Global sensitivity analysis of hepatic venous pressure gradient (HVPG) measurement with a stochastic computational model of the hepatic circulation

Wang, Tianqi; Liang, Fuyou; Zhou, Zun-Qiang; Qi, Xiaolong

doi:10.1016/j.compbiomed.2018.04.017

Cited by 33 publications

(16 citation statements)

References 55 publications

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“…Second, the integration of the perfusion models for all hepatic vascular vessels allows obtaining the portal pressure gradient (PPG), which is the pressure gradient between the portal vein and the inferior vena cava (IVC). The PPG has been employed as a gold standard for evaluating the reliability of measured hepatic venous pressure gradient (HVPG) as an indirect measure of pressure in portal vein . Finally, the hepatic haemodynamics are modelled in an anatomically based geometry with vessels up to six generations, which are sufficient for analysing the liver classifications, eg, Couinaud classification.…”

Section: Introductionmentioning

confidence: 99%

“…The PPG has been employed as a gold standard for evaluating the reliability of measured hepatic venous pressure gradient (HVPG) as an indirect measure of pressure in portal vein. 31,32 Finally, the hepatic haemodynamics are modelled in an anatomically based geometry with vessels up to six generations, which are sufficient for analysing the liver classifications, eg, Couinaud classification. Therefore, this model has the potential to integrate the physiology into current liver classifications in the literature, 33,34 which have been employed in hepatic surgical planning, however, are only based on liver anatomy.…”

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confidence: 99%

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Anatomically based simulation of hepatic perfusion in the human liver

Hunter

Cousins³

et al. 2019

Numer Methods Biomed Eng

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Liver structures of a healthy subject are digitised and segmented from computed tomography (CT) images, and hepatic perfusion is modelled in the hepatic artery and portal vein of the healthy subject with structured tree‐based outflow boundary conditions. This self‐similar structured tree is widely used in the literature, eg, blood flow simulation in larger systemic arteries and cerebral circulation, and is used in this study to model the effect of the smaller hepatic arteries and arterioles, as well as the smaller hepatic portal veins and portal venules. Physiologically reasonable results are obtained. Since the structured tree terminates at the size of the microvasculature system in liver lobules, the structured tree boundary condition will enable the proposed organ‐level model of hepatic arterial flow to be easily connected to tissue‐level models of liver lobules. Blood flow in the hepatic vein is also modelled in this subject with three‐element Windkessel model as outflow boundary conditions. The benefit of integrating the perfusion in all hepatic vascular vessels is that it helps us analyse some complicated clinical phenomenon more efficiently, eg, one possible application is to obtain the portal pressure gradient (PPG) to help examine the reliability of hepatic venous pressure gradient (HVPG) as an indirect measure of portal pressure. Moreover, since four to six generations of hepatic vessels, which are sufficient for liver classification analysis, were employed in the model, this study is setting the computational foundation of a potentially handy surgical tool.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Anatomically based simulation of hepatic perfusion in the human liver

Hunter

Cousins³

et al. 2019

Numer Methods Biomed Eng

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“…Kumar et al reported that an HPVG of 12 mm Hg is the cutoff value of variceal bleeding, whereas an FPP of 22 mm Hg or greater is the clinical cutoff value of gastroesophageal varices bleeding. In addition, HPVG is invasive, requires skillful administration, is expensive, and cannot be used for routine assessment and monitoring of chronic liver disease progression . Other indirect portal vein pressure measurement methods are not accurate, have multiple influence factors, and are not reliable .…”

Section: Discussionmentioning

confidence: 99%

Application of the Hepatic Transit Time (HTT) in Evaluation of Portal Vein Pressure in Gastroesophageal Varices Patients

