Full-field, frequency-domain comparison of simulated and measured human brain deformation

TL;DR

This paper introduces a framework to compare simulated and measured brain deformation during skull motion, helping improve models of brain biomechanics.

Contribution

A novel framework for comparing simulated and measured strain fields in the human brain using nonlinear registration and strain field correlations.

Findings

Global strain field correlations between different human subjects are higher than between models and subjects.

Nonlinear registration to a standard brain atlas enables accurate comparison of strain fields from models and experiments.

Abstract

We propose a robust framework for quantitatively comparing model-predicted and experimentally measured strain fields in the human brain during harmonic skull motion. Traumatic brain injuries (TBIs) are typically caused by skull impact or acceleration, but how skull motion leads to brain deformation and consequent neural injury remains unclear and comparison of model predictions to experimental data remains limited. Magnetic resonance elastography (MRE) provides high-resolution, full-field measurements of dynamic brain deformation induced by harmonic skull motion. In the proposed framework, full-field strain measurements from human brain MRE in vivo are compared to simulated strain fields from models with similar harmonic loading. To enable comparison, the model geometry and subject anatomy, and subsequently, the predicted and measured strain fields are nonlinearly registered to the same standard brain atlas. Strain field correlations (\(\:{C}_{v}\)), both global (over the brain volume) and local (over smaller sub-volumes), are then computed from the inner product of the complex-valued strain tensors from model and experiment at each voxel. To demonstrate our approach, we compare strain fields from MRE in six human subjects to predictions from two previously developed models. Notably, global \(\:{C}_{v}\) values are higher when comparing strain fields from different subjects (\(\:{C}_{v}\)~0.6–0.7) than when comparing strain fields from either of the two models to strain fields in any subject. The proposed framework provides a quantitative method to assess similarity (and to identify discrepancies) between model predictions and experimental measurements of brain deformation, and thus can aid in the development and evaluation of improved models of brain biomechanics.