Finite Element Head Model | Yuzhe Lab

Quantifying Morphology-Related Deviations in Brain Strain Using an Automated Mesh Morphing Method

Fri, 22 May 2026 00:00:00 +0000

Abstract

Finite element head models (FEHMs) have been widely used to study the biomechanics in traumatic brain injury (TBI). Most FEHMs are constructed to reflect the average head shape, which inevitably leads to the omission of individual brain morphology. In this study, an automated mesh morphing method based on radial basis function-thin plate spline (RBF-TPS) with automated landmark extraction and projection was developed. Five representative subject-specific head models and the baseline model were subjected to head kinematics from six datasets covering diverse impact scenarios. Results showed that morphology-related deviations increased with loading severity, reaching up to 0.21 for MPS95 and 0.14 s^-1 for MPSR95. Logistic regression indicated that TBI risk thresholds varied by approximately 19.4% for MPS95 and 11.4% for MPSR95 across representative models. These findings indicate that subject-specific morphology affects strain response beyond size scaling alone, underscoring the importance of incorporating individual morphology into brain injury prediction models.

The Presence of the Temporal Horn Exacerbates the Vulnerability of Hippocampus During Head Impacts

Tue, 22 Mar 2022 00:00:00 +0000

Abstract

The Presence of the Temporal Horn Exacerbates the Vulnerability of Hippocampus During Head Impacts Zhou Zhou 1,2*†, Xiaogai Li 2†, August G. Domel 1, Emily L. Dennis 3,4, Marios Georgiadis 4, Yuzhe Liu 1, Samuel J. Raymond 1, Gerald Grant 5,6, Svein Kleiven 2‡, David Camarillo 1,5,7‡ and Michael Zeineh 4*‡ 1Department of Bioengineering, Stanford University, Stanford, CA, United States, 2Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden, 3TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States, 4Department of Radiology, Stanford University, Stanford, CA, United States, 5Department of Neurosurgery, Stanford University, Stanford, CA, United States, 6Department of Neurology, Stanford University, Stanford, CA, United States, 7Department of Mechanical Engineering, Stanford University, Stanford, CA, United States Hippocampal injury is common in traumatic brain injury (TBI) patients, but the underlying pathogenesis rema

Toward a Comprehensive Delineation of White Matter Tract-Related Deformation

Wed, 01 Dec 2021 00:00:00 +0000

Abstract

Finite element (FE) models of the human head are valuable instruments to explore the mechanobiological pathway from external loading, localized brain response, and resultant injury risks. The injury predictability of these models depends on the use of effective criteria as injury predictors. The FE-derived normal defor- mation along white matter (WM) fiber tracts (i.e., tract-oriented strain) recently has been suggested as an appropriate predictor for axonal injury. However, the tract-oriented strain only represents a partial depiction of the WM fiber tract deformation. A comprehensive delineation of tract-related deformation may improve the injury predictability of the FE head model by delivering new tract-related criteria as injury predictors. Thus, the present study performed a theoretical strain analysis to comprehensively characterize the WM fiber tract deformation by relating the strain tensor of the WM element to its embedded fiber tract. Three new tract-related strains with exact analytical solutions were proposed, measuring the normal defor- mation perpendicular to the fiber tracts (i.e., tract-perpendicular strain), and shear deformation along and perpendicular to the fiber tracts (i.e., axial-shear strain and lateral-shear strain, respectively). The injury pre- dictability of these three newly proposed strain peaks along with the previously used tract-oriented strain peak and maximum principal strain (MPS) were evaluated by simulating 151 impacts with known outcome (concussion or non-concussion). The results preliminarily showed that four tract-related strain peaks exhibited superior performance than MPS in discriminating concussion and non-concussion cases. This study presents a comprehensive quantification of WM tract-related deformation and advocates the use of orientation-dependent strains as criteria for injury prediction, which may ultimately contribute to an ad- vanced mechanobiological understanding and enhanced computational predictability of brain injury.