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

Pinzani, M., Rosselli, M., and Zuckermann, M., 2011, “Liver Cirrhosis,” Best Pract. Res. Clin. Gastroenterol., 25(2), pp. 281–290. [CrossRef] [PubMed]
Thabut, D., and Shah, V., 2010, “Intrahepatic Angiogenesis and Sinusoidal Remodeling in Chronic Liver Disease: New Targets for the Treatment of Portal Hypertension?” J. Hepatol., 53(5), pp. 976–980. [CrossRef] [PubMed]
Desmet, V. J., and Roskams, T., 2004, “Cirrhosis Reversal: A Duel Between Dogma and Myth,” J. Hepatol., 40(5), pp. 860–867. [CrossRef] [PubMed]
Anthony, P. P., Ishak, K. G., Nayak, N. C., Poulsen, H. E., Scheuer, P. J., and Sobin, L. H., 1978, “The Morphology of Cirrhosis. Recommendations on Definition, Nomenclature, and Classification by a Working Group Sponsored by the World Health Organization,” J. Clin. Pathol., 31(5), pp. 395–414. [CrossRef] [PubMed]
Minami, Y., and Kudo, M., 2012, “HCC Risk Factors,” Biotargets of Cancer in Current Clinical Practice, Springer, New York, p. 273.
Ratib, S., West, J., Crooks, C. J., and Fleming, K. M., 2014, “Diagnosis of Liver Cirrhosis in England, a Cohort Study, 1998–2009: A Comparison With Cancer,” Am. J. Gastroenterol., 109(2), pp. 190–198. [CrossRef] [PubMed]
Tsochatzis, E. A., Bosch, J., and Burroughs, A. K., 2014, “Liver Cirrhosis,” Lancet, 383(9930), pp. 1749–1761. [CrossRef] [PubMed]
Pascher, A., Nebrig, M., and Neuhaus, P., 2013, “Irreversible Liver Failure: Treatment by Transplantation,” Dtsch. Arzteblatt Int., 110(10), pp. 167–173. [CrossRef]
Debbaut, C., Vierendeels, J., Casteleyn, C., Cornillie, P., Van Loo, D., Simoens, P., Van Hoorebeke, L., Monbaliu, D., and Segers, P., 2012, “Perfusion Characteristics of the Human Hepatic Microcirculation Based on Three-Dimensional Reconstructions and Computational Fluid Dynamic Analysis,” ASME J. Biomech. Eng., 134(1), p. 011003. [CrossRef]
Marieb, E. N., and Hoehn, K., 2007, Human Anatomy and Physiology, Pearson Education, Upper Saddle River, NJ.
Abdel-Misih, S. R., and Bloomston, M., 2010, “Liver Anatomy,” Surg. Clin. North Am., 90(4), pp. 643–653. [CrossRef] [PubMed]
Sherlock, S., and Dooley, J., 2008, Diseases of the Liver and Biliary System, Wiley, Hoboken, NJ.
Lee, U. E., and Friedman, S. L., 2011, “Mechanisms of Hepatic Fibrogenesis,” Best Pract. Res. Clin. Gastroenterol., 25(2), pp. 195–206. [CrossRef] [PubMed]
Huet, P. M., Goresky, C. A., Villeneuve, J. P., Marleau, D., and Lough, J. O., 1982, “Assessment of Liver Microcirculation in Human Cirrhosis,” J. Clin. Invest., 70(6), pp. 1234–1244. [CrossRef] [PubMed]
Villeneuve, J. P., Dagenais, M., Huet, P. M., Roy, A., Lapointe, R., and Marleau, D., 1996, “The Hepatic Microcirculation in the Isolated Perfused Human Liver,” Hepatology, 23(1), pp. 24–31. [CrossRef] [PubMed]
Vanheule, E., Geerts, A. M., Van Huysse, J., Schelfhout, D., Praet, M., Van Vlierberghe, H., De Vos, M., and Colle, I., 2008, “An Intravital Microscopic Study of the Hepatic Microcirculation in Cirrhotic Mice Models: Relationship Between Fibrosis and Angiogenesis,” Int. J. Exp. Pathol., 89(6), pp. 419–432. [CrossRef] [PubMed]
Varin, F., and Huet, P. M., 1985, “Hepatic Microcirculation in the Perfused Cirrhotic Rat Liver,” J. Clin. Invest., 76(5), pp. 1904–1912. [CrossRef] [PubMed]
Annet, L., Materne, R., Danse, E., Jamart, J., Horsmans, Y., and Van Beers, B. E., 2003, “Hepatic Flow Parameters Measured With MR Imaging and Doppler US: Correlations With Degree of Cirrhosis and Portal Hypertension,” Radiology, 229(2), pp. 409–414. [CrossRef] [PubMed]
