Demonstration of a Sliding-Window Diffusion Tensor Technique for Temporal Study of Post-Exercise Skeletal Muscle Dynamics
Conrad P Rockel1,2 and Michael D Noseworthy1,2,3

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.


To evaluate a custom gradient acquisition strategy for dynamic measures of post-exercise human calf muscle using Diffusion Tensor Imaging (DTI) that enables temporal resolution, reliable spatial representation, and concurrent estimates of T2 change.


Diffusion and T2 values of active muscle are known to temporarily increase immediately following exercise1-4 although their differing rates suggest different origins of contrast1,2. DTI, using at least 6 diffusion-weighted (DW) directions, produces better spatial representations of anisotropic tissue than single or 3-direction diffusion estimates5, although at the expense of temporal resolution6-8. This study tested the sensitivity of a novel sliding-window gradient scheme, designed to achieve both temporal resolution and spatial accuracy, in detecting changes within human calf muscle following exercise.


(Exercise Protocol) Lower leg muscles evaluated using a 3T GE MR750 and 8-channel extremity coil (GE Healthcare, Milwaukee WI). DTI was acquired using dual echo SE-EPI (b=0 or 450s/mm2, TR/TE=4000/69.6, custom 15-dir gradient scheme, 16 slices 4mm thick, 16cm FOV, 64x64, ASSET = 2). Baselines consisted of 40-60 volumes (10-15 timepoints), while post-exercise consisted of 60-120 volumes (15-30 timepoints, ~4-8 min). Experiment duration (scanning, exercise, rest) was ~90 min. Diffusion volumes were acquired before and immediately following in-bore exercise (plantar flexion @0.5 Hz for 20sec or 2min) using an MRI-compatible ergometer. It was expected lateral gastrocnemius (LG) and peroneus longus (PER) would be active in this exercise, while anterior tibialis (ATIB) would not9 (Fig 1). Four exercise/scanning sets were performed, each separated by 10min rest. Exercise intensity was based on maximum weight single flex (MWSF) of volunteer, and increased across sets by adding weight or number of flexes. The four exercise sets were: 10 flexes @10%MWSF; 60 flexes @10%MWSF; 10 flexes @40%MWSF; and 60 flexes @40%MWSF.

(Analysis) This study used a custom 15-dir gradient table developed to allow analysis of multiple time scales (Fig 2). Following acquisition, each pre- and post-exercise 4D volume was registered to a common space using FLIRT10, then broken into subunits of 3 or 15 DW images succeeding each b=0 volume (Fig 2). Apparent diffusion coefficients (ADCs) were calculated for each 3-dir subunit11, and diffusion tensors were calculated for each 15-dir subunit using FSL12, to produce mean diffusivity (MD) and fractional anisotropy (FA) maps. Signal intensity of each b=0 (S0) was also assessed. Regions-of-interest (ROIs) were drawn for LG, PER and ATIB, each three 2x2-voxel squares across 5 axial slices (Fig 1) and applied to all subunits for each measure (MD/ADC, FA, S0). Unless specified, all calculations used Matlab (v7.9; Mathworks, Natick MA).


MD/ADC. (Overall) MD and ADC demonstrated similar values for each muscle, although ADC showed more variation across time (Fig 3). MD/ADC returned to baseline values during the post-exercise scanning period (~4-8 min), and within-muscle baselines were similar across all exercise sets. (Between Muscles) The PER showed largest increase in MD/ADC, while LG and ATIB showed minimal change, except after the 10-flex 10% set. ADC of PER increased slightly less than MD, and peaked sooner (Timepoint 2 vs 6). (Exercise Intensity) MD increased in all muscles following the first and least intensive exercise set (10-flex 10%) although ADC did not. The post-exercise increase in MD/ADC of PER showed similarity of peak height within MWSF sets (10% vs 40%), with greater MD/ADC for the 40% sets. The post-exercise increase in PER 40% 60-flex demonstrated greater initial MD/ADC than did the 40% 10-flex set, and also longer sustained increase.

S0. Baselines increased with successive exercise in PER, but not LG or ATIB (Fig 4). PER showed large increase in peak height for both 40%MWSF sets, with greater and sustained increase observed for the 60-flex set. All muscles showed a temporary increase in S0 following the first exercise (10-flex 10%MWSF).

FA. Variability in FA across time made interpretation difficult (Fig 5), although PER showed large post-exercise decreases in both 40%MWSF sets, the 60-flex set showing a greater sustained decrease.


Post-exercise diffusion and S0 changes in an expected active muscle (PER) reflected the intensity of exercise sets, while the inactive muscle (ATIB) showed little change. Minimal post-exercise LG change may be due to limb positioning during exercise13. Further work exploring the capabilities of this technique will incorporate other muscles, additional subjects, stricter control and ordering of exercise, and investigation into DTI with <15-dir subunits. Nonetheless, this DTI technique shows promise for representing temporal and spatial aspects of skeletal muscle dynamics.


National Sciences and Engineering Research Council of Canada (NSERC) Discovery grant (MDN)



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Figure 1. Regions of interest (ROIs) measured within the right human calf: anterior tibialis (ATIB), peroneus longus (PER) and lateral head of gastrocnemius (LG).

Figure 2. (A) Schematic of acquisition scheme using 15 non-collinear diffusion directions with embedded b=0 images every 3 DW volumes. (B) Subunits of 3 orthogonal gradient vectors, each preceded by a b=0 volume. (C) Subunits of 15-directions, demonstrating “sliding-window” temporal combination.

Numbers refer to timepoints aligned by last DW volume.

Figure 3. Pre- and post-exercise timecourse of diffusivity measures for anterior tibialis (ATIB), lateral gastrocnemius (LG) and peroneus longus (PER). Top row: 15-dir MD. Bottom row: 3-dir ADC.

Figure 4. Pre- and post-exercise timecourse of signal intensity of b=0 volumes (S0) for anterior tibialis (ATIB), lateral gastrocnemius (LG) and peroneus longus (PER).

Figure 5. Pre- and post-exercise timecourse of 15-dir FA for anterior tibialis (ATIB), lateral gastrocnemius (LG) and peroneus longus (PER).

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)