Computational fluid dynamics of bladder voiding using 3D dynamic MRI.

Over the last couple of decades, image-based computational fluid dynamics (CFD) has revolutionized cardiovascular research by uncovering hidden features of wall strain, impact of vortices, and its use in treatment planning, as examples, that were simply not evident in the gold-standard catheterization studies done previously. In the work presented here, we have applied magnetic resonance imaging (MRI)-based CFD to study bladder voiding and to demonstrate the feasibility and potential of this approach. We used 3D dynamic MRI to image the bladder and urethra during voiding. A surface mesh processing tool was developed to process the bladder wall prior to executing a wall-motion driven CFD simulation of the bladder and urethra. The obtained flow rate and pressure were used to calculate urodynamic nomograms, which are currently used in the clinical setting to assess bladder voiding dysfunction. These nomograms concluded that our healthy volunteer has an unobstructed bladder and normal contractility. We calculated the work done to void the bladder and propose this as an additional quantitative metric to comprehensively assess bladder function. Further, we discuss the areas that would improve this relatively new methodology of image-based CFD in urodynamics.

Enhanced 4D Flow MRI-Based CFD with Adaptive Mesh Refinement for Flow Dynamics Assessment in Coarctation of the Aorta.

4D Flow MRI is a diagnostic tool that can visualize and quantify patient-specific hemodynamics and help interventionalists optimize treatment strategies for repairing coarctation of the aorta (COA). Despite recent developments in 4D Flow MRI, shortcomings include phase-offset errors, limited spatiotemporal resolution, aliasing, inaccuracies due to slow aneurysmal flows, and distortion of images due to metallic artifact from vascular stents. To address these limitations, we developed a framework utilizing Computational Fluid Dynamics (CFD) with Adaptive Mesh Refinement (AMR) that enhances 4D Flow MRI visualization/quantification. We applied this framework to five pediatric patients with COA, providing in-vivo and in-silico datasets, pre- and post-intervention. These two data sets were compared and showed that CFD flow rates were within 9.6% of 4D Flow MRI, which is within a clinically acceptable range. CFD simulated slow aneurysmal flow, which MRI failed to capture due to high relative velocity encoding (Venc). CFD successfully predicted in-stent blood flow, which was not visible in the in-vivo data due to susceptibility artifact. AMR improved spatial resolution by factors of 101 to 103 and temporal resolution four-fold. This computational framework has strong potential to optimize visualization/quantification of aneurysmal and in-stent flows, improve spatiotemporal resolution, and assess hemodynamic efficiency post-COA treatment.