The impact of diffusion tensor imaging tractography settings on muscle fascicle architecture and diffusion parameter estimates: Tract length, completion, and curvature are most sensitive to tractography settings

Author:

Lockard Carly A.1ORCID,Hooijmans Melissa T.123,Zhou Xingyu134,Coolbaugh Crystal3,Damon Bruce M.13456

Affiliation:

1. Carle Clinical Imaging Research Program, Stephens Family Clinical Research Institute Carle Health Urbana Illinois USA

2. Department of Radiology and Nuclear Medicine, Amsterdam UMC University of Amsterdam Amsterdam The Netherlands

3. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville Tennessee USA

4. Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA

5. Department of Radiology and Radiological Sciences Vanderbilt University Nashville Tennessee USA

6. Department of Bioengineering University of Illinois at Urbana‐Champaign Urbana Illinois USA

Abstract

AbstractDiffusion‐tensor (DT)‐MRI tractography provides information about properties relevant to muscle health and function, including estimates of architectural properties such as fascicle length, pennation angle, and curvature and diffusion properties such as mean diffusivity (MD) and fractional anisotropy (FA). Tractography settings, including integration algorithms, thresholds for early tract termination, and tract smoothing approaches, impact the accuracy of the muscle property estimates. However, muscle DT‐MRI tractography is performed using a variety of these settings, complicating comparisons between different studies. The effects of different tractography settings on muscle architecture estimates have not been fully explored, and optimized settings for muscle tractography have not yet been determined. We examined the influence of integration algorithm and termination check settings combined with a range of step sizes, termination criteria, and smoothing polynomial orders on tract characteristics, completion/reason for termination, and goodness of fit between fiber tracts and smoothing polynomials using 3‐T DT‐MR images of the lower leg muscles of seven healthy adults. We found that tract length and completion were highly sensitive to strict FA and intersegment angle thresholds (25%–69% reduction in complete fiber tracts from lowest to highest minimum FA threshold and 11%–36% reduction from highest to lowest intersegment angle threshold). Higher order polynomials (third and fourth order vs. second order) better fit the muscle fiber trajectories, but curvature estimates were highly sensitive to smoothing polynomial order (3.9–6.6 m−1 increase for second‐ vs. fourth‐order fitting polynomials). Step size impacted curvature estimates, albeit to a lesser degree. Integration algorithm had little impact, and mean pennation angle, and tract‐based FA and MD, were relatively insensitive to all parameters. The results demonstrate which muscle diffusion measures and architectural estimates are most sensitive to varying tractography settings and support the need for consistent reporting of tractography details to aid interpretation and comparison of results between studies.

Funder

National Institutes of Health

Publisher

Wiley

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