joom | júm, n.

Vollständiger Abstract

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OBJECTIVES: To assess whether radiomics analysis of carotid ultrasound (CUS) can identify texture features associated with severe coronary artery calcification, even in individuals without carotid plaque. METHODS: This study included 105 participants with coronary artery calcium score (CACS) ≥400 and no carotid plaque, matched by age and sex to 105 controls with CACS = 0. B-mode CUS images of the bilateral distal common carotid arteries (CCA) were analyzed, with 1-cm longitudinal regions of interest extending from the lumen to the adventitia. Radiomic features were extracted from each frame, filtered by variance and correlation, and ranked using bootstrap-based XGBoost feature importance (FI) to identify reproducible features for evaluation. RESULTS: Among 700 extracted features, the final retained features were reproducible: 8 (right) and 11 (left) for CACS = 0, and 7 (right) and 10 (left) for CACS ≥400 (all p < .05). Group-specific features, observed only in the CACS 0 or CACS ≥400 group, included 90th Percentile (CACS = 0: right distal CCA, FI = 0.030; left distal CCA, FI = 0.025) and Run Entropy (CACS ≥400: right distal CCA, FI = 0.046; left distal CCA, FI = 0.038). Shared features such as Long Run Emphasis, Dependence Non-Uniformity, and Entropy were consistently observed across both groups and sides (FI = 0.023-0.029), with Dependence Non-Uniformity consistent in the left distal CCA across both groups. CONCLUSIONS: Although no plaque was detected on CUS, radiomics can identify ultrasound texture patterns associated with severe coronary calcification. This approach may improve detection of high-risk individuals who would otherwise be classified as low-risk by CUS alone.

Abstract: PubMed · Datensatz