Digital Twin-Based Risk Stratification Integrating Aortic Shape and Wall Mechanics in Acute Uncomplicated Type B Aortic Dissection

Objective This study evaluated whether patient-specific digital twins integrating 3D aortic anatomy and structural wall stress could identify patients with acute uncomplicated type B aortic dissection (AUTBAD) at high risk for adverse aortic events. Methods We analyzed CTAs from 50 patients extracted from a 400 AUTBAD patient database treated with optimal medical therapy from 1999-2025. Digital twin models were constructed, and statistical shape modeling and reduced-order fluid-structure interaction analysis were performed. Anatomic shape and biomechanical stress data were integrated into mode

This content is for informational purposes only and is not medical advice. It is not intended to diagnose, treat, cure, or prevent any disease. Consult a healthcare professional before starting any supplement, treatment, or program: especially if you are pregnant, nursing, taking medication, or managing a health condition.