Skeletal muscle diffusion tensor-MRI fiber tracking: rationale, data acquisition and analysis methods, applications and future directions

Bruce M. Damon, Martijn Froeling, Amanda K. W. Buck, Jos Oudeman, Zhaohua Ding, Aart J. Nederveen, Emily C. Bush, Gustav J. Strijkers

Research output: Contribution to journalReview articleAcademicpeer-review

74 Citations (Scopus)

Abstract

The mechanical functions of muscles involve the generation of force and the actuation of movement by shortening or lengthening under load. These functions are influenced, in part, by the internal arrangement of muscle fibers with respect to the muscle's mechanical line of action. This property is known as muscle architecture. In this review, we describe the use of diffusion tensor (DT)-MRI muscle fiber tracking for the study of muscle architecture. In the first section, the importance of skeletal muscle architecture to function is discussed. In addition, traditional and complementary methods for the assessment of muscle architecture (brightness-mode ultrasound imaging and cadaver analysis) are presented. Next, DT-MRI is introduced and the structural basis for the reduced and anisotropic diffusion of water in muscle is discussed. The third section discusses issues related to the acquisition of skeletal muscle DT-MRI data and presents recommendations for optimal strategies. The fourth section discusses methods for the pre-processing of DT-MRI data, the available approaches for the calculation of the diffusion tensor and the seeding and propagating of fiber tracts, and the analysis of the tracking results to measure structural properties pertinent to muscle biomechanics. Lastly, examples are presented of how DT-MRI fiber tracking has been used to provide new insights into how muscles function, and important future research directions are highlighted. Copyright © 2016 John Wiley & Sons, Ltd
Original languageEnglish
Article numbere3563
JournalNMR in Biomedicine
Volume30
Issue number3
Early online date2017
DOIs
Publication statusPublished - 2017

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