Abstract #0014

Demonstration of a Sliding-Window Diffusion Tensor Technique for Temporal Study of Post-Exercise Skeletal Muscle Dynamics

Conrad P Rockel^1,2 and Michael D Noseworthy^1,2,3

¹School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada, ²Imaging Research Centre, St Josephs Healthcare, Hamilton, ON, Canada, ³Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada

A novel sliding-window DTI analysis strategy, aimed at achieving both temporal resolution and valid spatial representation, was tested on one human subject pre- and post-exercise (plantar flexion) across 4 sets of different intensity. Temporal diffusion measures comprised of 3- and 15-directions (ADC and MD/FA, respectively) were assessed, as well as signal intensity of accompanying T2-weighted images (S0). Peroneus longus demonstrated increase in MD, ADC and S0, the peak and duration of which reflected exercise intensity. FA appeared noisy, although demonstrated large decreases following higher intensity exercise. While further work is needed, this method shows promise in measuring skeletal muscle dynamics.

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