Models of traumatic brain injury: modern approaches, classification, and research perspectives

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Abstract

Traumatic brain injury represents one of the most complex biomedical challenges, affecting millions of people worldwide each year. Various experimental and theoretical models are used to understand the pathophysiology of traumatic brain injury and to develop effective therapeutic strategies. This review focuses on three main groups of models: theoretical (in silico), cellular (in vitro), and animal (in vivo). Theoretical models of traumatic brain injury are based on mathematical approaches and computer simulations to analyze mechanical brain injuries, edema processes, ischemia, and neuroinflammation. In silico approaches provide high precision and reproducibility but require proper validation with biological data. Cellular models include the cultivation of neurons, astrocytes, microglia, and brain organoids, which are subjected to mechanical or chemical factors that mimic traumatic brain injury. These systems allow researchers to study cellular and molecular mechanisms such as apoptosis, neuroinflammation, and regeneration. However, in vitro models are limited by the absence of a systemic response characteristic of an entire organism. Animal models are considered the “gold standard” for studying traumatic brain injury. These involve direct mechanical impacts on the brains of animals (e.g., mice, rats, pigs), enabling the reproduction of clinical aspects of trauma, including behavioral and pathophysiological changes. Despite their high physiological relevance, in vivo models face ethical limitations and challenges in extrapolating results to humans. This article provides an overview of modern approaches to traumatic brain injury modeling, including their classification, characteristics, advantages, and limitations. The data presented may serve as a foundation for developing more effective treatment and rehabilitation strategies for traumatic brain injury patients.

About the authors

Anna A. Prokhorycheva

National Research Center “Kurchatov Institute”

Author for correspondence.
Email: Prokhorycheva_AA@nrcki.ru
ORCID iD: 0009-0001-5226-0803
SPIN-code: 5543-4462

Postgraduate Student

Russian Federation, Moscow

Alexander I. Budko

National Research Center “Kurchatov Institute”

Email: Budko_AI@nrcki.ru
ORCID iD: 0009-0007-3354-1646
SPIN-code: 2623-4530

Postgraduate Student

Russian Federation, Moscow

Olga M. Ignatova

National Research Center “Kurchatov Institute”

Email: Ignatova_OM@nrcki.ru
ORCID iD: 0000-0003-2763-3935
SPIN-code: 9352-3233

Research Laboratory Asistant

Russian Federation, Moscow

Yulia I. Vecherskaya

National Research Center “Kurchatov Institute”

Email: Vecherskaya_YI@nrcki.ru
ORCID iD: 0009-0000-2489-4588

PhD student

Russian Federation, Moscow

Stanislav A. Fokin

National Research Center “Kurchatov Institute”

Email: Fokin_SA@nrcki.ru

MD, PhD, Director of the Kurchatov Сomplex of Medical Primatology

Russian Federation, Moscow

Mariya A. Pahomova

Saint Petersburg State Pediatric Medical University

Email: mariya.pahomova@mail.ru
ORCID iD: 0009-0002-4570-8056
SPIN-code: 3168-2170

Senior Research Associate, Research Center

Russian Federation, Saint Petersburg

Andrey G. Vasiliev

Saint Petersburg State Pediatric Medical University

Email: avas7@mail.ru
ORCID iD: 0000-0002-8539-7128
SPIN-code: 1985-4025

MD, PhD, Dr. Sci. (Medicine), Professor, Head of the Department of Pathological Physiology with a Course in Immunology

Russian Federation, Saint Petersburg

Alexander P. Trashkov

National Research Center “Kurchatov Institute”

