Numerical simulation of liver perfusion: from CT scans to FE model

TL;DR

This paper presents a Python-based framework for simulating liver perfusion by generating finite element meshes and vascular structures from CT scans, enabling detailed analysis of blood flow and contrast transport in the liver.

Contribution

It introduces a semi-automatic pipeline for creating FE models of the liver from CT data, including artificial vascular tree generation when real data is incomplete.

Findings

Successful simulation of pressure distribution in the liver

Effective reconstruction of vascular structures from CT scans

Validation of contrast transport modeling in liver tissue

Abstract

We use a collection of Python programs for numerical simulation of liver perfusion. We have an application for semi-automatic generation of a finite element mesh of the human liver from computed tomography scans and for reconstruction of the liver vascular structure. When the real vascular trees can not be obtained from the CT data we generate artificial trees using the constructive optimization method. The generated FE mesh and vascular trees are imported into SfePy (Simple Finite Elements in Python) and numerical simulations are performed in order to get the pressure distribution and perfusion flows in the liver tissue. In the post-processing steps we calculate transport of a contrast fluid through the liver parenchyma.