OBJECTIVE: To obtain dense spatiotemporal measurements of brain deformation from two distinct but complementary head motion experiments: linear and rotational accelerations. METHODS: This study introduces a strategy for integrating harmonic phase analysis of tagged magnetic resonance imaging (MRI) and finite-element models to extract mechanically representative deformation measurements. The method was calibrated using simulated as well as experimental data, demonstrated in a phantom including data with image artifacts, and used to measure brain deformation in human volunteers undergoing rotational and linear acceleration. RESULTS: Evaluation methods yielded a displacement error of 1.1 mm compared to human observers and strain errors between [Formula: see text] for linear acceleration and [Formula: see text] for rotational acceleration. This study also demonstrates an approach that can reduce error by 86% in the presence of corrupted data. Analysis of results shows consistency with 2-D motion estimation, agreement with external sensors, and the expected physical behavior of the brain. CONCLUSION: Mechanical regularization is useful for obtaining dense spatiotemporal measurements of in vivo brain deformation under different loading regimes. SIGNIFICANCE: The measurements suggest that the brain's 3-D response to mild accelerations includes distinct patterns observable using practical MRI resolutions. This type of measurement can provide validation data for computer models for the study of traumatic brain injury.
OBJECTIVE: To obtain dense spatiotemporal measurements of brain deformation from two distinct but complementary head motion experiments: linear and rotational accelerations. METHODS: This study introduces a strategy for integrating harmonic phase analysis of tagged magnetic resonance imaging (MRI) and finite-element models to extract mechanically representative deformation measurements. The method was calibrated using simulated as well as experimental data, demonstrated in a phantom including data with image artifacts, and used to measure brain deformation in human volunteers undergoing rotational and linear acceleration. RESULTS: Evaluation methods yielded a displacement error of 1.1 mm compared to human observers and strain errors between [Formula: see text] for linear acceleration and [Formula: see text] for rotational acceleration. This study also demonstrates an approach that can reduce error by 86% in the presence of corrupted data. Analysis of results shows consistency with 2-D motion estimation, agreement with external sensors, and the expected physical behavior of the brain. CONCLUSION: Mechanical regularization is useful for obtaining dense spatiotemporal measurements of in vivo brain deformation under different loading regimes. SIGNIFICANCE: The measurements suggest that the brain's 3-D response to mild accelerations includes distinct patterns observable using practical MRI resolutions. This type of measurement can provide validation data for computer models for the study of traumatic brain injury.
Authors: Andrew K Knutsen; Arnold D Gomez; Mihika Gangolli; Wen-Tung Wang; Deva Chan; Yuan-Chiao Lu; Eftychios Christoforou; Jerry L Prince; Philip V Bayly; John A Butman; Dzung L Pham Journal: Brain Multiphys Date: 2020-09-03
Authors: Arnold D Gomez; Philip V Bayly; John A Butman; Dzung L Pham; Jerry L Prince; Andrew K Knutsen Journal: J R Soc Interface Date: 2021-06-23 Impact factor: 4.293
Authors: Philip V Bayly; Ahmed Alshareef; Andrew K Knutsen; Kshitiz Upadhyay; Ruth J Okamoto; Aaron Carass; John A Butman; Dzung L Pham; Jerry L Prince; K T Ramesh; Curtis L Johnson Journal: Ann Biomed Eng Date: 2021-07-01 Impact factor: 4.219