Towards a patient-specific hepatic arterial modeling for microspheres distribution optimization in SIRT protocol |
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Authors: | Costanza Simoncini Krzysztof Jurczuk Daniel Reska Simon Esneault Jean-Claude Nunes Jean-Jacques Bellanger Hervé Saint-Jalmes Yan Rolland Pierre-Antoine Eliat Johanne Bézy-Wendling Marek Kretowski |
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Affiliation: | 1.U 1099,INSERM,Rennes,France;2.LTSI,Université de Rennes 1,Rennes,France;3.Faculty of Computer Science,Bialystok University of Technology,Bialystok,Poland;4.Therenva,CCP-CHU Pontchaillou,Rennes,France;5.Centre Eugène Marquis,Rennes,France;6.PRISM,Université de Rennes 1,Rennes,France;7.Biosit UMS 3480,CNRS,Rennes,France;8.UMS 018,INSERM,Rennes,France |
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Abstract: | Selective internal radiation therapy (SIRT) using Yttrium-90 loaded glass microspheres injected in the hepatic artery is an emerging, minimally invasive therapy of liver cancer. A personalized intervention can lead to high concentration dose in the tumor, while sparing the surrounding parenchyma. We propose a computational model for patient-specific simulation of entire hepatic arterial tree, based on liver, tumors, and arteries segmentation on patient’s tomography. Segmentation of hepatic arteries down to a diameter of 0.5 mm is semi-automatically performed on 3D cone-beam CT angiography. The liver and tumors are extracted from CT-scan at portal phase by an active surface method. Once the images are registered through an automatic multimodal registration, extracted data are used to initialize a numerical model simulating liver vascular network. The model creates successive bifurcations from given principal vessels, observing Poiseuille’s and matter conservation laws. Simulations provide a coherent reconstruction of global hepatic arterial tree until vessel diameter of 0.05 mm. Microspheres distribution under simple hypotheses is also quantified, depending on injection site. The patient-specific character of this model may allow a personalized numerical approximation of microspheres final distribution, opening the way to clinical optimization of catheter placement for tumor targeting. |
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