Patient-specific computational simulation for thoracic endovascular aortic repair in patients with Stanford type B aortic dissection
Background The accuracy and clinical utility of patient-specific computational simulations for thoracic endovascular aortic repair (TEVAR) planning in Stanford type B aortic dissection (TBAD) patients remain insufficiently validated. Objectives This study aimed to develop and validate the safety and efficacy of a patient-specific computational simulation framework tailored for TEVAR in patients with TBAD. Methods This prospective, observational, multicenter study enrolled 153 consecutive patients with TBAD undergoing TEVAR. Patients were stratified into two groups: the simulation group (n=72) and non-simulation group (n=81). For the simulation cohort, personalized three-dimensional models of the stent frame and covered graft were constructed based on preprocedural computed tomography angiography, followed by computational simulation. The predictive performance of the simulation was evaluated by comparing simulated hemodynamic parameters with postprocedural measurements. The primary endpoint was the procedural success rate. Results The overall cohort had an average age of 67.1 ± 9.1 years, with 66.0% being male. The simulation group showed a higher procedural success rate (100.0% vs. 95.1%, P = 0.042), lower rates of endoleak (0% vs. 9.9%, P = 0.007) and stent-related rupture (0% vs. 4.9%, P = 0.002), and a lower complete false lumen thrombosis rate (61.1% vs. 79.0%, P = 0.015) compared to the non-simulation group. Notably, postprocedural hemodynamic metrics (including maximum pressure gradient, peak velocity, and wall shear stress) were significantly improved in the simulation group (all P < 0.001). Conclusions Patient-specific computational simulation of TEVAR was associated with postprocedural hemodynamic profiles that closely matched simulated predictions, and showed favorable periprocedural trends and potential utility in optimizing pre-TEVAR planning. These findings are preliminary and require validation in randomized controlled settings.