A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.

Journal: Tomography (Ann Arbor, Mich.)
Published Date: Sep 3, 2024

Abstract

BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. Radiomics analysis in cardiovascular disease has largely focused on CT and MRI modalities. This scoping review aims to summarise the existing literature on radiomic analysis techniques in cardiovascular disease.

Authors

  • Arshpreet Singh Badesha
    Department of Radiology, St. James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, UK.
  • Russell Frood
    Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.
  • Marc A Bailey
    Faculty of Medicine and Health, University of Leeds, Leeds LS2 9TJ, UK.
  • Patrick M Coughlin
    The Leeds Vascular Institute, Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds LS1 3EX, UK.
  • Andrew F Scarsbrook
    Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.

Keywords

External Resources

Popular Topics
Recent Journals