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White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities

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Abstract

A systematic correlation between finite element models (FEMs) and histopathology is needed to define deformation thresholds associated with traumatic brain injury (TBI). In this study, a FEM of a transected piglet brain was used to reverse engineer the range of optimal shear moduli for infant (5 days old, 553–658 Pa) and 4-week-old toddler piglet brain (692–811 Pa) from comparisons with measured in situ tissue strains. The more mature brain modulus was found to have significant strain and strain rate dependencies not observed with the infant brain. Age-appropriate FEMs were then used to simulate experimental TBI in infant (\(n=36\)) and preadolescent (\(n=17\)) piglets undergoing a range of rotational head loads. The experimental animals were evaluated for the presence of clinically significant traumatic axonal injury (TAI), which was then correlated with FEM-calculated measures of overall and white matter tract-oriented tissue deformations, and used to identify the metric with the highest sensitivity and specificity for detecting TAI. The best predictors of TAI were the tract-oriented strain (6–7 %), strain rate (38–40 s\(^{-1})\), and strain times strain rate (1.3–1.8 s\(^{-1})\) values exceeded by 90 % of the brain. These tract-oriented strain and strain rate thresholds for TAI were comparable to those found in isolated axonal stretch studies. Furthermore, we proposed that the higher degree of agreement between tissue distortion aligned with white matter tracts and TAI may be the underlying mechanism responsible for more severe TAI after horizontal and sagittal head rotations in our porcine model of nonimpact TAI than coronal plane rotations.

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Acknowledgments

We gratefully acknowledge support from the Department of Transportation—National Highway Transportation and Safety Administration (DTNH 22-07-H-00088), the National Institutes of Health (R01 NS39679), and the American Heart Association. We also acknowledge the work of Sohaib Hashmi, Nicole Ibrahim, and Jesse Jiang in the development of the finite element models and DTI image processing.

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Authors and Affiliations

  1. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    Sarah Sullivan, David Gabrieli, Connor Bradfield & Susan S. Margulies

  2. Division of Emergency Medicine, Department of Surgery, Duke University Medical Center, Durham, NC, USA

    Stephanie A. Eucker

  3. Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA

    Brittany Coats

  4. Department of Anesthesiology and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Matthew R. Maltese

  5. Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea

    Jongho Lee

  6. Academic Department of Neuropathology, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK

    Colin Smith

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  1. Sarah Sullivan
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  2. Stephanie A. Eucker
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  3. David Gabrieli
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  4. Connor Bradfield
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  9. Susan S. Margulies
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Correspondence to Susan S. Margulies.

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Sullivan, S., Eucker, S.A., Gabrieli, D. et al. White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities. Biomech Model Mechanobiol 14, 877–896 (2015). https://doi.org/10.1007/s10237-014-0643-z

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