Abstract
Clinically significant portal hypertension (CSPH) is a severe complication of chronic liver disease associated with cirrhosis, which is diagnosed by the measurement of hepatic venous pressure gradient (HVPG). However, HVPG measurement is invasive and therefore difficult to be widely applied in clinical routines. There is no currently available technique to measure HVPG noninvasively. Computational fluid dynamics (CFD) has been used for noninvasive measurement of vascular pressure gradient in the intracranial and coronary arteries. However, it has been scarcely employed in the hepatic vessel system due to the difficulties in reconstructing precise vascular anatomies and setting appropriate boundary conditions. Several computer tomography and ultrasound based studies have verified the effectiveness of virtual HVPG (vHVPG) by directly connecting the portal veins and hepatic veins before CFD simulations [12, 16]. We apply the latest techniques of phase-contrast magnetic resonance imaging (PC-MRI) and DIXON to obtain the velocity and vessel anatomies at the same time. Besides, we improve the CFD pipeline in regards to the construction of vessel connections and reduction of calculation time. The proposed method shows high accuracy in the CSPH diagnosis in a study containing ten healthy volunteers and five patients. The MRI-based noninvasive HVPG measurement is promising in the clinical application of CSPH diagnosis.
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Acknowledgements
This study was funded by the National Natural Science Foundation of China (No. 81971583, No. 62001120), National Key R&D Program of China (No. 2018YFC1312900, No. 2019YFA0709502), Shanghai Natural Science Foundation (No. 20ZR1406400), Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01, No. 2018SHZDZX01), Shanghai Municipal Science and Technology (No. 17411953600), Shanghai Sailing Program (No. 20YF1402400), ZJLab and Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, China.
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Wang, K., Wang, S., Xiong, M., Wang, C., Wang, H. (2021). Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics. In: de Bruijne, M., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021. MICCAI 2021. Lecture Notes in Computer Science(), vol 12907. Springer, Cham. https://doi.org/10.1007/978-3-030-87234-2_4
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