Machine Learning-Assisted Feature Selection Identifies the Joint Association of Body Mass Index and Periaortic Adipose Tissue as a Risk Factor for Aortic Dissection: A Multicenter Retrospective Study

BACKGROUNDAortic dissection (AD) is a life-threatening emergency with high mortality. Although elevated body mass index (BMI) is associated with both AD incidence and mortality, the underlying mechanisms remain unclear. Periaortic adipose tissue (PAAT) increases with BMI, and the PAAT of AD shows marked inflammatory infiltration, suggesting PAAT-driven inflammation may contribute to the development of AD. However, no direct evidence links BMI and PAAT to AD. To further elucidate the obesity-inflammation-AD relationship, we aim to quantify the contributions of BMI, PAAT, and their derived indices to the risk of AD. METHODSThis retrospective multicenter study (June-November 2025) quantified PAAT around the descending thoracic aorta with CT angiography (CTA). Logistic regression analyses were performed to identify AD risk factors. Based on the Boruta algorithm (a machine learning feature selection method) and ROC curve analysis, the variable importance for AD risk was assessed. The dose-response relationship between BMI-Volume-derived metric (BMV) and AD risk was further characterized by quartile stratification and restricted cubic spline (RCS). RESULTSThis study enrolled 376 consecutive participants. After adjusting for potential confounders, BMI, smoking, systolic blood pressure (SBP), diabetes mellitus (DM), TC/HDLC, ApoE, PAAT volume (Volume), PAAT fat attenuation index (FAI), and BMV were identified as independent predictors of AD. Volume was the strongest AD predictor with the highest Z-score. Compared with BMI [AUC 0.627, 95% confidence interval (CI): 0.569-0.687] and Volume (AUC 0.716, 95% CI: 0.662-0.772), BMV showed better discriminatory performance (AUC 0.726, 95% CI: 0.673-0.778). RCS showed an approximately linear positive association between BMV and AD risk (P-overall < 0.001, P-non-linear = 0.09). CONCLUSIONSIn this retrospective multicenter study, BMV, a composite measure integrating systemic and periaortic adipose tissue factor, showed a positive association with AD risk, and improved predictive performance beyond BMI, indicating incremental predictive value, pending external validation. GRAPHIC ABSTRACTA graphic abstract is available for this article. WHAT IS KNOWNO_LIBody-mass index (BMI) appears to be associated with an increased risk of aortic dissection (AD) and higher all-cause mortality, but a definitive consensus remains elusive. C_LIO_LIPAAT has been identified as an independent cardiovascular risk factor, with marked inflammatory cell infiltration observed in the PAAT of PAAT has been identified as an independent cardiovascular risk factor, with marked inflammatory cell infiltration observed in the PAAT of aortic diseases patients. C_LIO_LIPAAT increases with BMI, and its pro-inflammatory function may destabilize the aortic wall, but relationship of BMI-PAAT synergy and AD remains to be demonstrated. C_LI WHAT THE STUDY ADDSO_LIBMI, PAAT volume, and its FAI were independent predictors of AD, with volume ranked as the strongest predictor by the Boruta algorithm. C_LIO_LIThe BMV, a composite metric that integrated systemic and periaortic adipose tissue factor, was positively associated with AD risk and improved predictive performance beyond BMI alone. C_LI