was obtained using a phantom experiment. Seventy patients who underwent SPECT/CT imaging were studied. SUV, ANV, and TNU were calculated using a quantitative analysis software for bone SPECT. SUV mean , ANV, and TNU were analyzed using the (1) threshold method (set 40%) and constant-value method for (2) vertebral SUV max , and (3) vertebral SUV mean . ROC analysis was used to evaluate SUV, ANV, and TNU diagnostic abilities to distinguish nephritis presence and absence as well as interstitial nephritis (IN) and non-IN. The area under the curve (AUC) for nephritis presence or absence had a good value (0.80) for SUV mean (1), ANV (3), and TNU (3). The AUC for differentiation between IN and non-IN groups had a good value (0.80) for SUV mean (1). Thus, the new Ga-S-based quantitative indices were useful to evaluate nephritis and distinguish IN and non-IN., (© 2024. The Author(s).)

Published
2024
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23. 11 C-Methionine PET/CT and 18 F-FDG PET/CT in the Evaluation of Adult Alveolar Rhabdomyosarcoma.

Author

Hiroshima Y, Otomi Y, Shinya T, Otsuka H, and Harada M

Abstract

A 70-year-old man with a tumor in the nasal and paranasal space, was pathologically diagnosed with an alveolar rhabdomyosarcoma, with right cervical lymph node metastasis. Magnetic resonance imaging revealed a primary tumor in the nasal and paranasal sinuses, with associated intracranial infiltration. 11 C-methionine positron emission tomography/computed tomography (PET/CT) revealed increased uptake in the primary tumor and right cervical lymph node metastasis. 18 F-fluorodeoxyglucose PET/CT also revealed increased uptake in the primary tumor and right cervical lymph node. However, the physiological brain uptake overlapped with the primary tumor uptake. Our case suggests the usefulness of 11 C-methionine PET/CT for accurately assessing the extent of alveolar rhabdomyosarcoma, especially in cases with intracranial infiltration or those approximating the brain., Competing Interests: Conflict of Interest: No conflict of interest was declared by the authors., (©Copyright 2023 by Turkish Society of Nuclear Medicine Molecular Imaging and Radionuclide Therapy published by Galenos Yayınevi.)

Published
2023
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24. Axillary Lymph Node Uptake on 18 F-FDG PET/CT after COVID-19 Vaccination: A Direct Comparison Study with Influenza Vaccination.

Author

Otomi Y, Shinya T, Kasai H, Okada N, Matsushita T, Higashi K, Matsuzaki S, Hiroshima Y, Kubo M, Otsuka H, and Harada M

Abstract

Objectives: To compare vaccinated-side axillary lymph node uptake on 18 F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) after coronavirus disease-2019 (COVID-19) and influenza vaccination., Methods: We retrospectively analyzed 177 patients who underwent 18 F-FDG PET/CT after COVID-19 or influenza vaccination. We compared the uptake of the vaccinated-side axillary lymph nodes of 109 COVID-19 vaccinated patients with those of a lot of influenza-vaccinated patients. We also compared the uptake between 66 patients who received the first COVID-19 vaccination with 43 who received the second COVID-19 vaccination., Results: 18 F-FDG-avid axillary lymph nodes on the vaccinated side were significantly more frequently observed in the COVID-19 group (45%) than in the influenza group (19%) (p<0.001). When the interval between vaccination to PET/CT was within 7 days, there was no significant difference in the frequency of 18 F-FDG-avid vaccinated-side axillary lymph nodes between the groups (COVID-19 group: 41% vs. influenza group: 45%, p=0.724). When the interval was over 7 days, 18 F-FDG-avid lymph nodes were much more frequent in the COVID-19 group (47%) than in the influenza group (7%) (p<0.001). Comparing the first and second COVID-19 groups, 18 F-FDG-avid lymph nodes were more frequent in the second vaccination group than in the first vaccination group, but the difference was not significant., Conclusion: 18 F-FDG-avid vaccinated-side axillary lymph nodes were more frequently observed in the COVID-19 group than in the influenza group. In the case of the COVID-19 vaccine, a delay of 18 F-FDG PET/CT examination is recommended by a longer interval from vaccination than in the influenza vaccine., Competing Interests: Conflict of Interest: No conflicts of interest was declared by the authors., (©Copyright 2023 by Turkish Society of Nuclear Medicine Molecular Imaging and Radionuclide Therapy published by Galenos Yayınevi.)

