How accurate is atherosclerosis imaging by coronary computed tomography angiography?

Nakanishi, Rine; Motoyama, Sadako; Leipsic, Jonathon; Budoff, Matthew J.

doi:10.1016/j.jcct.2019.06.005

Cited by 33 publications

(23 citation statements)

References 61 publications

(81 reference statements)

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“…[2][3][4][5][6][7] While atherosclerosis quantification and characterization by CCTA appears to be a highly effective non-invasive approach for direct visualization for assessing disease progression, stabilization and future cardiovascular events 8 , whole heart quantitative CCTA analysis of atherosclerosis requires high expertise and is time-intensive for manual or semi-automated evaluation. 9 Recently, advancements in data science and computational processing power now enable application of deep learning frameworks applied to CCTA images for enhanced automation. [10][11][12][13][14][15] We hypothesized that AI-aided analysis would allow for rapid, accurate evaluation of vessel morphology and stenosis when compared to consensus of Level 3 (L3) expert readers.…”

Section: Introductionmentioning

confidence: 99%

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study

Choi

Marques

Kumar

et al. 2021

Journal of Cardiovascular Computed Tomography

101

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Background: Atherosclerosis evaluation by coronary computed tomography angiography (CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming and requires high expertise. Artificial Intelligence (AI) applied to CCTA for comprehensive CAD assessment may overcome these limitations. We hypothesized AI aided analysis allows for rapid, accurate evaluation of vessel morphology and stenosis. Methods: This was a multi-site study of 232 patients undergoing CCTA. Studies were analyzed by FDA-cleared software service that performs AI-driven coronary artery segmentation and labeling, lumen and vessel wall determination, plaque quantification and characterization with comparison to ground truth of consensus by three L3 readers. CCTAs were analyzed for: % maximal diameter stenosis, plaque volume and composition, presence of high-risk plaque and Coronary Artery Disease Reporting & Data System (CAD-RADS) category.

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Section: Introductionmentioning

confidence: 99%

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study

Choi

Marques

Kumar

et al. 2021

Journal of Cardiovascular Computed Tomography

101

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“…Furthermore, the severity of coronary plaques estimated by imaging is consistent with intravascular ultrasound (IVUS) (23). However, it cannot detect minute elements such as macrophage accumulation and prominent plaque characteristics (24).…”

Section: The Significance Of Vascular Calcification Assessed By Ct Especially In the Coronary Arterymentioning

confidence: 74%

Advances in CT Techniques in Vascular Calcification

Zhang

Feng

et al. 2021

Front. Cardiovasc. Med.

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Vascular calcification, a common pathological phenomenon in atherosclerosis, diabetes, hypertension, and other diseases, increases the incidence and mortality of cardiovascular diseases. Therefore, the prevention and detection of vascular calcification play an important role. At present, various techniques have been applied to the analysis of vascular calcification, but clinical examination mainly depends on non-invasive and invasive imaging methods to detect and quantify. Computed tomography (CT), as a commonly used clinical examination method, can analyze vascular calcification. In recent years, with the development of technology, in addition to traditional CT, some emerging types of CT, such as dual-energy CT and micro CT, have emerged for vascular imaging and providing anatomical information for calcification. This review focuses on the latest application of various CT techniques in vascular calcification.

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“…However, the diagnostic potential of CCTA is burdened by a certain degree of subjectivity and inter-reader variability. Moreover, it is unable to detect some fine elements characteristic of high risk plaques, such as macrophage activity, neovascularization, plaque rupture and plaque erosion, which in turn can all be identified by OCT (33).…”

Section: Limitations In Conventional Ct Analysis and Future Directionsmentioning

confidence: 99%

Cardiac computed tomography radiomics: an emerging tool for the non-invasive assessment of coronary atherosclerosis

Murgia¹,

Balestrieri²,

Crivelli³

et al. 2020

Cardiovasc Diagn Ther

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In the last decades, significant advances have been made in the preventive approaches to cardiovascular disease. Even so, coronary artery disease remains one of the main causes of morbidity and mortality worldwide. Invasive imaging modalities, such as intravascular ultrasound or optical coherence tomography, have played a key role in the comprehension of the pathological processes underlying myocardial infarction and cerebrovascular disease. These imaging techniques have contributed greatly to the identification and phenotyping of the culprit lesion, the so-called vulnerable plaque. Coronary computed tomographic angiography (CCTA) has emerged in more recent years as the non-invasive modality of choice in the study of coronary atherosclerosis, showing in many studies a diagnostic yield comparable to invasive approaches. Moreover, being able to describe extra-luminal characteristics of the affected vessel, CCTA has greatly contributed towards shifting the attention of researchers from the mere quantification of luminal stenosis to the identification of adverse plaque features, which appear to have a stronger prognostic value.However, the identification of some of the hallmarks of vulnerable plaques is qualitative in nature and, therefore, subject to some degree of inter-reader variability. Moreover, CCTA is still unable to identify some fine markers of plaque vulnerability which can be detected by invasive techniques, such as neovascularization and plaque erosion, among others. Nonetheless, radiological images can be viewed as vast 3-D datasets which, via the use of recent technology, allow for the extraction of numerous quantitative features that may be used to accurately phenotype a given lesion. Radiomics is the process of extrapolating innumerable parameters from a given region of interest, with the goal of establishing correlations between quantitative variables and clinical data. These datasets can then be manipulated to create predictive models via the use of automated algorithms in a process called machine learning. As a result of these approaches, radiological images may offer information regarding the characterization of a plaque which can go much beyond the boundaries of what can be qualitatively asserted by the human eye, contributing to expanding the knowledge of the disease and ultimately assist clinical decisions. Thus far, radiomics has found its more consistent area of application in the field of oncology; to present date, the amount of clinical data regarding coronary artery disease is still relatively small, partly due to the technical difficulties associated with the implementation of such techniques to the study of a small and geometrically complex lesion such as the coronary plaque. The present review, after a summary of the imaging modalities most commonly used nowadays in the study of coronary plaques, will provide a perspective on the application of radiomic analysis to coronary artery disease.

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How accurate is atherosclerosis imaging by coronary computed tomography angiography?

Cited by 33 publications

References 61 publications

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study

Advances in CT Techniques in Vascular Calcification

Cardiac computed tomography radiomics: an emerging tool for the non-invasive assessment of coronary atherosclerosis

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How accurate is atherosclerosis imaging by coronary computed tomography angiography?

Cited by 33 publications

References 61 publications

CT ​Evaluation ​by ​Artificial ​Intelligence ​for ​Atherosclerosis, Stenosis and Vascular ​Morphology ​(CLARIFY): ​A ​Multi-center, international study

CT ​Evaluation ​by ​Artificial ​Intelligence ​for ​Atherosclerosis, Stenosis and Vascular ​Morphology ​(CLARIFY): ​A ​Multi-center, international study

Advances in CT Techniques in Vascular Calcification

Cardiac computed tomography radiomics: an emerging tool for the non-invasive assessment of coronary atherosclerosis

Contact Info

Product

Resources

About

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study

CT Evaluation by Artificial Intelligence for Atherosclerosis, Stenosis and Vascular Morphology (CLARIFY): A Multi-center, international study