Cardiac CT: present and future applications

Chahal, Harjit; Levsky, Jeffrey M.; García, Mario J.

doi:10.1136/heartjnl-2015-307481

Cited by 3 publications

(2 citation statements)

References 97 publications

(55 reference statements)

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“…Coronary CTA should not be performed routinely to evaluate for stent thrombosis or restenosis post-PCI. 108 If there is sufficient clinical suspicion, ICA is required for both diagnosis and treatment in these cases.…”

Section: Risk Stratification After Revascularizationmentioning

confidence: 99%

Non-Invasive Imaging in Coronary Syndromes: Recommendations of The European Association of Cardiovascular Imaging and the American Society of Echocardiography, in Collaboration with The American Society of Nuclear Cardiology, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance

Edvardsen

Asch

Davidson

et al. 2022

Journal of Cardiovascular Computed Tomography

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Section: Risk Stratification After Revascularizationmentioning

confidence: 99%

Non-Invasive Imaging in Coronary Syndromes: Recommendations of The European Association of Cardiovascular Imaging and the American Society of Echocardiography, in Collaboration with The American Society of Nuclear Cardiology, Society of Cardiovascular Computed Tomography, and Society for Cardiovascular Magnetic Resonance

Edvardsen

Asch

Davidson

et al. 2022

Journal of Cardiovascular Computed Tomography

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“…This reduces cardiac motion artefact, improves image quality and diagnostic accuracy, and enables better quantitative analysis. 2 These newer systems are relatively expensive and further research is needed into their full potential. In this review, we provide an up-to-date summary of the evolving machine learning (ML) techniques used in conjunction with cardiac CTs, including: (i) coronary artery imaging [fractional flow reserve (FFR), coronary artery calcium (CAC), and plaque characterization], (ii) epicardial adiposity quantification, (iii) aortic stenosis (AS), and (iv) atrial fibrillation (AF).…”

Section: Introductionmentioning

confidence: 99%

Machine learning applications in cardiac computed tomography: a composite systematic review

Bray

Hanif

Alradhawi

et al. 2022

European Heart Journal Open

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Introduction Artificial intelligence (AI) and machine learning (ML) models are rapidly being applied to analysis of cardiac computed tomography (CT). We sought to provide an overview of the contemporary advances brought about by the combination of ML and cardiac CT. Methods Six searches were performed in Medline, Embase and the Cochrane Library up to November 2021 for i) Computed Tomography-Fractional Flow Reserve (CT-FFR), ii) atrial fibrillation, iii) aortic stenosis, iv) plaque characterisation, v) fat quantification and vi) coronary artery calcium score. Results We included 57 studies pertaining to the aforementioned topics. Non-invasive CT-fractional flow reserve (FFR) can accurately be estimated using ML algorithms and has the potential to reduce the requirement for invasive angiography. Coronary artery calcification (CAC) and non-calcified coronary lesions can now be automatically and accurately calculated. Epicardial adipose tissue (EAT) can also be automatically, accurately and rapidly quantified. Effective ML algorithms have been developed to streamline and optimise the safety of aortic annular measurements to facilitate pre-transcatheter aortic valve replacement (TAVR) valve selection. Within electrophysiology, the left atrium (LA) can be segmented and resultant LA volumes have contributed to accurate predictions of post-ablation recurrence of atrial fibrillation. Conclusion In this review, we discuss the latest studies and evolving techniques of ML and cardiac CT.

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Coronary angiotomography in the emergency department

Patiño-Jaramillo¹,

Medina²

2019

Revista Colombiana de Cardiología

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Cardiac CT: present and future applications

Cited by 3 publications

References 97 publications

Machine learning applications in cardiac computed tomography: a composite systematic review

Coronary angiotomography in the emergency department

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