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Principal component analysis of morphological features of the aortic arch for predicting the risk for acute type B aortic dissection.

Created on 09 Jul 2026

Authors

Yanqing Zhan, Chenshu Li, Ruihua Wang, Peng Qiu, Wei Chen

Published in

Scientific reports. Jul 08, 2026. Epub Jul 08, 2026.

Abstract

To characterize aortic morphological features associated with Stanford type B aortic dissection. This retrospective cross-sectional study included patients who underwent contrast-enhanced CT angiography between January 2017 and December 2018. TBAD cases and controls without aortic disease were identified based on imaging findings. The dataset was randomly divided into a derivation cohort and an independent validation cohort. Aortic geometric parameters were measured and summarized using principal component analysis (PCA). A multivariable logistic regression model was developed in the derivation cohort and evaluated in the validation cohort, with performance assessed by discrimination and calibration in distinguishing TBAD cases from controls. In multivariable analysis, hypertension, rotated component 1, and rotated component 5 were associated with increased odds of TBAD, whereas age, smoking status, rotated component 2, and rotated component 4 were associated with decreased odds. The area under the curve (AUC) was 0.935 (95% CI 0.912-0.959) in the derivation cohort and 0.948 (95% CI 0.918-0.977) in the validation cohort. The Hosmer-Lemeshow test indicated no evidence of poor fit (P = 0.971). This study identified PCA-derived morphological features associated with Stanford type B aortic dissection. These findings may contribute to future risk stratification strategies. Further validation in prospective, multicenter studies is required.Trial registration: Chinese Clinical Trials Registry: ChiCTR2000029219.

PMID:
42420543
Bibliographic data and abstract were imported from PubMed on 09 Jul 2026.

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