Severe spinal cord injury (SCI) leads to skeletal muscle atrophy and adipose tissue infiltration in the skeletal muscle, which can result in compromised muscle mechanical output and lead to health-related complications. In this study, we developed a novel automatic 3-D approach for volumetric segmentation and quantitative assessment of thigh Magnetic Resonance Imaging (MRI) volumes in individuals with chronic SCI as well as non-disabled individuals. In this framework, subcutaneous adipose tissue, inter-muscular adipose tissue and total muscle tissue are segmented using linear combination of discrete Gaussians algorithm. Also, three thigh muscle groups were segmented utilizing the proposed 3-D Joint Markov Gibbs Random Field model that integrates first order appearance model, spatial information, and shape model to localize the muscle groups. The accuracy of the automatic segmentation method was tested both on SCI (N = 16) and on non-disabled (N = 14) individuals, showing an overall 0.93±0.06 accuracy for adipose tissue and muscle compartments segmentation based on Dice Similarity Coefficient. The proposed framework for muscle compartment segmentation showed an overall higher accuracy compared to ANTs and STAPLE, two previously validated atlas-based segmentation methods. Also, the framework proposed in this study showed similar Dice accuracy and better Hausdorff distance measure to that obtained using DeepMedic Convolutional Neural Network structure, a well-known deep learning network for 3-D medical image segmentation. The automatic segmentation method proposed in this study can provide fast and accurate quantification of adipose and muscle tissues, which have important health and functional implications in the SCI population.
Chronic motor complete spinal cord injury (SCI) results in paralysis and deleterious neuromuscular and autonomic adaptations. Paralysed muscles demonstrate atrophy, loss of force and increased fatigability. Also, SCI-induced autonomic impairment results in persistently low resting blood pressure and heart rate, among other features. We previously reported that spinal cord epidural stimulation (scES) optimized for cardiovascular (CV) function (CV-scES), which is applied in sitting position and does not activate the leg muscles, can maintain systolic blood pressure within a normotensive range during quiet sitting and during orthostatic stress. In the present study, dualenergy X-ray absorptiometry collected from six individuals with chronic clinically motor complete SCI demonstrated that 88 ± 11 sessions of CV-scES (7 days week −1 ; 2 h day −1 in four individuals and 5 h day −1 in two individuals) over a period of ∼6 months significantly increased lower limb lean mass (by 0.67 ± 0.39 kg or 9.4 ± 8.1%; P < 0.001). Additionally, muscle strength and fatigability data elicited by neuromuscular electrical stimulation in three of these individuals demonstrated a general increase (57 ± 117%) in maximal torque output (between 2 and 44 N m in 14 of the 17 muscle groups tested overall) and torque-time integral during intermittent, fatiguing contractions (63 ± 71%; between 7 and 230% in 16 of the 17 muscle groups tested overall). In contrast, whole-body mass and composition did not change significantly. In conclusion, long-term use of CV-scES can have a significant impact on lower limb muscle properties after chronic motor complete SCI.
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