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- W4229377263 abstract "Abstract Benign prostatic hyperplasia (BPH) is a common disease associated with lower urinary tract symptoms and is the most frequent benign tumor in men. To reduce BPH therapy complications, prostatic artery embolization (PAE) was developed to replace the surgical options. PAE is a minimally invasive technique in which emboli are injected into the prostate arteries (PA), obstructing the blood flow in the hypervascular nodules. In this work, a personalized PAE treatment strategy was proposed using patient-specific computational fluid dynamics (CFD). First, the hemodynamics environment in the iliac arterial tree considering a large network of bifurcations was studied. The results showed complex blood flow patterns in the iliac arterial network. Subsequently, the transport of embolic particulates during PAE for the standard horizontal and hypothetical vertical patient positioning was simulated using Lagrangian particle tracking. Emboli of different sizes were released at various locations across the iliac arterial tree. The emboli entering the PA were mapped back to their initial location to create emboli release maps (ERMs). The obtained ERMs during the standard patient positioning for smaller emboli at certain release locations showed distinct regions in which if the emboli were released within these regions, all of them would reach the PA without nontarget embolization. During the hypothetical vertical patient positioning, the larger emboli formed a larger coherent region in the ERMs. Our patient-specific model can be used to find the best spatial location for emboli injection and perform the embolization procedure with minimal off-target delivery." @default.
- W4229377263 created "2022-05-10" @default.
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- W4229377263 date "2022-06-16" @default.
- W4229377263 modified "2023-09-27" @default.
- W4229377263 title "Guiding the Prostatic Artery Embolization Procedure With Computational Fluid Dynamics" @default.
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- W4229377263 doi "https://doi.org/10.1115/1.4054515" @default.
- W4229377263 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35532245" @default.
- W4229377263 hasPublicationYear "2022" @default.
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