Lin

Jiang

et al. 2019

J of Ultrasound Medicine

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Objectives-To analyze the clinical significance of using hepatic transit time (HTT) to evaluate portal vein pressure in gastroesophageal varices patients.Methods-For the observation group, we enrolled 50 gastroesophageal varices patients who had received esophagogastric variceal embolization in our hospital between January 2015 and February 2018. Patients without liver disease populated the control group and were recruited during the same time period. All patients underwent contrast-enhanced sonography. In the observation group, free portal pressure (FPP) was detected during esophagogastric variceal embolization with ultrasound guidance. Differences in hepatic artery-hepatic vein transit time (HA-HVTT), portal vein-hepatic vein transit time (PV-HVTT), and parenchyma-hepatic vein transit time (PA-HVTT) were compared between groups. Correlations between HA-HVTT, PV-HVTT, PA-HVTT, and FPP in the observation group were analyzed using the Pearson coefficient and linear regression analysis.Results-HA-HVTT (t = 5.078; P < .001), PV-HVTT (t = 12.163; P < .001), and PA-HVTT (t = 2.649; P = .009) within the observation group were significantly lower than those of the control group. The areas under the curve of HTT were 0.771 (HA-HVTT), 0.951 (PV-HVTT), and 0.652 (PA-HVTT), and the sensitivity and specificity of PV-HVTT at 7.99 seconds were 86.0% and 88.0%, respectively. The HA-HVTT (r = -0.799; P < .001), PV-HVTT (r = -0.554; P < .001), and PA-HVTT (r = -0.735; P < .001) negatively correlated to FPP in the observation group. Linear regression analysis showed y = -0.410x + 7.254 (HA-HVTT and FPP), y = -0.335x + 4.983 (PV-HVTT and FPP), and y = -0.566x + 4.997 (PA-HVTT and FPP) in the observation group.Conclusion-Compared with the control patients, the HTT of patients with portal hypertension-esophagogastric varices was significantly shorter, and showed an inverse relationship with FPP.Abbreviations AUC, area under the curve; FPP, free portal pressure; HA-HVTT, hepatic artery-hepatic vein transit time; HTT, hepatic transit time; HVPG, hepatic venous pressure gradient; PA-HVTT, parenchyma-hepatic vein transit time; PV-HVTT, portal vein-hepatic vein transit time; ROC, receiver operating characteristic

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“…In this study, the downstream vasculature of each outlet was modeled with a 3-element Windkessel-lumped parameter network (LPN) as shown in Figure 1 c. The LPN model at each outlet consisted of a proximal resistance ( R p ), compliance ( C ), and distal resistance ( R d ) that was connected to a distal pressure ( P d ) [ 27 ]. The distal pressure was assumed to be constant and determined from a separate closed LPN model of the total body [ 28 ], which was tuned using the patient’s heart rate, systolic and diastolic pressure (72 bpm, 80 mmHg and 110 mmHg, respectively). In all the simulations, P d was 15 mmHg.…”

Section: Methodsmentioning

confidence: 99%

Computational Modeling of the Liver Arterial Blood Flow for Microsphere Therapy: Effect of Boundary Conditions

et al. 2020

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Transarterial embolization is a minimally invasive treatment for advanced liver cancer using microspheres loaded with a chemotherapeutic drug or radioactive yttrium-90 (90Y) that are injected into the hepatic arterial tree through a catheter. For personalized treatment, the microsphere distribution in the liver should be optimized through the injection volume and location. Computational fluid dynamics (CFD) simulations of the blood flow in the hepatic artery can help estimate this distribution if carefully parameterized. An important aspect is the choice of the boundary conditions imposed at the inlet and outlets of the computational domain. In this study, the effect of boundary conditions on the hepatic arterial tree hemodynamics was investigated. The outlet boundary conditions were modeled with three-element Windkessel circuits, representative of the downstream vasculature resistance. Results demonstrated that the downstream vasculature resistance affected the hepatic artery hemodynamics such as the velocity field, the pressure field and the blood flow streamline trajectories. Moreover, the number of microspheres received by the tumor significantly changed (more than 10% of the total injected microspheres) with downstream resistance variations. These findings suggest that patient-specific boundary conditions should be used in order to achieve a more accurate drug distribution estimation with CFD in transarterial embolization treatment planning.

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Global sensitivity analysis of hepatic venous pressure gradient (HVPG) measurement with a stochastic computational model of the hepatic circulation

Cited by 33 publications

References 55 publications

Anatomically based simulation of hepatic perfusion in the human liver

Anatomically based simulation of hepatic perfusion in the human liver

Application of the Hepatic Transit Time (HTT) in Evaluation of Portal Vein Pressure in Gastroesophageal Varices Patients

Computational Modeling of the Liver Arterial Blood Flow for Microsphere Therapy: Effect of Boundary Conditions

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