Extraction of coronary atherosclerotic plaques from computed tomography imaging: a review of recent methods

H Liu, A Wingert, J Wang, J Zhang, X Wang… - Frontiers in …, 2021 - frontiersin.org
Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD).
Currently, computed tomography (CT) is the most commonly applied imaging technique in …

Coronary computed tomography angiography–derived fractional flow reserve: an expert consensus document of Chinese Society of Radiology

LJ Zhang, C Tang, P Xu, B Guo, F Zhou… - Journal of Thoracic …, 2022 - journals.lww.com
Invasive fractional flow reserve (FFR) measured by a pressure wire is a reference standard
for evaluating functional stenosis in coronary artery disease. Coronary computed …

Artificial intelligence applications in aortic dissection imaging

D Mastrodicasa, M Codari, K Bäumler… - Seminars in …, 2022 - Elsevier
In 2020, the US Food and Drug Administration (FDA) reviewed and authorized over 60
artificial intelligence (AI)-enabled devices across a variety of medical fields, including …

[HTML][HTML] Cardiac CT perfusion and FFRCTA: pathophysiological features in ischemic heart disease

S Seitun, A Clemente, C De Lorenzi… - Cardiovascular …, 2020 - ncbi.nlm.nih.gov
Cardiac computed tomography (CCT) has rapidly evolved, becoming a powerful integrated
tool for the evaluation of coronary artery disease (CAD), and being superior to other …

Value of Machine Learning–based Coronary CT Fractional Flow Reserve Applied to Triple-Rule-Out CT Angiography in Acute Chest Pain

SS Martin, D Mastrodicasa, M van Assen… - Radiology …, 2020 - pubs.rsna.org
Purpose To evaluate the additional value of noninvasive artificial intelligence (AI)–based CT-
derived fractional flow reserve (CT FFR), derived from triple-rule-out coronary CT …

The impact of deep learning reconstruction on image quality and coronary CT angiography-derived fractional flow reserve values

C Xu, M Xu, J Yan, YY Li, Y Yi, YB Guo, M Wang… - European …, 2022 - Springer
Objectives To explore the impact of deep learning reconstruction (DLR) on image quality
and machine learning-based coronary CT angiography (CTA)-derived fractional flow …

[HTML][HTML] Cardiac CT angiography: Normal and pathological anatomical features—A narrative review

A Clemente, S Seitun, C Mantini, G Gentile… - Cardiovascular …, 2020 - ncbi.nlm.nih.gov
The normal and pathological anatomy of the heart and coronary arteries are nowadays
widely developed topics and constitute a fundamental part of the cultural background of the …

Additional value of machine-learning computed tomographic angiography-based fractional flow reserve compared to standard computed tomographic angiography

D Lossnitzer, L Chandra, M Rutsch, T Becher… - Journal of Clinical …, 2020 - mdpi.com
Background: Machine-learning-based computed-tomography-derived fractional flow reserve
(CT-FFRML) obtains a hemodynamic index in coronary arteries. We examined whether it …

Artificial intelligence and its application in cardiovascular disease management

V Namasivayam, N Senguttuvan, V Saravanan… - Machine Learning and …, 2022 - Springer
Artificial intelligence (AI) is a type of computing technology that enables machines to perform
cognitive functions like a human brain. In comparison to manual or traditional approaches …

Prevalence of pathological FFRCT values without coronary artery stenosis in an asymptomatic marathon runner cohort

S Gassenmaier, I Tsiflikas, S Greulich, J Kuebler… - European …, 2021 - Springer
Objectives To evaluate computed tomography fractional flow reserve (FFRCT) values in
distal parts of the coronaries in an asymptomatic cohort of marathon runners without any …