Thesis

Characterisation of musculoskeletal interactions after spinal cord injury

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Awarding institution
  • University of Strathclyde
Date of award
  • 2014
Thesis identifier
  • T13922
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Abstract
  • A well-established principle called Wolff's Law asserts that the changes in form and/or function of bone are followed by changes in its internal architecture (Frost 1994). Bone is adaptive, and its strength is dependent on its mechanical loading history. The largest loads imposed on bones are generally the result of muscular contraction (Lu et al. 1997), and thus bone adaptation is strongly linked with muscle activity. Following a complete spinal cord injury (SCI), paralysis of the lower limbs leads to rapid muscle atrophy. In time, this is followed by bone loss due to the extreme reduction in mechanical loading on the previously weight-bearing bones of the lower limbs. This research project aimed to study how early muscle atrophy could be used to predict future bone loss. Eighteen subjects with motor complete SCI were scanned using peripheral quantitative computed tomography (pQCT) at the 66% distal tibia at four separate time intervals within the first year following injury. Fully automated software was then developed which was able to segment the tissues within each scan, ultimately determining the quantities of fat, muscle, and bone. From these data, changes in tissue volume could be characterised for individual subjects. Over 12 months, fat increased by 39:2% ± 42:4, muscle decreased by 4:4% ± 17:3, and cortical bone decreased by 2:5% ± 2:3. The data further revealed that there was a positive, but weak, correlation between change in muscle CSA at 4 months post-SCI and change in cortical bone CSA at 12 months post-SCI (r = 0:27) when compared to the baseline scan; however, this value was not statistically significant. These results suggest that there may be a relationship between early muscle atrophy and future bone loss. However, future work in this area must be accomplished to support this theory.
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DOI
Date Created
  • 2014
Former identifier
  • 1042725

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