Modelling pipeline for subject‐specific arterial blood flow—A review

Abstract

SUMMARYIn this paper, a robust and semi-automatic modelling pipeline for blood flow through subject-specific arterial geometries is presented. The framework developed consists of image segmentation, domain discretization (meshing) and fluid dynamics. All the three subtopics of the pipeline are explained using an example of flow through a severely stenosed human carotid artery. In the Introduction, the state-of-the-art of both image segmentation and meshing is presented in some detail, and wherever possible the advantages and disadvantages of the existing methods are analysed. Followed by this, the deformable model used for image segmentation is presented. This model is based upon a geometrical potential force (GPF), which is a function of the image. Both the GPF calculation and level set determination are explained. Following the image segmentation method, a semi-automatic meshing method used in the present study is explained in full detail. All the relevant techniques required to generate a valid domain discretization are presented. These techniques include generating a valid surface mesh, skeletonization, mesh cropping, boundary layer mesh construction and various mesh cosmetic methods that are essential for generating a high-quality domain discretization. After presenting the mesh generation procedure, how to generate flow boundary conditions for both the inlets and outlets of a geometry is explained in detail. This is followed by a brief note on the flow solver, before studying the blood flow through the carotid artery with a severe stenosis.

Chaotic flow in an aortic aneurysm

“…This approach finds justification in the literature on biological flows. 18,19 The particle trajectories and velocities during oscillatory flow within the bulge, computed as well as recorded are compared. The flow statistics were seen to converge with ten cycles of oscillation.…”

Image Segmentation for Cardiovascular Biomedical Applications at Different Scales

“…Individualized numerical simulations of physiological processes in the human body received a great deal of attention over several decades, and a vast number of models have been described in the literature. Contemporary resolution of medical images and new algorithms for their post-processing allow us to develop high resolution numerical models of various processes at cellular-, organ-, and whole organism-levels [1][2][3][4][5]. Given an imaging dataset, one performs image segmentation, volume reconstruction, and numerical discretization.…”

“…The bidomain electrophysiology simulation requires the detailed model of the heart ventricles and atria. Whole body haemodynamics modeling requires the full blood vessel network [3,4,14]. Local haemodynamics modeling requires the patient-specific local reconstruction of coronary and cerebral arteries [15,16].…”

New software developments for quality mesh generation and optimization from biomedical imaging data

“…One of the challenges in using the FEM, however, is to generate high-quality meshes on which the simulations are performed. In order to obtain more accurate simulation results, it is also practically important to incorporate realistic biological structures into geometric mesh models [11, 14, 29, 48, 49, 56]. To this end, the goal of the present paper is to construct high-quality geometric mesh models from 3D biomedical imaging data.…”