The argument appears in a perspective article published open access in the journal Cardiovascular Diabetology on 17 October 2026, authored by Nordin M.J. Hanssen, Cheyenne Y.Y. Beverloo, Saloua El Messaoudi, Richard A.P. Takx and Nick S. Nurmohamed.
The authors frame their proposal against a growing clinical challenge. Because of the increasing prevalence of diabetes, the burden of cardiovascular disease attributable to the condition is projected to rise substantially. At the same time, they note a growing need to better identify the patients at highest cardiovascular risk and to optimise the use of increasingly available but costly weight-, glucose- and lipid-lowering therapies. More precise risk stratification, they suggest, would help target these treatments to the patients most likely to benefit.
Their central postulate is that coronary CT angiography, potentially enhanced by novel artificial intelligence-based image analysis, could serve as a valuable tool for more accurately assessing atherosclerotic cardiovascular risk in diabetes care. Patients with diabetes represent one of the highest-risk populations for coronary artery disease, making them a group in which quantifying the actual burden of coronary atherosclerosis could carry particular clinical value.
The authors point to practical trends that make the technique more feasible than in the past. With ongoing reductions in cost and radiation exposure, coronary CT angiography has become a more accessible modality for quantifying coronary artery disease burden. Artificial intelligence-guided analysis may further enhance scalability by reducing radiologist workload and improving reproducibility.
The perspective is not an unqualified endorsement. The authors explicitly discuss the current limitations of the approach, including unresolved questions about whether intravenous contrast should be used, and how best to manage incidental findings or clinically significant stenoses discovered during scanning. These operational and interpretive questions, they indicate, remain open and will shape whether the technique can be integrated into routine diabetes care.
Beyond individual patient care, the article explores a research application: the potential role of coronary CT angiography-derived endpoints in clinical trials of anti-atherosclerotic therapies. Traditional major adverse cardiovascular event outcomes increasingly require large sample sizes because event rates are declining, which drives up the cost and duration of trials. Imaging-based endpoints could complement or partially replace these hard outcomes.
The authors outline a specific trial design concept: combining non-inferiority on hard clinical endpoints with superiority on coronary CT angiography measures. Such a design, they suggest, may reduce costs while accelerating the generation of evidence about new therapies.
Ultimately, the article argues that integrating AI-guided coronary CT angiography into clinical care and research may enable more precise and scalable cardiovascular risk stratification in diabetes care. The authors present the piece as a balanced assessment of both the promise and the limitations of the approach, rather than a declaration that the technology is ready for immediate routine adoption. The question posed in its title—whether the technique is ready for prime time—remains, on their account, an open one that further work on cost, contrast use, incidental findings and AI-based analysis will need to answer.
Subject of Research: The potential role of AI-guided coronary CT angiography in cardiovascular risk stratification and clinical trials in diabetes care
Article Title: Is (AI-guided) coronary CT angiography ready for prime time in diabetes care and research?
Article References: Hanssen, N. M. J., Beverloo, C. Y. Y., Messaoudi, S. E., Takx, R. A. P., & Nurmohamed, N. S. (2026). Is (AI-guided) coronary CT angiography ready for prime time in diabetes care and research?. Cardiovascular Diabetology. https://doi.org/10.1186/s12933-026-03412-9
Image Credits: AI Generated
DOI: 10.1186/s12933-026-03412-9
Keywords: coronary CT angiography, artificial intelligence, diabetes, cardiovascular risk, atherosclerosis, clinical trials, medical imaging, CCTA, risk stratification, Cardiovascular Diabetology, AI-guided, coronary
News Source: Ophelia Keating. (October 30, 2026). AI-guided coronary CT angiography may sharpen cardiovascular risk assessment in diabetes. Scienmag.
