0
Research Papers

A Multilevel Modeling Framework to Study Hepatic Perfusion Characteristics in Case of Liver Cirrhosis

[+] Author and Article Information
Geert Peeters, Charlotte Debbaut, Patrick Segers

IBiTech – bioMMeda,
Department of Electronics and
Information Systems,
iMinds Medical IT Department,
Ghent University,
De Pintelaan 185 – Block B,
Gent 9000, Belgium
e-mail: geert.peeters@ugent.be

Pieter Cornillie

Department of Morphology,
Faculty of Veterinary Medicine,
Ghent University,
Salisburylaan 133,
Merelbeke 9820, Belgium

Thomas De Schryver

Centre for X-Ray Tomography,
Department of Physics and Astronomy,
Ghent University,
Proeftuinstraat 86,
Gent 9000, Belgium

Diethard Monbaliu

Department of Microbiology and Immunology,
Abdominal Transplant Surgery,
University Hospitals Leuven,
KU Leuven, Herestraat 49,
Leuven 3000, Belgium

Wim Laleman

Department of Liver and
Biliopancreatic Disorders,
Hepatology,
University Hospitals Leuven,
KU Leuven, Herestraat 49,
Leuven 3000, Belgium

Manuscript received September 24, 2014; final manuscript received November 28, 2014; published online March 10, 2015. Assoc. Editor: Tim David.

J Biomech Eng 137(5), 051007 (May 01, 2015) (9 pages) Paper No: BIO-14-1475; doi: 10.1115/1.4029280 History: Received September 24, 2014; Revised November 28, 2014; Online March 10, 2015

Liver cirrhosis represents the end-stage of different liver disorders, progressively affecting hepatic architecture, hemodynamics, and function. Morphologically, cirrhosis is characterized by diffuse fibrosis, the conversion of normal liver architecture into structurally abnormal regenerative nodules and the formation of an abundant vascular network. To date, the vascular remodeling and altered hemodynamics due to cirrhosis are still poorly understood, even though they seem to play a pivotal role in cirrhogenesis. This study aims to determine the perfusion characteristics of the cirrhotic circulation using a multilevel modeling approach including computational fluid dynamics (CFD) simulations. Vascular corrosion casting and multilevel micro-CT imaging of a single human cirrhotic liver generated detailed datasets of the hepatic circulation, including typical pathological characteristics of cirrhosis such as shunt vessels and dilated sinusoids. Image processing resulted in anatomically correct 3D reconstructions of the microvasculature up to a diameter of about 500 μm. Subsequently, two cubic samples (150 × 150 × 150 μm3) were virtually dissected from vascularized zones in between regenerative nodules and applied for CFD simulations to study the altered cirrhotic microperfusion and permeability. Additionally, a conceptual 3D model of the cirrhotic macrocirculation was developed to reveal the hemodynamic impact of regenerative nodules. Our results illustrate that the cirrhotic microcirculation is characterized by an anisotropic permeability showing the highest value in the direction parallel to the central vein (kd,zz = 1.68 × 10−13 m2 and kd,zz = 7.79 × 10−13 m2 for sample 1 and 2, respectively) and lower values in the circumferential (kd,ϑϑ = 5.78 × 10−14 m2 and kd,ϑϑ = 5.65 × 10−13 m2 for sample 1 and 2, respectively) and radial (kd,rr = 9.87 × 10−14 m2 and kd,rr = 5.13 × 10−13 m2 for sample 1 and 2, respectively) direction. Overall, the observed permeabilities are markedly higher compared to a normal liver, implying a locally decreased intrahepatic vascular resistance (IVR) probably due to local compensation mechanisms (dilated sinusoids and shunt vessels). These counteract the IVR increase caused by the presence of regenerative nodules and dynamic contraction mechanisms (e.g., stellate cells, NO-concentration, etc.). Our conceptual 3D model of the cirrhotic macrocirculation indicates that regenerative nodules severely increase the IVR beyond about 65 vol. % of regenerative nodules. Numerical modeling allows quantifying perfusion characteristics of the cirrhotic macro- and microcirculation, i.e., the effect of regenerative nodules and compensation mechanisms such as dilated sinusoids and shunt vessels. Future research will focus on the development of models to study time-dependent degenerative adaptation of the cirrhotic macro- and microcirculation.

FIGURES IN THIS ARTICLE
<>
Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Cirrhotic liver (a) and the corresponding vascular corrosion cast (b). Smaller samples were dissected from the cast (see ellipse) to analyze the microcirculation.

Grahic Jump Location
Fig. 5

Macrocirculation model of liver cirrhosis: (a) conceptual 3D model of the cirrhotic macrocirculation; A1/2 and l1/2 represent the branch's area and length for the first and second vessel generation, respectively. The indicated dimensions are shown in millimeter (mm). (b) Simplified electrical analog model of a healthy liver [28].

Grahic Jump Location
Fig. 4

Fluid domain in r-direction for sample 1: (a) and sample 2 (b). Inflow and outflow guidance boxes were added to facilitate solution convergence. The surface mesh density of both samples is displayed in the smaller frames. The arrows indicate the flow direction (from top to bottom). The lateral boundaries were defined as symmetry planes.

Grahic Jump Location
Fig. 3

3D reconstructions of dissected samples of the cirrhotic microvasculature based on micro-CT images: (a) sample 1 (resolution of 1.9 μm) containing seemingly unaffected sinusoids and (b) sample 2 (resolution of 1.7 μm) displaying abnormal shunt vessels (dashed circles)

Grahic Jump Location
Fig. 2

Microscopic analysis of the cirrhotic angioarchitecture: SEM image of enlarged, irregularly shaped intrahepatic vessels, most likely representing shunt vessels: ((a)—dashed circle causing blood flow to bypass hepatocytes, and an abnormal and bumpy blood vessel wall; ((b)—dashed circle). Microscopic images: ((c)—left and top right) and a SEM image ((c)—bottom right) show ellipsoidal holes which become visible after the maceration of the tissue in regenerative nodules, illustrating the compressed walls.

Grahic Jump Location
Fig. 8

Pressure distribution and velocity streamlines of a section through (a) the sinusoidal region of a normal liver and (b) the nodular region of a cirrhotic liver (simulation of severe cirrhosis with a nodular vol. % of 81.2%)

Grahic Jump Location
Fig. 9

Results of the conceptual macrocirculation model. The pressure difference over the nodular region (a) increases and the flows through the vascular trees (b) decrease as a consequence of the regenerative nodules. Hence, the vascular resistance over the nodular region (c) increases due to regenerative nodules.

Grahic Jump Location
Fig. 6

CFD models of cirrhotic sample 1 in the r direction: (a) static pressure distribution on the sinusoidal walls. (b) Visualization of the preferential pathways through the geometry. The streamlines are colored according to the local flow velocities. (c) The spatial distribution of wall shear stress along the sinusoidal walls. Wall shear stresses remained mostly under 1 Pa.

Grahic Jump Location
Fig. 7

CFD models of cirrhotic sample 2 in the r direction: (a) static pressure distribution on the sinusoidal walls. (b) Visualization of the preferential pathways through the geometry. The streamlines are colored according to the local flow velocities. (c) The spatial distribution of wall shear stress along the sinusoidal walls. Wall shear stresses remained mostly under 1 Pa.

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In