3-D Measurements of Acceleration-Induced Brain Deformation via Harmonic Phase Analysis and Finite-Element Models

• Published in: IEEE transactions on biomedical engineering 2019-05, Vol.66 (5), p.1456-1467
• Main Authors: Gomez, Arnold D., Knutsen, Andrew K., Xing, Fangxu, Lu, Yuan-Chiao, Chan, Deva, Pham, Dzung L., Bayly, Philip, Prince, Jerry L.
• Format: Article
• Language: English
• Subjects: Acceleration; Biomechanical Phenomena - physiology; Biomedical measurement; Brain; Brain - anatomy & histology; Brain - diagnostic imaging; Brain - physiology; brain biomechanics; Computer simulation; Data processing; Deformation; Error reduction; Finite Element Analysis; Finite element method; finite strain; Harmonic analysis; harmonic phase analysis; Head; Head injuries; Head movement; Humans; Image Processing, Computer-Assisted - methods; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Mathematical models; Motion estimation; Motion simulation; Movement - physiology; Neuroimaging; NMR; Nuclear magnetic resonance; Phantoms, Imaging; Power harmonic filters; Regularization; Strain; Tagged MRI; Three dimensional motion; Traumatic brain injury
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2018.2874591

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 0.1 ± 0.2% (mean ± std. dev.) for linear acceleration and 0.7 ± 0.3% 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.