Fischer, M. A., Donati, O. F., Reiner, C. S., Hunziker, R., Nanz, D., and Boss, A., 2012, “Feasibility of Semiquantitative Liver Perfusion Assessment by Ferucarbotran Bolus Injection in Double-Contrast Hepatic MRI,” J. Magn. Reson. Imaging, 36(1), pp. 168–176. [CrossRef] [PubMed]
Ma, G., Bai, R., Jiang, H., Hao, X., Ling, Z., and Li, K., 2013, “Assessment of Hemodynamics in a Rat Model of Liver Cirrhosis With Precancerous Lesions Using Multislice Spiral CT Perfusion Imaging,” BioMed Res. Int., 2013, p. 813174. [CrossRef]
Chen, M. L., Zeng, Q. Y., Huo, J. W., Yin, X. M., Li, B. P., and Liu, J. X., 2009, “Assessment of the Hepatic Microvascular Changes in Liver Cirrhosis by Perfusion Computed Tomography,” World J. Gastroenterol., 15(28), pp. 3532–3537. [CrossRef] [PubMed]
Ying, M., Leung, G., Lau, T. Y., Tipoe, G. L., Lee, E. S., Yuen, Q. W., Huang, Y. P., and Zheng, Y. P., 2012, “Evaluation of Liver Fibrosis by Investigation of Hepatic Parenchymal Perfusion Using Contrast-Enhanced Ultrasound: An Animal Study,” J. Clin. Ultrasound, 40(8), pp. 462–470. [CrossRef] [PubMed]
Ridolfi, F., Abbattista, T., Busilacchi, P., and Brunelli, E., 2012, “Contrast-Enhanced Ultrasound Evaluation of Hepatic Microvascular Changes in Liver Diseases,” World J. Gastroenterol., 18(37), pp. 5225–5230. [CrossRef] [PubMed]
Ho, C. M., Lin, R. K., Tsai, S. F., Hu, R. H., Liang, P. C., Sheu, T. W., and Lee, P. H., 2010, “Simulation of Portal Hemodynamic Changes in a Donor After Right Hepatectomy,” ASME J. Biomech. Eng., 132(4), p. 041002. [CrossRef]
Ho, C. M., Tsai, S. F., Lin, R. K., Liang, P. C., Sheu, T. W., Hu, R. H., and Lee, P. H., 2007, “Computer Simulation of Hemodynamic Changes After Right Lobectomy in a Liver With Intrahepatic Portal Vein Aneurysm,” J. Formosan Med. Assoc., 106(8), pp. 617–623. [CrossRef]
Ho, H., Sorrell, K., Bartlett, A., and Hunter, P., 2012, “Blood Flow Simulation for the Liver After a Virtual Right Lobe Hepatectomy,” Medical Image Computing and Computer-Assisted Intervention: MICCAI. International Conference on Medical Image Computing and Computer-Assisted Intervention, Nice, France, Oct. 1–Oct. 5, 15(Pt 3), pp. 525–532. [CrossRef] [PubMed]
Kennedy, A. S., Kleinstreuer, C., Basciano, C. A., and Dezarn, W. A., 2010, “Computer Modeling of Yttrium-90-Microsphere Transport in the Hepatic Arterial Tree to Improve Clinical Outcomes,” Int. J. Radiat. Oncol. Biol. Phys., 76(2), pp. 631–637. [CrossRef] [PubMed]
Debbaut, C., Monbaliu, D., Casteleyn, C., Cornillie, P., Van Loo, D., Masschaele, B., Pirenne, J., Simoens, P., Van Hoorebeke, L., and Segers, P., 2011, “From Vascular Corrosion Cast to Electrical Analog Model for the Study of Human Liver Hemodynamics and Perfusion,” IEEE Trans. Biomed. Eng., 58(1), pp. 25–35. [CrossRef] [PubMed]
Ho, H., Sorrell, K., Bartlett, A., and Hunter, P., 2013, “Modeling the Hepatic Arterial Buffer Response in the Liver,” Med. Eng. Phys., 35(8), pp. 1053–1058. [CrossRef] [PubMed]
Debbaut, C., De Wilde, D., Casteleyn, C., Cornillie, P., Van Loo, D., Van Hoorebeke, L., Monbaliu, D., Fan, Y. D., and Segers, P., 2012, “Modeling the Impact of Partial Hepatectomy on the Hepatic Hemodynamics Using a Rat Model,” IEEE Trans. Biomed. Eng., 59(12), pp. 3293–3303. [CrossRef] [PubMed]
Bonfiglio, A., Leungchavaphongse, K., Repetto, R., and Siggers, J. H., 2010, “Mathematical Modeling of the Circulation in the Liver Lobule,” ASME J. Biomech. Eng., 132(11), p. 111011. [CrossRef]
