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Abstract #1135

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

Joshua Ethan McGillivray1,2, Dinesh Kumbhare1,2,3, and Michael D Noseworthy1,2,4,5
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


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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