Darsh Gandhi / Mathematics / Faculty Mentor: Mette Olufsen
Chronic thromboembolic pulmonary hypertension (CTEPH) is a fatal disease, causing high blood pressure and unresolved lesions in the pulmonary arteries. Balloon pulmonary angioplasty (BPA) treats some lesions by inserting micro-balloons into the arteries to aid blood flow, but patients typically need to undergo several treatments. However, there is no objective way to identify which lesions to treat to minimize blood pressure and maximize perfusion of the lung. To inform this treatment, we develop a patient-specific fluid mechanics model predicting hemodynamics in geometries extracted from computed tomography (CT) images. From the images, we generate a three-dimensional (3D) volumetric surface and extract centerlines and junctions creating a tree. We developed a statistical change point algorithm to determine vessel radii, length, and uncertainty. We generate 1000 networks by sampling from the distribution of radii from each vessel., and for each network, we predict blood pressure and flow in each vessel. Perfusion is determined by projecting average flow and pressure at the end of each vessel onto the 3D lung volume. Results show segmentation quality, network size, and changes in radius and length significantly impact hemodynamics. Future work includes optimizing BPA strategies for CTEPH patients, simulating lesion reduction and its hemodynamic impact.
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