Email: Trashkov_AP@nrcki.ru
ORCID iD: 0000-0002-3441-0388
SPIN-code: 4231-1258

MD, PhD, Associate Professor

Russian Federation, Moscow

References

  1. Lichterman LB. Classification of cranial trauma. Russian journal of forensic medicine. 2015;1(3):37–48. EDN: YHMUBF
  2. Alshareef A, Giudice SJ, Forman J, et al. Biomechanics of the human brain during dynamic rotation of the head. J Neurotrauma. 2020;37(13):1546–1555. doi: 10.1089/neu.2019.6847
  3. Amirifar L, Shamloo A, Nasiri R, et al. Brain-on-a-chip: Recent advances in design and techniques for microfluidic models of the brain in health and disease. Biomaterials. 2022;285:121531. doi: 10.1016/j.biomaterials.2022.121531
  4. Azizi S, Hier DB, Allen B, et al. A kinetic model for blood biomarker levels after mild traumatic brain injury. Front Neurol. 2021;12:668606. doi: 10.3389/fneur.2021.668606
  5. Baird A, Oelsner L, Fisher C, et al. A multiscale computational model of angiogenesis after traumatic brain injury, investigating the role location plays in volumetric recovery. Math Biosci Eng. 2021;18(4):3227–3257. doi: 10.3934/mbe.2021161
  6. Bayly PV, Cohen TS, Leister EP, et al. Deformation of the human brain induced by mild acceleration. J Neurotrauma. 2005;22(8): 845–856. doi: 10.1089/neu.2005.22.845
  7. Beitchman JA, Lifshitz J, Harris NG, et al. Spatial distribution of neuropathology and neuroinflammation elucidate the biomechanics of fluid percussion injury. Neurotrauma Rep. 2021;2(1):59–75. doi: 10.1089/neur.2020.0046
  8. Bellotti C, Samudyata S, Thams S, et al. Organoids and chimeras: the hopeful fusion transforming traumatic brain injury research. Acta Neuropathol Commun. 2024;12(1):141. doi: 10.1186/s40478-024-01845-5
  9. Cernak I. Animal models of head trauma. NeuroRx. 2005;2(3):410–422. doi: 10.1602/neurorx.2.3.410
  10. Chapman DP, Vicini S, Burns MP, Evans R. Single neuron modeling identifies potassium channel modulation as potential target for repetitive head impacts. Neuroinformatics. 2023;21(3):501–516. doi: 10.1007/s12021-023-09633-7
  11. Chen Y, Constantini S, Trembover V, et al. An experimental model of closed head injury in mice: pathophysiology, histopathology, and cognitive deficit. J Neurotrauma. 1996;13(10):557–568. doi: 10.1089/neu.1996.13.557
  12. Donat CK, Yanez Lopez M, Sastre M, et al. From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury. Brain. 2021;144(1):70–91. doi: 10.1093/brain/awaa336
  13. Feeney DM, Boyeson MG, Linn RT, et al. Responses to cortical injury: I. Methodology and local effects of contusions in the rat. Brain Res. 1981;211(1):67–77. doi: 10.1016/0006-8993(81)90067-6
  14. Fitzgerald J, Houle S, Cotter C, et al. Lateral fluid percussion injury causes sex-specific deficits in anterograde but not retrograde memory. Front Behav Neurosci. 2022;16:806598. doi: 10.3389/fnbeh.2022.806598
  15. Galgano M, Russel T, McGillis S, et al. A review of traumatic brain injury animal models: are we lacking adequate models replicating chronic traumatic encephalopathy. J Neurol Neurobiol. 2015;2(1):2379–7150.117. doi: 10.16966/2379-7150.117
  16. Gennarelli TA. Animate models of human head injury. J Neurotrauma. 1994;11(4):357–368. doi: 10.1089/neu.1994.11.357
  17. Goldstein LE, Fisher AM, Tagge CA, et al. Chronic traumatic encephalopathy in blast-exposed military veterans and a blast neurotrauma mouse model. Sci Transl Med. 2012;4(134): 134ra60–134ra60. doi: 10.1126/scitranslmed.3003716
