Quantification of coronary calcification in non-gated CT imaging.
Research type
Research Study
Full title
Quantification of coronary artery calcification in contrast enhanced, un-gated, non-cardiac CT imaging: a comparison with the Agatston score derived from dedicated CT coronary calcium imaging.
IRAS ID
322243
Contact name
Richard Good
Contact email
Sponsor organisation
Golden Jubilee/National Waiting Times Centre
Duration of Study in the UK
1 years, 0 months, 0 days
Research summary
Coronary artery calcification is indicative of atherosclerotic coronary artery disease and is a major determinant of cardiovascular events and all cause mortality for patients. Coronary calcification can be detected on commuted tomography (CT) scans, the "gold standard" investigation is a gated non-contrast cardiac CT. We have identified that coronary calcification can also be detected on ungated CT that include the heart in the field of view. These scans are performed for a number of non-cardiac indications including sepsis, cancer and lung disease. This ‘incidental’ finding is often not reported and patients may remain undertreated for the prevention of cardiovascular events. In addition, coronary calcification may be a harbinger of risk for patients undergoing treatments including surgery, chemotherapy or radiotherapy.
Artificial intelligence applied to the analysis of medical imaging is a rapidly evolving field with the potential to transform the way we detect and manage many conditions. Together with Canon Medical Europe Ltd and University of Glasgow, our team in GJNH have developed a number of projects to assess the presence and extent of coronary calcification on ungated CT scans that include the heart in the field of view. In particular, we are developing an artificial intelligence algorithm to automatically detect and report this finding.
As previous mentioned the "gold standard" investigation for coronary calcification is CT-CA. Calcification on these scans is quantified using a threshold level previously determined by Agatston et al, providing an overall Agatston score.
The aim of this project is to compare the manual and AI quantification of calcification via coronary calcium score (CCS) on ungated, contrast enhanced CT scans with the historic Agatston score derived from a dedicated, non-contrast, cardiac gated CT scan. To our knowledge contrast enhanced CT scans have not be assessed for the ability to detect and quantify coronary calcification.
REC name
South Central - Hampshire B Research Ethics Committee
REC reference
23/SC/0052
Date of REC Opinion
12 May 2023
REC opinion
Further Information Favourable Opinion