On the Sensitivity Analysis of Porous Finite Element Models for Cerebral Perfusion Estimation
Journal
Annals of Biomedical Engineering
Journal Volume
49
Journal Issue
12
Pages
3647-3665
Date Issued
2021
Author(s)
Abstract
Computational physiological models are promising tools to enhance the design of clinical trials and to assist in decision making. Organ-scale haemodynamic models are gaining popularity to evaluate perfusion in a virtual environment both in healthy and diseased patients. Recently, the principles of verification, validation, and uncertainty quantification of such physiological models have been laid down to ensure safe applications of engineering software in the medical device industry. The present study sets out to establish guidelines for the usage of a three-dimensional steady state porous cerebral perfusion model of the human brain following principles detailed in the verification and validation (V&V 40) standard of the American Society of Mechanical Engineers. The model relies on the finite element method and has been developed specifically to estimate how brain perfusion is altered in ischaemic stroke patients before, during, and after treatments. Simulations are compared with exact analytical solutions and a thorough sensitivity analysis is presented covering every numerical and physiological model parameter. The results suggest that such porous models can approximate blood pressure and perfusion distributions reliably even on a coarse grid with first order elements. On the other hand, higher order elements are essential to mitigate errors in volumetric blood flow rate estimation through cortical surface regions. Matching the volumetric flow rate corresponding to major cerebral arteries is identified as a validation milestone. It is found that inlet velocity boundary conditions are hard to obtain and that constant pressure inlet boundary conditions are feasible alternatives. A one-dimensional model is presented which can serve as a computationally inexpensive replacement of the three-dimensional brain model to ease parameter optimisation, sensitivity analyses and uncertainty quantification. The findings of the present study can be generalised to organ-scale porous perfusion models. The results increase the applicability of computational tools regarding treatment development for stroke and other cerebrovascular conditions. ? 2021, The Author(s).
Subjects
Finite element method
In silico trial
Ischaemic stroke
Organ-scale perfusion modelling
Porous brain model
Application programs
Blood
Blood pressure
Blood vessels
Boundary conditions
Brain
Decision making
Hemodynamics
Physiological models
Sensitivity analysis
Uncertainty analysis
Verification
Virtual reality
Cerebral perfusion
Finite element modelling (FEM)
In-silico
Ischemic strokes
Organ-scale perfusion modeling
Perfusion estimation
Perfusion models
Uncertainty quantifications
SDGs
Type
journal article