4.6 Article

Radiomics The Next Frontier of Cardiac Computed Tomography

Journal

CIRCULATION-CARDIOVASCULAR IMAGING
Volume 14, Issue 3, Pages 256-264

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCIMAGING.120.011747

Keywords

atherosclerosis; heart diseases; humans; machine learning; phenotype

Funding

  1. Jiangsu Province Key Project of Comprehensive Prevention and Control of Chronic Diseases [BE2020699]

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Radiomics utilizes advanced image analysis to extract quantitative information, revealing correlations between imaging features and clinical endpoints. Cardiac CT radiomics analysis shows diagnostic potential and benefits for patients and physicians.
Radiomics uses advanced image analysis to extract massive amounts of quantitative information from digital images, which is not otherwise distinguishable to the human eye. The mined data can be used to explore and establish new and undiscovered correlations between these imaging features and clinical end points. Cardiac computed tomography (CT) is a first-line imaging modality for evaluating coronary artery disease and has a primary role in the assessment of cardiac structures. Conventional interpretation of cardiac CT images relies mostly on subjective and qualitative analysis, as well as basic geometric quantification. To date, some proof-of-concept studies have demonstrated the feasibility and diagnostic performance of cardiac CT radiomics analysis. This review describes the current literature on radiomics in cardiac CT and discusses its advantages, challenges, and future directions. Although much evidences are needed in this field, cardiac CT radiomics has a lot to offer to patients and physicians with potential to define cardiac disease phenotypes on imaging with higher precision.

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