Measurement of Twitch Dynamics in Response to Exercise Induced Changes in Mitochondrial Disease Using Motor Unit Magnetic Resonance Imaging (MUMRI): A Proof-of-Concept Study

Abstract

Muscle twitch dynamics and fatigability change in response to muscle disease. In this study, we developed an imaging paradigm to measure muscle twitch dynamics, and the response of the muscle to voluntary fatiguing contractions. We used a novel imaging technique called motor unit magnetic resonance imaging (MUMRI). MUMRI allows visualisation of muscle and motor unit activity by combining in-scanner electrical stimulation with dynamic pulsed gradient spin echo (twitch dynamics, PGSE-MUMRI) and phase contrast (fatigue, PC-MUMRI) imaging. In Part I of this study, we scanned 10 healthy controls, we measured the muscle rise (T_rise), contraction (T_contract) and half-relaxation time (T_half-relax) of the tibialis anterior (TA) muscle on a voxel-wise basis using PGSE-MUMRI. Five controls were scanned twice to assess reproducibility; PGSE-MUMRI demonstrated reproducible results, with low variation between scans 3.4% for T_rise, 6.4% for T_contract and 7.1% for T_half-relax. We then developed a PC-MUMRI paradigm to measure the recovery of the TA in response to a fatiguing voluntary exercise. In Part II of the study, we applied these two novel imaging paradigms in a cohort study of nine patients with single large-scale mtDNA deletion primary mitochondrial myopathy (PMM). Patients underwent a 12-week resistance exercise programme and baseline, and follow-up MRI was performed. PGSE-MUMRI detected a significantly longer muscle contraction time between baseline and follow-up in PMM patients 108.7 ± 7.9 vs. post-119.3 ± 10.4 ms; p = 0.018. There was no statistical difference in the recovery half maximum measured using PC-MUMRI in PMM patients between baseline and follow-up 254 ± 109 vs. 137 ± 41 s; p = 0.074. In conclusion, PGSE-MUMRI has detected differences in muscle twitch dynamics between controls and PMM following an exercise programme, and we can visualise differences in twitch dynamics subregions of muscle using this technique. The PC-MUMRI technique has shown promise as a novel measure of muscle fatigue.

Keywords: exercise; fatigue; mitochondrial disease; motor unit; twitch dynamics.

FIGURE 1

Flowchart providing an overview of the study design. Ten healthy controls underwent a baseline MRI, with a subset of five volunteers returning for reproducibility and 31P‐MRS comparison assessments. Then an interventional study in nine patients with PMM was performed, consisting of baseline clinical and imaging assessments followed by a 12‐week exercise intervention and subsequent follow‐up clinical and imaging assessments. Numbers of controls/patients shown at each stage.

FIGURE 2

(A) Set‐up for a MUMRI experiment showing the placement of the surface coils and anode and cathode for common peroneal nerve stimulation. (B) Schematic of a pulsed gradient spin echo sequence (PGSE), representing altering of the electrical stimulus with respect to the 90° RF pulse, the stimulus was altered for each acquisition from 45 ms after the 90° RF pulse to 400 ms before the 90° RF pulse. (C) Example of a PGSE setup scan showing increasing stimulus current until maximum contrast between stimulated and non‐stimulated muscle is observed (at 15.5 mA). (D) Example images from a PGSE latency scan (twitch profile scan) showing images corresponding to different electrical stimulus delays relative to the RF 90° pulse.

