Digital Twin and Artificial Intelligence Technologies to Assess the Type IA Endoleak.

ABSTRACT:

Background/objectives

Endovascular aneurysm repair (EVAR) is the standard treatment for abdominal aortic aneurysms, but the risk of endoleak compromises its effectiveness. Type IA endoleak, stemming from an inadequate proximal seal, is the most critical complication associated with the highest risk of rupture. Current preoperative planning relies on static anatomical measurements from computed tomography angiography that fail to predict seal failure due to dynamic biomechanical forces. This study aimed to retrospectively validate the predictive accuracy of a novel physics-informed digital twin and artificial intelligence (AI) model for predicting type IA endoleak risk compared to conventional static planning methods.

Methods

This was a retrospective, single-center proof-of-c

SUBMITTER: Cho S 

PROVIDER: S-EPMC12837158 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature