Abstract Purpose: To develop and demonstrate an image-driven computational framework for reconstructing patient specific Type-B aortic dissection (TBAD) geometry and analyzing associated hemodynamics, with the goal of improving assessment of true lumen (TL), false lumen (FL), and tear morphology. Methods: Computed tomography (CT) images were processed in 3D Slicer to manually segment the TL, FL, tear size, and overall dissection morphology. Forty-eight axial cross-sections from the aortic arch to the FL termination were analyzed to quantify lumen areas. The reconstructed 3D geometry was used to generate a high-fidelity computational domain. Unsteady Navier–Stokes equations were solved under physiologic pulsatile flow conditions to assess velocity fields, pressure distribution, and WSS throughout the cardiac cycle. Results: Simulations suggested that systolic flow preferentially entered the FL, producing elevated FL pressure relative to the TL, while diastolic flow into the FL decreased substantially. Increased WSS occurred in the TL due to higher velocity gradients. Geometric conditions such as a small or absent distal tear were associated with greater pressure buildup in the FL, indicating increased risk of rupture. Conclusion: The integrated image-based segmentation and CFD platform provides a reliable method for evaluating TBAD hemodynamics. The approach captures relevant pressure and stress patterns and can be readily extended to develop patient specific simulators, offering potential value for diagnosis, risk assessment, and treatment planning in TBAD.
Aboelkassem et al. (Mon,) studied this question.