Published
2023
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25. Imaging features of a myoepithelial carcinoma of the nasal cavity: A case report and literature review.

Author

Shinya T, Matsushita T, Hiroshima Y, Otomi Y, Kanematsu Y, Bando Y, Uehara H, Kitamura Y, and Harada M

Abstract

Myoepithelial carcinoma of the nasal cavity is extremely rare. We report the case of a 66-year-old man with myoepithelial carcinoma of the nasal cavity. Computed tomography (CT) and magnetic resonance imaging revealed a lobulated soft tissue mass with central necrosis and hemorrhage, as well as an invasion of the skull base and left orbit. The patient presented with continuous nasal congestion and heavy head and had no elevated level of squamous cell carcinoma-related antigen. CT, magnetic resonance imaging, or 18 F-fluorodeoxyglucose (FDG) positron emission tomography/CT revealed no evidence of a metastatic lesion. 18 F-FDG accumulation in the tumor was inhomogeneous and moderate. Histopathological examination of the resected specimen confirmed a well-circumscribed solid tumor with septa, a small area of hemorrhage, and necrosis. The subsequent diagnosis was a myoepithelial carcinoma of the left nasal cavity. This case shows that nasal myoepithelial carcinoma might appear as a well-defined lobulated mass with hemorrhagic necrosis and intense contrast enhancement in the solid component. We conjecture that hemorrhagic necrosis and intense enhancement values may be potential markers of nasal myoepithelial carcinoma., (© 2022 Published by Elsevier Inc. on behalf of University of Washington.)

Published
2022
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26. 18 F-FDG PET/CT Showing Rare Mediastinal Growing Teratoma Syndrome Following Chemotherapy.

Author

Sasahara M, Abe T, Otomi Y, Abe Y, Toba H, Shinya T, Otsuka H, and Harada M

Abstract

Growing teratoma syndrome (GTS) is a condition in which poorly differentiated cells in a mixed-germ cell tumor (GCT) regress after chemotherapy, and the number of well-differentiated components increases. A 60-year-old man had an 8.0 cm mediastinal tumor with strong 18 F-fluorodeoxyglucose (FDG) uptake [maximum standardized uptake value (SUV max ): 9.2], which was diagnosed as a GCT. After chemotherapy, serum alpha fetoprotein, beta-human chorionic gonadotropin, and tumor 18 F-FDG uptake decreased (SUV max : 3.9), but the tumor volume increased. The tumor was completely resected, and pathology confirmed the diagnosis of GTS. 18 F-FDG positron emission tomography after chemotherapy reflects the proliferation of highly differentiated tumor components with poor 18 F-FDG uptake., Competing Interests: Conflict of Interest: No conflict of interest is declared by the authors., (©Copyright 2022 by Turkish Society of Nuclear Medicine | Molecular Imaging and Radionuclide Therapy published by Galenos Yayınevi.)

Published
2022
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27. Increased 18 F-FDG Uptake in the Axillary Lymph Nodes of the Vaccinated Side Associated with COVID-19 Vaccination.

Author

Otomi Y, Irahara S, Inoue H, Shinya T, Otsuka H, and Harada M

Abstract

A 50-year-old female patient underwent ( 18 fluorine-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography/computed tomography (PET/CT) following modified radical mastectomy for cancer of the left breast. Ten days before the PET/CT, the coronavirus disease-2019 (COVID-19) vaccine was injected intramuscularly into the right deltoid muscle. Increased ( 18 F-FDG uptake of maximum standardized uptake value (11.0) was observed in the lymph nodes of the right axilla, which had not been observed in the previous PET/CT. The size of the oval-shaped lymph nodes was up to approximately 11×9 mm; however, it was larger than that observed on the previous PET/CT. We contemplate that the increased ( 18 F-FDG uptake was a reactive change in the lymph nodes associated with the COVID-19 vaccine., Competing Interests: Conflict of Interest: No conflict of interest was declared by the authors., (©Copyright 2022 by Turkish Society of Nuclear Medicine, Molecular Imaging and Radionuclide Therapy published by Galenos Yayınevi.)

Published
2022
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