title: Anisotropic finite element models for brain injury prediction: the sensitivity of axonal strain to white matter tract inter-subject variability.
abstract: Computational models incorporating anisotropic features of brain tissue have become a valuable tool for studying the occurrence of traumatic brain injury. The tissue deformation in the direction of white matter tracts (axonal strain) was repeatedly shown to be an appropriate mechanical parameter to predict injury. However, when assessing the reliability of axonal strain to predict injury in a population, it is important to consider the predictor sensitivity to the biological inter-subject variability of the human brain. The present study investigated the axonal strain response of 485 white matter subject-specific anisotropic finite element models of the head subjected to the same loading conditions. It was observed that the biological variability affected the orientation of the preferential directions (coefficient of variation of 39.41% for the elevation angle-coefficient of variation of 29.31% for the azimuth angle) and the determination of the mechanical fiber alignment parameter in the model (gray matter volume 55.55-70.75%). The magnitude of the maximum axonal strain showed coefficients of variation of 11.91%. On the contrary, the localization of the maximum axonal strain was consistent: the peak of strain was typically located in a 2 cm3volume of the brain. For a sport concussive event, the predictor was capable of discerning between non-injurious and concussed populations in several areas of the brain. It was concluded that, despite its sensitivity to biological variability, axonal strain is an appropriate mechanical parameter to predict traumatic brain injury.
authors.affiliation: Royal Institute of Technology KTH, School of Technology and Health, Hälsovägen 11C, 141 57, Huddinge, Sweden. chiaragi@kth.se.
authors.forename: Chiara
authors.identifier: 0000-0002-0569-5118
authors.initials: C
authors.lastname: Giordano
authors.affiliation: Royal Institute of Technology KTH, School of Technology and Health, Hälsovägen 11C, 141 57, Huddinge, Sweden.
authors.forename: Stefano
authors.initials: S
authors.lastname: Zappalà
authors.affiliation: Royal Institute of Technology KTH, School of Technology and Health, Hälsovägen 11C, 141 57, Huddinge, Sweden.
authors.forename: Svein
authors.initials: S
authors.lastname: Kleiven
mesh_terms: D001930:Brain Injuries / Q000175:diagnosis* / Q000473:pathology*; D006801:Humans; D008954:Models, Biological; D015203:Reproducibility of Results; D013314:Stress, Mechanical; D066127:White Matter / Q000473:pathology*
keywords: Axonal strain; Brain anisotropy; Finite element analysis; Traumatic brain injury