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Related Experiment Video

Updated: Jul 12, 2025

Rat Model of the Associating Liver Partition and Portal Vein Ligation for Staged Hepatectomy ALPPS Procedure
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Lumped parameter liver simulation to predict acute haemodynamic alterations following partial resections.

Jeffrey Tithof1, Timothy L Pruett2, Joseph Sushil Rao2,3

  • 1Department of Mechanical Engineering, University of Minnesota, 111 Church Street SE, Minneapolis, MN 55455, USA.

Journal of the Royal Society, Interface
|October 25, 2023
PubMed
Summary

This study introduces a computational model to predict blood flow changes in the liver after partial resection. The model aids surgeons in making better decisions for liver transplantation and tumor removal, potentially preventing liver failure.

Keywords:
haemodynamicshepatic blood flowliver resectionlumped parameter model

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Area of Science:

  • Computational modeling
  • Hepatobiliary surgery
  • Medical imaging analysis

Background:

  • Partial liver resections are common in liver transplantation and cancer surgery.
  • Current pre-operative assessments using imaging do not fully predict post-resection hemodynamic changes.
  • Altered blood flow and shear stress after surgery can lead to complications like small for size syndrome.

Purpose of the Study:

  • To develop a mathematical model simulating liver perfusion alterations after partial resection.
  • To provide a tool for predicting hemodynamic changes and assisting surgical planning.
  • To quantify changes in flow rate, speed, and wall shear stress.

Main Methods:

  • Developed a lumped parameter mathematical model of human liver vasculature.
  • Incorporated realistic heterogeneities and parametrized it with clinical measurements.
  • Simulated acute perfusion changes following various liver resection scenarios.

Main Results:

  • The model accurately captures established liver perfusion characteristics with a single free parameter.
  • Quantified acute changes in volume flow rate, flow speed, and wall shear stress post-resection.
  • Demonstrated the model runs in minutes and can be adapted to patient-specific anatomy.

Conclusions:

  • The developed computational tool can assist in pre- and intra-operative decision-making for liver resections.
  • Predicting hemodynamic alterations is crucial for optimizing surgical outcomes and preventing complications.
  • This model offers a novel approach to enhance surgical planning for liver procedures.