Abstract #1135

Differentiating Skeletal Muscle Fiber Composition Using a Bi-Fractal Model of Resting-State Muscle BOLD

Joshua Ethan McGillivray^1,2, Dinesh Kumbhare^1,2,3, and Michael D Noseworthy^1,2,4,5

¹School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada, ²Imaging Research Centre, St. Joseph's Healthcare, Hamilton, ON, Canada, ³Department of Medicine and Biomedical Engineering, University of Toronto, Toronto, ON, Canada, ⁴Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada, ⁵Department of Radiology, McMaster University, Hamilton, ON, Canada

Synopsis

Lower leg resting-state BOLD images (n=8 males, 4 endurance, 4 power athletes), were acquired after 30min of rest, allowing for blood-flow normalization. BOLD images were motion corrected and the gastrocnemius and soleus manually segmented using an anatomical reference for their differing twitch fibre profiles. Voxel-wise BOLD mono- and bi-fractal dimension were computed using the scaled windowed variance approach, with linear detrending, removing scanner induced low-frequency variations. The bi-fractal dimension was significantly different between endurance and power groups in both muscles. Specific bi-fractal components more readily distinguished soleus and gastrocnemius for the endurance (I) and power (II) group, when at rest.

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