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Health·G Space·Evidence-backed gain·Published 2026-08-03

Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study

Objective To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial intelligence(AI)-derived coronary computed tomography angiography (CCTA) parameters combined with clinical indicators. Methods This retrospective study enrolled 114 patients with T2DM and non-obstructive coronary artery disease (1%-49% stenosis) who underwent CCTA at our hospital between September 2019 and September 2024. After follow-up of 1-5 years, patients were…

TRV-2026-0628Peer-reviewedPermanent record — cite & verify
Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study

"2018.11.03 Continuous Glucose Monitor 14 day, Washington, DC USA 3458" by tedeytan is licensed under CC BY-SA 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/2.0/.

The quick read

Between 2019 and 2024, researchers retrospectively followed 114 patients with type 2 diabetes and non-obstructive coronary artery disease who had baseline CCTA. Using AI-derived measurements of pericoronary adipose tissue and coronary plaques combined with clinical labs, they built a logistic regression nomogram to distinguish 48 patients who later had infarction, revascularization, or stenosis 265 50% from 66 who did not.

The work matters because non-obstructive lesions in diabetes can still progress to major events, and a noninvasive imaging-based risk tool could guide earlier preventive management. What remains uncertain from the supplied text is external validation, generalizability beyond one center and 114 patients, and whether use of the nomogram changes outcomes or costs in practice.

Main points
  • Retrospective study of 114 T2DM patients with 1%-49% stenosis on CCTA between September 2019 and September 2024, followed 1-5 years.
  • 48 patients progressed defined as acute myocardial infarction, revascularization, or stenosis progression to 265 50% on follow-up CCTA versus 66 controls.
  • Progression group had significantly higher glycated hemoglobin (HbA1c) and troponin, and lower HDL-C.
  • Model used stepwise logistic regression combining AI-derived PCAT and plaque parameters with clinical indicators.
Gain

Researchers developed a nomogram using AI-derived CCTA measures of pericoronary adipose tissue and plaque plus HbA1c to predict progression of non-obstructive coronary lesions in T2DM patients.

The rundown

The study enrolled 114 patients with T2DM and non-obstructive disease at a single hospital from September 2019 to September 2024, with 1-5 year follow-up. Progression was defined as acute myocardial infarction, revascularization, or stenosis reaching 265 50% on repeat CCTA.

Clinical and AI-quantified PCAT and plaque features were compared between groups, and stepwise logistic regression identified LAD-FAI, plaque length, and HbA1c as independent predictors incorporated into a nomogram.

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