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Wu T, Rifkin JA, Rayfield AC, Anderson ED, Panzer MB, Meaney DF. Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models. Ann Biomed Eng 2022; 50:1423-1436. [PMID: 36125606 DOI: 10.1007/s10439-022-03085-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/11/2022] [Indexed: 11/30/2022]
Abstract
While individual susceptibility to traumatic brain injury (TBI) has been speculated, past work does not provide an analysis considering how physical features of an individual's brain (e.g., brain size, shape), impact direction, and brain network features can holistically contribute to the risk of suffering a TBI from an impact. This work investigated each of these features simultaneously using computational modeling and analyses of simulated functional connectivity. Unlike the past studies that assess the severity of TBI based on the quantification of brain tissue damage (e.g., principal strain), we approached the brain as a complex network in which neuronal oscillations orchestrate to produce normal brain function (estimated by functional connectivity) and, to this end, both the anatomical damage location and its topological characteristics within the brain network contribute to the severity of brain function disruption and injury. To represent the variations in the population, we analyzed a publicly available database of brain imaging data and selected five distinct network architectures, seven different brain sizes, and three uniaxial head rotational conditions to study the consequences of 74 virtual impact scenarios. Results show impact direction produces the most significant change in connections across brain areas (structural connectome) and the functional coupling of activity across these brain areas (functional connectivity). Axial rotations were more injurious than those with sagittal and coronal rotations when the head kinematics were the same for each condition. When the impact direction was held constant, brain network architecture showed a significantly different vulnerability across axial and sagittal, but not coronal rotations. As expected, brain size significantly affected the expected change in structural and functional connectivity after impact. Together, these results provided groupings of predicted vulnerability to impact-a subgroup of male brain architectures exposed to axial impacts were most vulnerable, while a subgroup of female brain architectures was the most tolerant to the sagittal impacts studied. These findings lay essential groundwork for subject-specific analyses of concussion and provide invaluable guidance for designing personalized protection equipment.
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Affiliation(s)
- Taotao Wu
- Department of Bioengineering, University of Pennsylvania, 240 Skirkanich Hall, 210 S 33rd St, Philadelphia, PA, 19104, USA
| | - Jared A Rifkin
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA
| | - Adam C Rayfield
- Department of Bioengineering, University of Pennsylvania, 240 Skirkanich Hall, 210 S 33rd St, Philadelphia, PA, 19104, USA
| | - Erin D Anderson
- Department of Bioengineering, University of Pennsylvania, 240 Skirkanich Hall, 210 S 33rd St, Philadelphia, PA, 19104, USA
| | - Matthew B Panzer
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - David F Meaney
- Department of Bioengineering, University of Pennsylvania, 240 Skirkanich Hall, 210 S 33rd St, Philadelphia, PA, 19104, USA. .,Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
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Rifkin JA, Wu T, Rayfield AC, Anderson ED, Panzer MB, Meaney DF. Brain architecture-based vulnerability to traumatic injury. Front Bioeng Biotechnol 2022; 10:936082. [PMID: 36091446 PMCID: PMC9448929 DOI: 10.3389/fbioe.2022.936082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/01/2022] [Indexed: 02/03/2023] Open
Abstract
The white matter tracts forming the intricate wiring of the brain are subject-specific; this heterogeneity can complicate studies of brain function and disease. Here we collapse tractography data from the Human Connectome Project (HCP) into structural connectivity (SC) matrices and identify groups of similarly wired brains from both sexes. To characterize the significance of these architectural groupings, we examined how similarly wired brains led to distinct groupings of neural activity dynamics estimated with Kuramoto oscillator models (KMs). We then lesioned our networks to simulate traumatic brain injury (TBI) and finally we tested whether these distinct architecture groups’ dynamics exhibited differing responses to simulated TBI. At each of these levels we found that brain structure, simulated dynamics, and injury susceptibility were all related to brain grouping. We found four primary brain architecture groupings (two male and two female), with similar architectures appearing across both sexes. Among these groupings of brain structure, two architecture types were significantly more vulnerable than the remaining two architecture types to lesions. These groups suggest that mesoscale brain architecture types exist, and these architectural differences may contribute to differential risks to TBI and clinical outcomes across the population.
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Affiliation(s)
- Jared A. Rifkin
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, United States
| | - Taotao Wu
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Adam C. Rayfield
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Erin D. Anderson
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Matthew B. Panzer
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, United States
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States
| | - David F. Meaney
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: David F. Meaney,
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