Neural Regeneration Research (Jan 2023)

A benchtop brain injury model using resected donor tissue from patients with Chiari malformation

  • Jacqueline A Tickle,
  • Jon Sen,
  • Christopher Adams,
  • David N Furness,
  • Rupert Price,
  • Viswapathi Kandula,
  • Nikolaos Tzerakis,
  • Divya M Chari

DOI
https://doi.org/10.4103/1673-5374.355761
Journal volume & issue
Vol. 18, no. 5
pp. 1057 – 1061

Abstract

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The use of live animal models for testing new therapies for brain and spinal cord repair is a controversial area. Live animal models have associated ethical issues and scientific concerns regarding the predictability of human responses. Alternative models that replicate the 3D architecture of the central nervous system have prompted the development of organotypic neural injury models. However, the lack of reliable means to access normal human neural tissue has driven reliance on pathological or post-mortem tissue which limits their biological utility. We have established a protocol to use donor cerebellar tonsillar tissue surgically resected from patients with Chiari malformation (cerebellar herniation towards the foramen magnum, with ectopic rather than diseased tissue) to develop an in vitro organotypic model of traumatic brain injury. Viable tissue was maintained for approximately 2 weeks with all the major neural cell types detected. Traumatic injuries could be introduced into the slices with some cardinal features of post-injury pathology evident. Biomaterial placement was also feasible within the in vitro lesions. Accordingly, this ‘proof-of-concept’ study demonstrates that the model offers potential as an alternative to the use of animal tissue for preclinical testing in neural tissue engineering. To our knowledge, this is the first demonstration that donor tissue from patients with Chiari malformation can be used to develop a benchtop model of traumatic brain injury. However, significant challenges in relation to the clinical availability of tissue were encountered, and we discuss logistical issues that must be considered for model scale-up.

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