Siggers, J. H., Leungchavaphongse, K., Ho, C. H., and Repetto, R., 2013, “Mathematical Model of Blood and Interstitial Flow and Lymph Production in the Liver,” Biomech. Model. Mechanobiol., 13(2), pp. 363–378. [CrossRef] [PubMed]
Ricken, T., Dahmen, U., and Dirsch, O., 2010, “A Biphasic Model for Sinusoidal Liver Perfusion Remodeling After Outflow Obstruction,” Biomech. Model. Mechanobiol., 9(4), pp. 435–450. [CrossRef] [PubMed]
Rani, H. P., Sheu, T. W., Chang, T. M., and Liang, P. C., 2006, “Numerical Investigation of Non-Newtonian Microcirculatory Blood Flow in Hepatic Lobule,” J. Biomech., 39(3), pp. 551–563. [CrossRef] [PubMed]
Van Steenkiste, C., Trachet, B., Casteleyn, C., van Loo, D., Van Hoorebeke, L., Segers, P., Geerts, A., Van Vlierberghe, H., and Colle, I., 2010, “Vascular Corrosion Casting: Analyzing Wall Shear Stress in the Portal Vein and Vascular Abnormalities in Portal Hypertensive and Cirrhotic Rodents,” Lab. Invest., 90(11), pp. 1558–1572. [CrossRef] [PubMed]
Debbaut, C., Vierendeels, J., Siggers, J. H., Repetto, R., Monbaliu, D., and Segers, P., 2014, “A 3D Porous Media Liver Lobule Model: The Importance of Vascular Septa and Anisotropic Permeability for Homogeneous Perfusion,” Comput. Methods Biomech. Biomed. Eng., 17(12), pp. 1295–1310. [CrossRef]
Masschaele, B., Cnudde, V., Dierick, M., Jacobs, P., Van Hoorebeke, L., and Vlassenbroeck, J., 2007, “UGCT: New X-Ray Radiography and Tomography Facility,” Nucl. Instrum. Methods Phys. Res. Sect. A, 580(1), pp. 266–269. [CrossRef]
Debbaut, C., Segers, P., Cornillie, P., Casteleyn, C., Dierick, M., Laleman, W., and Monbaliu, D., 2014, “Analyzing the Human Liver Vascular Architecture by Combining Vascular Corrosion Casting and Micro-CT Scanning: A Feasibility Study,” J. Anat., 224(4), pp. 509–517. [CrossRef] [PubMed]
van der Plaats, A., t Hart, N. A., Verkerke, G. J., Leuvenink, H. G., Verdonck, P., Ploeg, R. J., and Rakhorst, G., 2004, “Numerical Simulation of the Hepatic Circulation,” Int. J. Artif. Organs, 27(3), pp. 222–230. [PubMed]
See the “ [CrossRef]” tab for this paper on the ASME Digital Collection.
Debbaut, C., Monbaliu, D., and Segers, P., 2013, “Hydraulic Input Impedances as a Tool to Capture Liver Graft Perfusion Properties,” Proceedings of the 12th Belgian National Day on Biomedical Engineering, Brussels.
Goldsmith, H. L., Cokelet, G. R., and Gaehtgens, P., 1989, “Robin Fahraeus: Evolution of His Concepts in Cardiovascular Physiology,” Am. J. Physiol., 257(3 Pt 2), pp. H1005–1015. [PubMed]
Debbaut, C., 2013, Multi-Level Modelling of Hepatic Perfusion in Support of Liver Transplantation Strategies, Ghent University, Gent, Belgium.
Laleman, W., Vander Elst, I., Zeegers, M., Servaes, R., Libbrecht, L., Roskams, T., Fevery, J., and Nevens, F., 2006, “A Stable Model of Cirrhotic Portal Hypertension in the Rat: Thioacetamide Revisited,” Eur. J. Clin. Invest., 36(4), pp. 242–249. [CrossRef] [PubMed]

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. 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. 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. 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. 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. 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.

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.

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