About this Research Topic
Radiomics is an emerging field in medical image analysis which aims to enumerate concepts of texture and shape using mathematical formulas. These novel imaging markers increase the amount of information extractable from different pathologies on radiological images. Recent investigations in the field of cardiovascular imaging have indicated that these imaging features hold valuable information regarding cardiovascular pathologies above and beyond volumetric analyses. Radiomics has the potential to provide precision phenotyping of diseases based on in-vivo medical imaging, therefore transforming patient diagnosis, management and prognostication in the future.
In recent years several papers have shown that radiomic analysis of coronary atherosclerosis can identify vulnerable plaques prone to rupture better than conventional qualitative and quantitative markers. It has also been shown that radiomic analysis of the perivascular fat tissue holds valuable information regarding inflammation and it may help identify patients at risk of future events. Furthermore, results indicate that analyses of the myocardium may help in identifying different disease pathologies.
This research topic aims to provide readers with a comprehensive overview of the ongoing efforts to utilize radiomics in different domains of cardiovascular imaging. In this collection we wish to provide readers with new results on using radiomics to better understand cardiovascular disease pathologies, identify cardiovascular diseases and improve patient prognostication.
Article submissions on applications of radiomics in cardiovascular imaging will be considered, with special focus on:
1) Precision phenotyping of cardiovascular diseases using radiomics analysis.
2) Utilizing radiomic analysis to improve patient prognostication.
3) Connecting biomarker data with radiomic signatures of cardiovascular diseases.
4) Linking radiomics with genomics.
In recent years several papers have shown that radiomic analysis of coronary atherosclerosis can identify vulnerable plaques prone to rupture better than conventional qualitative and quantitative markers. It has also been shown that radiomic analysis of the perivascular fat tissue holds valuable information regarding inflammation and it may help identify patients at risk of future events. Furthermore, results indicate that analyses of the myocardium may help in identifying different disease pathologies.
This research topic aims to provide readers with a comprehensive overview of the ongoing efforts to utilize radiomics in different domains of cardiovascular imaging. In this collection we wish to provide readers with new results on using radiomics to better understand cardiovascular disease pathologies, identify cardiovascular diseases and improve patient prognostication.
Article submissions on applications of radiomics in cardiovascular imaging will be considered, with special focus on:
1) Precision phenotyping of cardiovascular diseases using radiomics analysis.
2) Utilizing radiomic analysis to improve patient prognostication.
3) Connecting biomarker data with radiomic signatures of cardiovascular diseases.
4) Linking radiomics with genomics.
Keywords: Radiomics, artificial intelligence, cardiovascular pathology, cardiovascular imaging
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