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MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury

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Abstract

Computational models of the brain and its biomechanical response to skull accelerations are important tools for understanding and predicting traumatic brain injuries (TBIs). However, most models have been developed using experimental data collected on animal models and cadaveric specimens, both of which differ from the living human brain. Here we describe efforts to noninvasively measure the biomechanical response of the human brain with MRI—at non-injurious strain levels—and generate data that can be used to develop, calibrate, and evaluate computational brain biomechanics models. Specifically, this paper reports on a project supported by the National Institute of Neurological Disorders and Stroke to comprehensively image brain anatomy and geometry, mechanical properties, and brain deformations that arise from impulsive and harmonic skull loadings. The outcome of this work will be a publicly available dataset (http://www.nitrc.org/projects/bbir) that includes measurements on both males and females across an age range from adolescence to older adulthood. This article describes the rationale and approach for this study, the data available, and how these data may be used to develop new computational models and augment existing approaches; it will serve as a reference to researchers interested in using these data.

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Acknowledgments

We acknowledge support from the National Institutes of Health Grants U01NS112120 and R01/R56NS055951, the intramural research program in the Clinical Center of the National Institutes of Health, and the Department of Defense in the Center for Neuroscience and Regenerative Medicine.

Conflict of interest

Dr. Prince and Dr. Johnson have intellectual property rights related to some of the imaging methods described in this work.

Data Availability

All data described in this work is available at http://www.nitrc.org/projects/bbir.

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Authors and Affiliations

  1. Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO, USA

    Philip V. Bayly & Ruth J. Okamoto

  2. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA

    Ahmed Alshareef, Aaron Carass & Jerry L. Prince

  3. Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA

    Andrew K. Knutsen & Dzung L. Pham

  4. Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, USA

    Kshitiz Upadhyay & K. T. Ramesh

  5. Clinical Center, National Institutes of Health, Bethesda, MD, USA

    John A. Butman

  6. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA

    K. T. Ramesh

  7. Department of Biomedical Engineering, University of Delaware, Newark, DE, USA

    Curtis L. Johnson

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  1. Philip V. Bayly
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Correspondence to Philip V. Bayly or Curtis L. Johnson.

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Bayly, P.V., Alshareef, A., Knutsen, A.K. et al. MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury. Ann Biomed Eng 49, 2677–2692 (2021). https://doi.org/10.1007/s10439-021-02820-0

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