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- Montanino, Annaclaudia, 1990-, et al.
(author)
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Subject-specific multiscale analysis of concussion : from macroscopic loads to molecular-level damage
- 2021
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In: Brain Multiphysics. - : Elsevier BV. - 2666-5220. ; 2
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Journal article (peer-reviewed)abstract
- Sports concussion is a form of mild traumatic brain injury (mTBI) caused by an impulsive force transmitted to the head. While concussion is recognized as a complex pathophysiological process affecting the brain at multiple scales, the causal link between external load and cellular, molecular level damage in mTBI remains elusive. The present study proposes a multiscale framework to analyze concussion and demonstrates its applicability with a real-life concussion case. The multiscale analysis starts from inputting mouth guard-recorded head kinematic into a detailed finite element (FE) head model tailored to the subject's head and white matter (WM) tract morphology. The resulting WM tract-oriented strains are then extracted and input to histology-informed micromechanical models of corpus callosum subregions with axonal detail to obtain axolemma strains at a subcellular level. By comparing axolemma strains against mechanoporation thresholds obtained via molecular dynamics (MD) simulations, axonal damage is inferred corresponding to a likelihood of concussion, in line with clinical observation. This novel multiscale framework bridges the organ-to-molecule length scales and accounts both inter- and intra-subject regional variability, providing a new way of non-invasively predicting axonal damage and real-life concussion analysis. The framework may contribute to a better understanding of the mechanistic causes behind concussion. Statement of Significance This study reports a multiscale computational framework for concussion, for the first time revealing a picture of how a global impact to the head measured on the field transfers to the cellular level of axons and finally down to the molecular level. Demonstrated with a real-life concussion case using a detailed and subject-specific head model, the results show molecular level damage corresponds to a likelihood of concussion, in line with clinical observation. An insight into the multiscale mechanical consequences is critical for a better understanding of the complex pathophysiological process affecting the brain at impact, which today are still poorly understood. Analyzing the concussive injury mechanisms the whole way from brains to molecules may also have significant clinical relevance. We show that in a typical injury scenario, the axolemma sustains large enough strains to entail pore formation in the adjoining lipid bilayer. Proration is found to occur in bilayer regions lacking ganglioside lipids, which provides important implications for the treatment of brain injury and other related neurodegenerative diseases.
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| 2. |
- Yuan, Qiantailang, et al.
(author)
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A novel framework for video-informed reconstructions of sports accidents : A case study correlating brain injury pattern from multimodal neuroimaging with finite element analysis
- 2024
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In: Brain Multiphysics. - : Elsevier BV. - 2666-5220. ; 6
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Journal article (peer-reviewed)abstract
- Ski racing is a high-risk sport for traumatic brain injury. A better understanding of the injury mechanism and the development of effective protective equipment remains central to resolving this urgency. Finite element (FE) models are useful tools for studying biomechanical responses of the brain, especially in real-world ski accidents. However, real-world accidents are often captured by handheld monocular cameras; the videos are shaky and lack depth information, making it difficult to estimate reliable impact velocities and posture which are critical for injury prediction. Introducing novel computer vision and deep learning algorithms offers an opportunity to tackle this challenge. This study proposes a novel framework for estimating impact kinematics from handheld, shaky monocular videos of accidents to inform personalized impact simulations. The utility of this framework is demonstrated by reconstructing a ski accident, in which the extracted kinematics are input to a neuroimaging-informed, personalized FE model. The FE-derived responses are compared with imaging-identified brain injury sites of the victim. The results suggest that maximum principal strain may be a useful metric for brain injury. This study demonstrates the potential of video-informed accident reconstructions combined with personalized FE modeling to evaluate individual brain injury. Statement of significance: Reconstructing real-world sports accidents combined with finite element (FE) models presents a unique opportunity to study brain injuries, as it enables simulating complex loading conditions experienced in reality. However, a significant challenge lies in accurately obtaining kinematics from the often shaky, handheld video footage of such accidents. We propose a novel framework that bridges the gap between real-world accidents and video-informed injury predictions. By integrating video analysis, 3D kinematics estimation, and personalized FE simulation, we extract accurate impact kinematics of a ski accident captured from handheld shaky monocular videos to inform personalized impact simulations, predicting the injury pathology identified by multimodal neuroimaging. This study provides important guidance on how best to estimate impact conditions from video-recorded accidents, opening new opportunities to better inform the biomechanical study of head trauma with improved boundary conditions.
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| 3. |
- Zhou, Zhou, 1990-, et al.
(author)
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Brain strain rate response : Addressing computational ambiguity and experimental data for model validation
- 2023
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In: Brain Multiphysics. - : Elsevier BV. - 2666-5220. ; 4
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Journal article (peer-reviewed)abstract
- Traumatic brain injury (TBI) is an alarming global public health issue with high morbidity and mortality rates. Although the causal link between external insults and consequent brain injury remains largely elusive, both strain and strain rate are generally recognized as crucial factors for TBI onsets. With respect to the flourishment of strain-based investigation, ambiguity and inconsistency are noted in the scheme for strain rate calculation within the TBI research community. Furthermore, there is no experimental data that can be used to validate the strain rate responses of finite element (FE) models of the human brain. The current work presented a theoretical clarification of two commonly used strain rate computational schemes: the strain rate was either calculated as the time derivative of strain or derived from the rate of deformation tensor. To further substantiate the theoretical disparity, these two schemes were respectively implemented to estimate the strain rate responses from a previous-published cadaveric experiment and an FE head model secondary to a concussive impact. The results clearly showed scheme-dependent responses, both in the experimentally determined principal strain rate and model-derived principal and tract-oriented strain rates. The results highlight that cross-scheme comparison of strain rate responses is inappropriate, and the utilized strain rate computational scheme needs to be reported in future studies. The newly calculated experimental strain rate curves in the supplementary material can be used for strain rate validation of FE head models.
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