A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.
No Thumbnail Available
All Authors
Badesha, AS.
Frood, R.
Bailey, MA.
Coughlin, PM.
Scarsbrook, AF.
LTHT Author
Badesha, Arshpreet Singh
Frood, Russell
Bailey, Marc
Coughlin, Patrick
Scarsbrook, Andrew
Frood, Russell
Bailey, Marc
Coughlin, Patrick
Scarsbrook, Andrew
LTHT Department
Radiology
Vascular Surgery
Vascular Surgery
Non Medic
Publication Date
2024
Item Type
Journal Article
Scoping Review
Scoping Review
Language
Subject
Subject Headings
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.
METHODS: MEDLINE and Embase databases were searched for eligible studies evaluating radiomic techniques in living human subjects derived from CT, MRI or PET imaging investigating atherosclerotic disease. Data on study population, imaging characteristics and radiomics methodology were extracted.
RESULTS: Twenty-nine studies consisting of 5753 patients (3752 males) were identified, and 78.7% of patients were from coronary artery studies. Twenty-seven studies employed CT imaging (19 CT carotid angiography and 6 CT coronary angiography (CTCA)), and two studies studied PET/CT. Manual segmentation was most frequently undertaken. Processing techniques included voxel discretisation, voxel resampling and filtration. Various shape, first-order, second-order and higher-order radiomic features were extracted. Logistic regression was most commonly used for machine learning.
CONCLUSION: Most published evidence was feasibility/proof of concept work. There was significant heterogeneity in image acquisition, segmentation techniques, processing and analysis between studies. There is a need for the implementation of standardised imaging acquisition protocols, adherence to published reporting guidelines and economic evaluation.
Journal
Tomography