A Reanalysis of Experimental Brain Strain Data: Implication for Finite Element Head Model Validation

Abstract

Relative motion between the brain and skull and brain deformation are biomechanics aspects associated with many types of traumatic brain injury (TBI). Thus far, there is only one experimental endeavor reported brain strain under loading conditions commensurate with levels that were capable of producing injury. Most of the existing finite element (FE) head models are validated against brain-skull relative motion and then used for TBI prediction based on strain metrics. However, the suitability of using a model validated against brain-skull relative motion for strain prediction remains to be determined. To partially address the deficiency of experimental brain deformation data, this study revisits the only existing dynamic experimental brain strain data and updates the original calculations, which reflect incremental strain changes. The brain strain is recomputed by imposing the measured motion of neutral density target (NDT) to the NDT triad model. The revised brain strain and the brain-skull relative motion data are then used to test the hypothesis that an FE head model validated against brainskull relative motion does not guarantee its accuracy in terms of brain strain prediction. To this end, responses of brain strain and brain-skull relative motion of a previously developed FE head model (Kleiven, 2007) are compared with available experimental data. CORrelation and Analysis (CORA) and Normalized Integral Square Error (NISE) are employed to evaluate model validation performance for both brain strain and brain-skull relative motion. Correlation analyses (Pearson coefficient) are conducted between average cluster peak strain and average cluster peak brain-skull relative motion, and also between brain strain validation scores and brain-skull relative motion validation scores. The results show no significant correlations, neither between experimentally acquired peaks nor between computationally determined validation scores. These findings indicate that a head model validated against brain-skull relative motion may not be sufficient to assure its strain prediction accuracy. It is suggested that a FE head model with intended use for strain prediction should be validated against the experimental brain deformation data and not just the brain-skull relative motion.

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

“…Regarding experimental brain strain data used for model validation, the cluster brain strain presented in Zhou et al (2019b) is used, which is recalculated based on the original brain-skull relative motion experimental data from Hardy et al (2007) using a tetra approach instead of a triad approach used in the original study (Hardy et al 2007). Though it's well recognized (Zou et al 2007;Zhao and Ji 2020) and recently has been extensively verified (Zhou et al 2019b(Zhou et al , 2018) that a model validated against brain-skull relative motion may not necessarily guarantee its strain prediction accuracy. Therefore, it's suggested that a head model with the intended use for strain prediction should be validated against experimental brain strain data.…”

Biomechanics of Periventricular Injury

“…Details regarding numerical replicating the validating experiments are available in the study by Zhou and colleagues. 69 Validation results are plotted in Appendix 2 Figures 1-3…”

An anatomically accurate and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

“…Regarding experimental b rain strain data used for model validation, the cluster brain strain presented in Zhou et al (2019b) is used, which is recalculated based on the original brain-skull relative motion experimental data from Hardy et al (2007) using a tetra approach instead of a triad approach used in the original study (Hardy et al 2007). Though it's well recognized (Zou et al 2007;Zhao and Ji 2020) and recently has been extensively verified (Zhou et al 2019b;Zhou et al 2018) that a model validated against brain-skull relative motion may not necessarily guarantee its strain prediction accuracy. Therefore, it's suggested that a head model with an intended use for strain prediction should be validated against experimental brain strain data.…”

“…Note the tetra or triad approach is just one of another way to estimate brain strain from NDT motion, alternative approach has been proposed also, e.g., a generalized marker-based strain sampling approach to estimate and compare regional strains (Zhao and Ji 2020). Indeed, experimental brain strain data calculated by the tetra approach are much larger than by the triad approach, indicating the original triad strains (Hardy et al 2007), also the reanalyzed triad strains (Zhou et al 2018) largely underestimated the experimental brain strain. Thus, the experimental brain strain data calculated by the triad approach is not recommended to be used for head model validation due to its large underestimation of the real brain strain in the experiment.…”

“…The recalculated experimental cluster brain strain data is a result of the two-step efforts (Zhou et al 2018, Zhou et al 2019b attempted to best utilize the NDT motions close to or at injury level originally measured by Hardy et al (2007). The recalculated experimental cluster brain strain data provides a possibility to evaluate head models' brain strain prediction capacity; however, there are challenges, as mentioned above, that need integrated effort among the research community to allow its proper use for head model validation.…”