  18. Greenwald RM, Gwin JT, Chu JJ, Crisco JJ. Head impact severity measures for evaluating mild traumatic brain injury risk exposure. Neurosurgery. 2008;62(4):789–798. doi: 10.1227/01.neu.0000318162.67472.ad
  19. Harris JP, Mietus CJ, Browne KD, et al. Neuronal somatic plasmalemmal permeability and dendritic beading caused by head rotational traumatic brain injury in pigs — an exploratory study. Front Cell Neurosci. 2023;17:1055455. doi: 10.3389/fncel.2023.1055455
  20. Johnson VE, Meaney DF, Cullen DC, Smith DH. Animal models of traumatic brain injury. In: Grafman J, Salazar AM, editors. Handbook of clinical neurology. Vol. 127. Elsevier, 2015. P. 115–128. doi: 10.1016/B978-0-444-52892-6.00008-8
  21. Kayabaş M. Experimental traumatic brain injury models in rats: Experimental traumatic brain injury. Rats. 2023;1(1):15–19.
  22. Kiening KL, van Landeghem FKH, Shreiber S, et al. Decreased hemispheric Aquaporin-4 is linked to evolving brain edema following controlled cortical impact injury in rats. Neurosci Lett. 2002;324(20):105–108. doi: 10.1016/S0304-3940(02)00180-5
  23. Kim J-T, Song K, Han SW, et al. Modeling of the brain-lung axis using organoids in traumatic brain injury: an updated review. Cell Biosci. 2024;14(1):83. doi: 10.1186/s13578-024-01252-2
  24. Kumaria A. In vitro models as a platform to investigate traumatic brain injury. Altern Lab Anim. 2017;45(4):201–211. doi: 10.1177/026119291704500405
  25. Langenderfer M, Williams K, Douglas A, et al. An evaluation of measured and predicted air blast parameters from partially confined blast waves. Shock Waves. 2021;31:175–192. doi: 10.1007/s00193-021-00993-0
  26. Liaudanskaya V, Fiore NJ, Zhang Y, et al. Mitochondria dysregulation contributes to secondary neurodegeneration progression post-contusion injury in human 3D in vitro triculture brain tissue model. Cell Death Dis. 2023;14(8):496. doi: 10.1038/s41419-023-05980-0
  27. Lighthall JW. Controlled cortical impact: a new experimental brain injury model. J Neurotrauma. 1988;5(1):1–15. doi: 10.1089/neu.1988.5.1
  28. Liu N, Li Y, Jiang Y, et al. Establishment and application of a novel in vitro model of microglial activation in traumatic brain injury. J Neuroscience. 2023;43(2):319–332. doi: 10.1523/JNEUROSCI.1539-22.2022
  29. Long Y, Zou L, Liu H, et al. Altered expression of randomly selected genes in mouse hippocampus after traumatic brain injury. J Neurosci Res. 2003;71(5):710–720. doi: 10.1002/jnr.10524
  30. Ma X, Aravind A, Pfister BJ, et al. Animal models of traumatic brain injury and assessment of injury severity. Mol Neurobiol. 2019;56:5332–5345. doi: 10.1007/s12035-018-1454-5
  31. Marmarou A, Abd-Elfattah Foda A, van den Brink W, et al. A new model of diffuse brain injury in rats: Part I: Pathophysiology and biomechanics. J Neurosurg. 1994;80(2):291–300. doi: 10.3171/jns.1994.80.2.0291
  32. McAteer KM, Turner RJ, Corrigan F. Animal models of chronic traumatic encephalopathy. Concussion. 2017;2(2):CNC32. doi: 10.2217/cnc-2016-0031
  33. Morales DM, Marklund N, Lebold D, et al. Experimental models of traumatic brain injury: do we really need to build a better mousetrap? Neuroscience. 2005;136(4):971–989. doi: 10.1016/j.neuroscience.2005.08.030
  34. Namjoshi DR, Good C, Cheng WH, et al. Towards clinical management of traumatic brain injury: a review of models and mechanisms from a biomechanical perspective. Dis Models Mech. 2013;6(6): 1325–1338. doi: 10.1242/dmm.011320