FIGURE 3

(A) A PGSE‐MUMRI sequence was used to identify the stimulation current for the subsequent phase contrast series to measure muscle fatigue. This was achieved by incrementally increasing the current through a series of MUMRI acquisitions—to standardise the measurement between subjects, the optimal current is defined at the value which results in a signal of 67% of the maximum (red point) average value within the TA (red outline). The TA muscle is delineated in red. (B) Bipolar gradient phase contrast acquisitions (VENC = 6 cm/s) are acquired at the current identified in panel A), with incrementally increased latency between stimulation and slice acquisition. This produces a muscle twitch velocity map, demonstrated here for the TA muscle. The peak velocity is easily identified (red point). (C) Pre‐exercise cyclic PC‐MUMRI. The expected latency of the peak velocity is sampled cyclically with four additional datapoints (−10 to +10 ms, step 5 ms) to account for any shift in peak velocity latency resulting from the muscle fatigue protocol. (D) Post‐exercise cyclic PC MUMRI. The subject performs fatiguing isometric exercise in the scanner, resulting in a loss of the stimulated motor unit twitch. Stimulated PC‐MUMRI scans were then collected using the cyclic sampling of the peak velocity for 20 min. The graph demonstrates a velocity near 0 cm/s directly following exercise that gradually recovers back to baseline values over time.

FIGURE 4

(A) Data processing steps. First registration of the time‐series to the first image. Secondly, segmentation of the TA muscle. Finally, smoothing of the segmented image and interpolation of the time series. (B) Graph shows smoothed and interpolated signal from the red voxel in the smoothed image. The red points show the automatically extracted times to calculate rise time (T_rise), contraction time (T_contract) and half relaxation time (T_half‐relax). Example calculations are shown underneath for the red voxel. (C) This process is repeated for all voxels within the region of interest to create parametric maps. Each map has its own scale.

FIGURE 5

(A) Reproducibility plots for rise time, contraction time, and half relaxation time measured with PGSE‐MUMRI for five controls, d is the mean percentage difference in the metric between scan 1 and 2. (B) Post‐fatigue twitch velocity recovery curves measured with PC‐MUMRI of five healthy volunteers, collected in separate sessions. Data are normalised to end recovery velocity—red (scan 1) and blue (scan 2). Corresponding 31P recovery curves are plotted in black.

FIGURE 6

(A) Box plots of rise time, contraction time and half relaxation time comparing healthy controls (blue) and patients with primary mitochondrial myopathy (PMM, orange) at baseline. (B) Two example PC‐MUMRI recovery curves from a healthy control (blue) and PMM patient (orange) fitted with the five‐parameter Gompertz model, R ² values are shown on the graph.

FIGURE 7

(A) Dot plots for rise time, contraction time, and half relaxation time for patients with primary mitochondrial myopathy pre and post 12‐week exercise programme. This demonstrates a significantly longer contraction time post‐exercise programme. (B) Example parametric maps for contraction time from three patients, top row is baseline and bottom row is post 12‐week exercise programme, demonstrating regional changes in contraction time.

FIGURE 8

(A) Example twitch velocity post‐fatigue recovery curves in a participant with PMM, before (black dots) and after the 12‐week exercise programme (blue squares). Velocity data plotted with fitted model (red lines) and the time to half‐maximum (T_half‐max). (B) T_half‐max of the phase contrast velocity recovery curves before (circles) and after (triangles) a 12‐week exercise programme in five patients with PMM. The three patients with the highest initial T_half‐max demonstrate changes consistent with faster twitch recovery following the exercise programme. The remaining two patients did not demonstrate a significant change in the twitch recovery—we note that these had the quickest initial T_half‐max.

FIGURE 9

Histograms of the contraction time for each patient (P01–P07) on a voxel‐wise basis at baseline (blue bars; left) and at 12 weeks post‐exercise programme (green bars; right). A nonparametric fit is applied to show distribution (baseline—red; 12 weeks—black).

FIGURE 10

(A) Thresholded voxel wise maps of contraction time for each participant at baseline (top row) and at 12 weeks (bottom row). (B) Thresholded voxel wise maps of contraction time for the five healthy controls who underwent two scans scan 1 (top row), scan 2 (bottom row). Thresholds applied are based on the histogram distributions: light pink represents contraction times greater than the minimum value from the histogram and less than or equal to 100 ms; red represents contraction times greater than 100 and less than or equal to 150 ms; dark red represents contraction times greater than 150 ms and less than or equal to 200 ms; maroon represents contraction times greater than 200 ms and less than or equal to the maximum value from the histogram.