Anatomically based simulation of hepatic perfusion in the human liver

Ma, Renfei; Hunter, Peter; Cousins, Will; Ho, Harvey; Bartlett, Adam; Safaei, Soroush

doi:10.1002/cnm.3229

Cited by 18 publications

(35 citation statements)

References 52 publications

(120 reference statements)

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“…The details of imaging data, digitizing procedure, and major geometrical parameters of the hepatic artery were presented in our previous work. 23 Although the preoperative arterial results will be briefly reported in this study, it should be kept in mind that the main focus of this study is the postoperative hepatic arterial flow. In Figure 3, ST is also shown in the schematic, and more details are presented in Section 2.3.2.…”

Section: Left Hepatectomymentioning

confidence: 99%

“…In summary, the minimum postoperative radius of the ST for the hepatic artery BCs increases from 7.5 × 10 −6 m (as used in Ma et al 30 to model the preoperative hepatic arterial flow) to 8.5 × 10 −6 m, lying in the size range of the hepatic arterioles, ie, 15 to 35 m in diameter 37 in liver lobules. Other parameters and properties of the ST remain the same.…”

Section: Vessel Size Variation In Postoperative Stsmentioning

confidence: 99%

“…In the literature, various outflow boundary conditions for one-dimensional (1-D) models were used. The popular ones mainly includes (a) prescribing outflow pressure; (b) using electrical circuit model analogy, such as pure resistor model 19 and Windkessel models, 13,20 among which three-element Windkessel model is the most typical one; and (c) structured tree (ST)-based impedance, [21][22][23] as used in this study. Other boundary conditions were also reported; eg, Aramburu et al 24 developed a tissue-perfusion-based boundary condition to investigate the hepatic arterial flow in healthy subjects and cancer patient.…”

Section: Introductionmentioning

confidence: 99%

“…As a step further to our previous work, 23 which presented the preoperative hepatic hemodynamics of a healthy liver donor, four scenarios ST-based outflow BCs are employed in this study to investigate the postoperative hepatic hemodynamics in the liver. The main idea is to employ two different methods to obtain the postoperative outflow impedance: (a) using the resistive index (RI) to obtain a coefficient, which relates the postoperative impedance to the preoperative impedance, and (b) using new STs to obtain the postoperative impedance.…”

Section: Introductionmentioning

confidence: 99%

“…In summary, on the basis of our previous work of modeling the preoperative hepatic hemodynamics, 23 the purpose of this study is to investigate the postoperative hepatic arterial flow of the subject in Ma et al 23 after left hepatectomy. In order to construct appropriate outflow boundary condition (BC) that is capable of capturing the postoperative hepatic haemodynamics, the RI is novelly adopted to obtain a coefficient, which shows the potential to efficiently relate the postoperative impedance to the preoperative status shown in Ma et al 23 Besides, since compliant arterial vascular bed can enlarge its size to accommodate extra flow, the size variation of STs is also considered in this study to explore the postoperative impedance.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the hepatic arterial flow in living liver donor after left hepatectomy and postoperative boundary condition exploration

Hunter

Cousins³

et al. 2019

Numer Methods Biomed Eng

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Preoperative and postoperative hepatic perfusion is modeled with one‐dimensional (1‐D) Navier‐Stokes equations. Flow rates obtained from ultrasound (US) data and impedance resulted from structured trees are the inflow and outflow boundary condition (BC), respectively. Structured trees terminate at the size of the arterioles, which can enlarge their size after hepatectomy. In clinical studies, the resistance to pulsatile arterial flow caused by the microvascular bed can be reflected by the resistive index (RI), a frequently used index in assessing arterial resistance. This study uses the RI in a novel manner to conveniently obtain the postoperative outflow impedance from the preoperative impedance. The major emphasis of this study is to devise a model to capture the postoperative hepatic hemodynamics after left hepatectomy. To study this, we build a hepatic network model and analyze its behavior under four different outflow impedance: (a) the same as preoperative impedance; (b) evaluated using the RI and preoperative impedance; (c) computed from structured tree BC with increased radius of terminal vessels; and (d) evaluated using structured tree with both increased radius of root vessel, ie, the outlets of the postoperative hepatic artery, and increased radius of terminal vessels. Our results show that both impedance from (b) and (d) give a physiologically reasonable postoperative hepatic pressure range, while the RI in (b) allows for a fast approximation of postoperative impedance. Since hemodynamics after hepatectomy are not fully understood, the methods used in this study to explore postoperative outflow BC are informative for future models exploring hemodynamic effects of partial hepatectomy.

