Evaluation of segmentation accuracy and its impact on patient-specific CFD analysis

Medical image segmentation, especially for biological soft tissues, is an issue of great interest. The aim of this study is to evaluate the segmentation performance of a commercial and an open-source software, to segment aortic root and coronary arteries. 3D printing stereolithography technology was used to generate ground truth models, which were then re-acquired by means of a micro-CT scanner. Measurements from the printed and reconstructed models with both the software were compared, in order to evaluate the level of agreement. In the second phase of this study, Computational Fluid Dynamics (CFD) simulations were conducted, to compare the outputs between the models segmented with the two software. The goal was to understand how differences in the segmentation process propagate in CFD results. Results showed that both software guarantee satisfactory segmentation performance, with average geometrical differences between reconstructed and physical models in the order of a few percentage points. However, when we consider thin details, as a sharp stenotic region, the commercial validated software seems to be more accurate in replicating the real anatomy. We also realized how apparently negligible geometrical differences, varying the employed software, can turn into enormous variations of hemodynamic parameters, such as velocity and wall shear stress, which place in the centre the delicate role the segmentation process holds. This evidence is crucial in the biomedical field and especially in a coronary arteries study, where CFD simulations can be exploited as a starting point for surgery considerations.