SCCT 2021 expert consensus document on coronary computed tomographic angiography: a report of the society of cardiovascular computed tomography

J Narula, Y Chandrashekhar, A Ahmadi… - Journal of …, 2020 - pmc.ncbi.nlm.nih.gov
Cardiac computed tomography (CT) has changed rapidly since the last major guideline from
SCCT. 1 While there have been significant advances in technology, the most gratifying part …

Coronary CT angiography–derived fractional flow reserve

C Tesche, CN De Cecco, MH Albrecht, TM Duguay… - Radiology, 2017 - pubs.rsna.org
Invasive coronary angiography (ICA) with measurement of fractional flow reserve (FFR) by
means of a pressure wire technique is the established reference standard for the functional …

Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography–based fractional flow reserve: result from the MACHINE …

A Coenen, YH Kim, M Kruk, C Tesche… - Circulation …, 2018 - Am Heart Assoc
Background: Coronary computed tomographic angiography (CTA) is a reliable modality to
detect coronary artery disease. However, CTA generally overestimates stenosis severity …

A machine-learning approach for computation of fractional flow reserve from coronary computed tomography

L Itu, S Rapaka, T Passerini… - Journal of applied …, 2016 - journals.physiology.org
Fractional flow reserve (FFR) is a functional index quantifying the severity of coronary artery
lesions and is clinically obtained using an invasive, catheter-based measurement. Recently …

Coronary CT angiography–derived fractional flow reserve: machine learning algorithm versus computational fluid dynamics modeling

C Tesche, CN De Cecco, S Baumann, M Renker… - Radiology, 2018 - pubs.rsna.org
Purpose To compare two technical approaches for determination of coronary computed
tomography (CT) angiography–derived fractional flow reserve (FFR)—FFR derived from …

CT FFR for ischemia-specific CAD with a new computational fluid dynamics algorithm: a Chinese multicenter study

CX Tang, CY Liu, MJ Lu, UJ Schoepf, C Tesche… - Cardiovascular …, 2020 - jacc.org
Objectives The aim of this study was to validate the feasibility of a novel structural and
computational fluid dynamics–based fractional flow reserve (FFR) algorithm for coronary …

Integrating CT myocardial perfusion and CT-FFR in the work-up of coronary artery disease

A Coenen, A Rossi, MM Lubbers, A Kurata… - JACC: Cardiovascular …, 2017 - jacc.org
Objectives: The aim of this study was to investigate the individual and combined accuracy of
dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed …

Artificial intelligence in cardiac radiology

M van Assen, G Muscogiuri, D Caruso, SJ Lee… - La radiologia …, 2020 - Springer
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its
implementation will be focused on the automatization tasks, improving diagnostic accuracy …

Influence of coronary calcium on diagnostic performance of machine learning CT-FFR: results from MACHINE registry

C Tesche, K Otani, CN De Cecco, A Coenen… - Cardiovascular …, 2020 - jacc.org
Objectives This study was conducted to investigate the influence of coronary artery calcium
(CAC) score on the diagnostic performance of machine-learning–based coronary computed …

On-site computed tomography–derived fractional flow reserve to guide management of patients with stable coronary artery disease: the TARGET randomized trial

J Yang, D Shan, X Wang, X Sun, M Shao, K Wang… - Circulation, 2023 - Am Heart Assoc
Background: Computed tomography–derived fractional flow reserve (CT-FFR) using on-site
machine learning enables identification of both the presence of coronary artery disease and …