Surgical planning for living donor liver transplant using 4D flow MRI, computational fluid dynamics and in vitro experiments

This study used magnetic resonance imaging (MRI), computational fluid dynamics (CFD) modelling and in vitro experiments to predict patient-specific alterations in hepatic hemodynamics in response to partial hepatectomy in living liver donors. 4D Flow MRI was performed on three donors before and afte...

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Vydané v:Computer methods in biomechanics and biomedical engineering. Ročník 6; číslo 5; s. 545 - 555
Hlavní autori: Rutkowski, David R., Reeder, Scott B., Fernandez, Luis A., Roldán-Alzate, Alejandro
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England Taylor & Francis 03.09.2018
Predmet:
4D flow MRI
computational fluid dynamics
living donor liver transplantation
Portal hemodynamics
virtual surgery
Portal hemodynamics
4D Flow MRI
Computational Fluid Dynamics
Living Donor Liver Transplantation
Virtual Surgery
ISSN:2168-1163, 2168-1171
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Shrnutí:This study used magnetic resonance imaging (MRI), computational fluid dynamics (CFD) modelling and in vitro experiments to predict patient-specific alterations in hepatic hemodynamics in response to partial hepatectomy in living liver donors. 4D Flow MRI was performed on three donors before and after hepatectomy and models of the portal venous system were created. Virtual surgery was performed to simulate (1) surgical resection and (2) post-surgery vessel dilation. CFD simulations were conducted using in vivo flow data for boundary conditions. CFD results showed good agreement with in vivo data, and in vitro experimental values agreed well with imaging and simulation results. The post-surgery models predicted an increase in all measured hemodynamic parameters, and the dilated virtual surgery model predicted post-surgery conditions better than the model that only simulated resection. The methods used in this study have potential significant value for the surgical planning process for the liver and other vascular territories.
Bibliografia:ObjectType-Article-1
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ISSN:2168-1163
2168-1171
DOI:10.1080/21681163.2017.1278619