Clinical Validation of a Machine-Learned, Point-of-Care System to IDENTIFY Functionally Significant Coronary Artery Disease

Autor: Thomas D. Stuckey, Frederick J. Meine, Thomas R. McMinn, Jeremiah P. Depta, Brett A. Bennett, Thomas F. McGarry, William S. Carroll, David D. Suh, John A. Steuter, Michael C. Roberts, Horace R. Gillins, Farhad Fathieh, Timothy Burton, Navid Nemati, Ian P. Shadforth, Shyam Ramchandani, Charles R. Bridges, Mark G. Rabbat

Publikováno v: Diagnostics, Vol 14, Iss 10, p 987 (2024)

Many clinical studies have shown wide performance variation in tests to identify coronary artery disease (CAD). Coronary computed tomography angiography (CCTA) has been identified as an effective rule-out test but is not widely available in the USA,

Externí odkaz: https://doaj.org/article/1ace3123fc004960b45d1800947607d9

Development and validation of a machine learned algorithm to IDENTIFY functionally significant coronary artery disease

Autor: Thomas Stuckey, Frederick Meine, Thomas McMinn, Jeremiah P. Depta, Brett Bennett, Thomas McGarry, William Carroll, David Suh, John A. Steuter, Michael Roberts, Horace R. Gillins, Emmanuel Lange, Farhad Fathieh, Timothy Burton, Ali Khosousi, Ian Shadforth, William E. Sanders, Mark G. Rabbat

Publikováno v: Frontiers in Cardiovascular Medicine, Vol 9 (2022)

IntroductionMultiple trials have demonstrated broad performance ranges for tests attempting to detect coronary artery disease. The most common test, SPECT, requires capital-intensive equipment, the use of radionuclides, induction of stress, and time

Externí odkaz: https://doaj.org/article/7fd11bfb73a846698b6ad1a05a2b3ec4

Coronary Volume to Left Ventricular Mass Ratio in Patients With Hypertension

Autor: Sophie E. van Rosendael, Alexander R. van Rosendael, Jurrien H. Kuneman, Manesh R. Patel, Bjarne Linde Nørgaard, Timothy A. Fairbairn, Koen Nieman, Takashi Akasaka, Daniel S. Berman, Lynne M. Hurwitz Koweek, Gianluca Pontone, Tomohiro Kawasaki, Niels Peter Rønnow Sand, Jesper M. Jensen, Tetsuya Amano, Michael Poon, Kristian A. Øvrehus, Jeroen Sonck, Mark G. Rabbat, Campbell Rogers, Hitoshi Matsuo, Jonathon A. Leipsic, Nina Ajmone Marsan, J. Wouter Jukema, Jeroen J. Bax, Antti Saraste, Juhani Knuuti

Publikováno v: van Rosendael, S E, van Rosendael, A R, Kuneman, J H, Patel, M R, Nørgaard, B L, Fairbairn, T A, Nieman, K, Akasaka, T, Berman, D S, Koweek, L M H, Pontone, G, Kawasaki, T, Sand, N P R, Jensen, J M, Amano, T, Poon, M, Øvrehus, K A, Sonck, J, Rabbat, M G, Rogers, C, Matsuo, H, Leipsic, J A, Marsan, N A, Jukema, J W, Bax, J J, Saraste, A & Knuuti, J 2023, ' Coronary Volume to Left Ventricular Mass Ratio in Patients With Hypertension ', The American Journal of Cardiology, vol. 199, pp. 100-109 . https://doi.org/10.1016/j.amjcard.2023.04.025

The coronary vascular volume to left ventricular mass (V/M) ratio assessed by coronary computed tomography angiography (CCTA) is a promising new parameter to investigate the relation of coronary vasculature to the myocardium supplied. It is hypothesi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a741dad7bb72452ac03ecd5cde53543b
https://pure.au.dk/portal/da/publications/coronary-volume-to-left-ventricular-mass-ratio-in-patients-with-hypertension(26e75f0b-8baa-4fea-a1f4-3c4a436d3d5d).html

AI Cardiac MRI Scar Analysis Aids Prediction of Major Arrhythmic Events in the Multicenter DERIVATE Registry

Autor: Fahime Ghanbari, Thomas Joyce, Valentina Lorenzoni, Andrea I. Guaricci, Anna-Giulia Pavon, Laura Fusini, Daniele Andreini, Mark G. Rabbat, Giovanni Donato Aquaro, Raffaele Abete, Jan Bogaert, Giovanni Camastra, Samuela Carigi, Nazario Carrabba, Grazia Casavecchia, Stefano Censi, Gloria Cicala, Carlo N. De Cecco, Manuel De Lazzari, Gabriella Di Giovine, Mauro Di Roma, Marta Focardi, Nicola Gaibazzi, Annalaura Gismondi, Matteo Gravina, Chiara Lanzillo, Massimo Lombardi, Jordi Lozano-Torres, Ambra Masi, Claudio Moro, Giuseppe Muscogiuri, Alberto Nese, Silvia Pradella, Stefano Sbarbati, U. Joseph Schoepf, Adele Valentini, Gérard Crelier, Pier Giorgio Masci, Gianluca Pontone, Sebastian Kozerke, Juerg Schwitter

Publikováno v: Scientia

Background Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b879ef00d15d4be081a87357e2b8fd8
https://lirias.kuleuven.be/handle/20.500.12942/719835

Diagnostic performance of deep learning algorithm for analysis of computed tomography myocardial perfusion

Autor: Giuseppe Muscogiuri, Mattia Chiesa, Andrea Baggiano, Pierino Spadafora, Rossella De Santis, Marco Guglielmo, Stefano Scafuri, Laura Fusini, Saima Mushtaq, Edoardo Conte, Andrea Annoni, Alberto Formenti, Maria Elisabetta Mancini, Francesca Ricci, Francesco Paolo Ariano, Luigi Spiritigliozzi, Mario Babbaro, Rocco Mollace, Riccardo Maragna, Carlo Maria Giacari, Daniele Andreini, Andrea Igoren Guaricci, Gualtiero I. Colombo, Mark G. Rabbat, Mauro Pepi, Francesco Sardanelli, Gianluca Pontone

Publikováno v: European Journal of Nuclear Medicine and Molecular Imaging. 49:3119-3128

Purpose: Artificial intelligence could play a key role in cardiac imaging analysis. To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cc452b90aba1f98439e20741a61342f
https://doi.org/10.1007/s00259-022-05732-w