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Section: Left Hepatectomymentioning

confidence: 99%

Section: Vessel Size Variation In Postoperative Stsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling the hepatic arterial flow in living liver donor after left hepatectomy and postoperative boundary condition exploration

Hunter

Cousins³

et al. 2019

Numer Methods Biomed Eng

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A highly parallel simulation of patient‐specific hepatic flows

Lin

Chen

Gao

et al. 2021

Numer Methods Biomed Eng

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Computational hemodynamics is being developed as an alternative approach for assisting clinical diagnosis and treatment planning for liver diseases. The technology is non‐invasive, but the computational time could be high when the full geometry of the blood vessels is taken into account. Existing approaches use either one‐dimensional model of the artery or simplified three‐dimensional tubular geometry in order to reduce the computational time, but the accuracy is sometime compromised, for example, when simulating blood flows in arteries with plaque. In this work, we study a highly parallel method for the transient incompressible Navier–Stokes equations for the simulation of the blood flows in the full three‐dimensional patient‐specific hepatic artery, portal vein and hepatic vein. As applications, we also simulate the flow in a patient with hepatectomy and calculate the S (PPG). One of the advantages of simulating blood flows in all hepatic vessels is that it provides a direct estimate of the PPG, which is a gold standard value to assess the portal hypertension. Moreover, the robustness and scalability of the algorithm are also investigated. A 83% parallel efficiency is achieved for solving a problem with 7 million elements on a supercomputer with more than 1000 processor cores.

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Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials

et al. 2022

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Purpose Virtual (in silico) imaging trials (VITs), involving computerized phantoms and models of the imaging process, provide a modern alternative to clinical imaging trials. VITs are faster, safer, and enable otherwise‐impossible investigations. Current phantoms used in VITs are limited in their ability to model functional behavior such as contrast perfusion which is an important determinant of dose and image quality in CT imaging. In our prior work with the XCAT computational phantoms, we determined and modeled inter‐organ (organ to organ) intravenous contrast concentration as a function of time from injection. However, intra‐organ concentration, heterogeneous distribution within a given organ, was not pursued. We extend our methods in this work to model intra‐organ concentration within the XCAT phantom with a specific focus on the liver. Methods Intra‐organ contrast perfusion depends on the organ's vessel network. We modeled the intricate vascular structures of the liver, informed by empirical and theoretical observations of anatomy and physiology. The developed vessel generation algorithm modeled a dual‐input‐single‐output vascular network as a series of bifurcating surfaces to optimally deliver flow within the bounding surface of a given XCAT liver. Using this network, contrast perfusion was simulated within voxelized versions of the phantom by using knowledge of the blood velocities in each vascular structure, vessel diameters and length, and the time since the contrast entered the hepatic artery. The utility of the enhanced phantom was demonstrated through a simulation study with the phantom voxelized prior to CT simulation with the relevant liver vasculature prepared to represent blood and iodinated contrast media. The spatial extent of the blood–contrast mixture was compared to clinical data. Results The vascular structures of the liver were generated with size and orientation which resulted in minimal energy expenditure required to maintain blood flow. Intravenous contrast was simulated as having known concentration and known total volume in the liver as calibrated from time–concentration curves. Measurements of simulated CT ROIs were found to agree with clinically observed values of early arterial phase contrast enhancement of the parenchyma (∼5$ \sim 5$ HU). Similarly, early enhancement in the hepatic artery was found to agree with average clinical enhancement false(180$(180$ HU). Conclusions The computational methods presented here furthered the development of the XCAT phantoms allowing for multi‐timepoint contrast perfusion simulations, enabling more anthropomorphic virtual clinical trials intended for optimization of current clinical imaging technologies and applications.

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Anatomically based simulation of hepatic perfusion in the human liver

Cited by 18 publications

References 52 publications

Modeling the hepatic arterial flow in living liver donor after left hepatectomy and postoperative boundary condition exploration

Modeling the hepatic arterial flow in living liver donor after left hepatectomy and postoperative boundary condition exploration

A highly parallel simulation of patient‐specific hepatic flows

Anatomically and physiologically informed computational model of hepatic contrast perfusion for virtual imaging trials

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