Diagnostics, Vol. 16, Pages 600: Semi-Automated Plaque Assessment in Cardiac CT: Prognostic Value in Long-Term Follow-Up of Intermediate Stenosis

Diagnostics doi: 10.3390/diagnostics16040600

Authors:
Laura Zajančkauskienė
Kristina Balnė
Eglė Montrimavičienė
Antanas Jankauskas
Gintarė Šakalytė

Background/Objectives: Intermediate coronary artery stenosis is difficult to risk-stratify, as stenosis severity alone often fails to predict events. This study aimed to evaluate whether quantitative CCTA-derived plaque characteristics and lesion morphology are associated with MACE during long-term follow-up. Methods: In this single-center prospective study, 128 patients with stable angina symptoms underwent standardized CCTA and were diagnosed with at least one intermediate coronary stenosis (50–69%, CAD-RADS 3). Quantitative parameters of lesion morphology, lumen geometry, vessel wall dimensions, and plaque composition were assessed using semi-automated CCTA adapted plaque analysis (QAngio CT). Patients were followed for a median of 72 months. MACE was defined as a composite outcome of all-cause mortality, target lesion revascularization, non-fatal MI, and stroke. Results: During follow-up, 26.6% of patients experienced MACE. High-risk plaque features were more frequent in patients with MACE. Lesions associated with MACE demonstrated significantly smaller lumen area, reduced mean lumen diameter, and decreased vessel wall area at the obstruction site. In addition, plaques leading to adverse events exhibited larger necrotic core areas. Although no single quantitative parameter independently predicted MACE, a combined multivariable model incorporating lumen geometry and plaque composition showed significant prognostic value. Conclusions: In patients with intermediate coronary stenosis, lesion-specific quantitative CCTA parameters—particularly luminal geometry and necrotic core extent—provide prognostic information beyond traditional plaque burden and stenosis assessment. Incorporating detailed plaque morphology into routine CCTA evaluation may improve long-term risk stratification and support more individualized clinical management.

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Laura Zajančkauskienė www.mdpi.com