  35. Navarro VM, Boehme N, Wasserman EA, Harper MM. Enhanced attention in rats following blast-induced traumatic brain injury. Heliyon. 2024;10(4):e25661. doi: 10.1016/j.heliyon.2024.e25661
  36. Ommaya AK, Yarnell P, Hirsch AE, Harris EH. Scaling of experimental data on cerebral concussion in sub-human primates to concussion threshold for man. In: 11th Stapp Car Crash Conference. Vol. 6. 1967. doi: 10.4271/670906
  37. Risling M, Davidsson J. Experimental animal models for studies on the mechanisms of blast-induced neurotrauma. Front Neurol. 2012;3:30. doi: 10.3389/fneur.2012.00030
  38. Robinson BD, Isbell CL, Melge AR, et al. Doxycycline prevents blood–brain barrier dysfunction and microvascular hyperpermeability after traumatic brain injury. Sci Rep. 2022;12(1):5415. doi: 10.1038/s41598-022-09394-4
  39. Salvador E, Burek M, Förster CY. Stretch and/or oxygen glucose deprivation (OGD) in an in vitro traumatic brain injury (TBI) model induces calcium alteration and inflammatory cascade. Front Cell Neurosci. 2015;9:323. doi: 10.3389/fncel.2015.00323
  40. Shapira Y, Shohami E, Sidi A, et al. Experimental closed head injury in rats: mechanical, pathophysiologic, and neurologic properties. Crit Care Med. 1988;16(3):258–265. doi: 10.1097/00003246-198803000-00010
  41. Shrirao AB, Kung FH, Omelchenko A, et al. Microfluidic platforms for the study of neuronal injury in vitro. Biotechnol Bioeng. 2018;115(4):815–830. doi: 10.1002/bit.26519
  42. Smith DH, Chen X-H, Xu B-N, et al. Characterization of diffuse axonal pathology and selective hippocampal damage following inertial brain trauma in the pig. J Neuropathol Exp Neurol. 1997;56(7): 822–834. doi: 10.1097/00005072-199756070-00009
  43. Umfress A, Chakraborti A, Sudarsana Devi SP, et al. Cdk5 mediates rotational force-induced brain injury. Sci Rep. 2023;13(1):3394. doi: 10.1038/s41598-023-29322-4
  44. Viano DC, Hamberger A, Bolouri H, Säljö A. Evaluation of three animal models for concussion and serious brain injury. Ann Biomed Eng. 2012;40:213–226. doi: 10.1007/s10439-011-0386-2
  45. Wang S, Eckstein KN, Guertler CA, et al. Post-mortem changes of anisotropic mechanical properties in the porcine brain assessed by MR elastography. Brain Multiphys. 2024;6:100091. doi: 10.1016/j.brain.2024.100091
  46. Witcher KG, Dziadis JE, Bray CE, et al. Comparison between midline and lateral fluid percussion injury in mice reveals prolonged but divergent cortical neuroinflammation. Brain Res. 2020;1746:146987. doi: 10.1016/j.brainres.2020.146987
  47. Wojnarowicz MW, Fisher AM, Minaeva O, Goldstein LE. Considerations for experimental animal models of concussion, traumatic brain injury, and chronic traumatic encephalopathy — these matters matter. Front Neurol. 2017;8:240. doi: 10.3389/fneur.2017.00240
  48. Wu T, Rifkin JA, Rayfield A, et al. An interdisciplinary computational model for predicting traumatic brain injury: Linking biomechanics and functional neural networks. NeuroImage. 2022;251:119002. doi: 10.1016/j.neuroimage.2022.119002
  49. Youn DH, Jung H, Tran NM, et al. The therapeutic role of nanoparticle shape in traumatic brain injury: an in vitro comparative study. J Korean Neurosurg Soc. 2022;65(2):196–203. doi: 10.3340/jkns.2021.0185
  50. Zhao Q, Zhang J, Li H, et al. Models of traumatic brain injury-highlights and drawbacks. Front Neurol. 2023;14:1151660. doi: 10.3389/fneur.2023.1151660

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2. Figure. Schematic portrayal of Traumatic Brain Injury free-falling load models

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