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In peripheral quantitative computed tomography scans of the calf muscles, segmentation of muscles from subcutaneous fat is challenged by muscle fat infiltration. Threshold-based edge detection segmentation by manufacturer software fails when muscle boundaries are not smooth. This study compared the test-retest precision error for muscle-fat segmentation using the threshold-based edge detection method vs manual segmentation guided by the watershed algorithm. Three clinical populations were investigated: younger adults, older adults, and adults with spinal cord injury (SCI). The watershed segmentation method yielded lower precision error (1.18%-2.01%) and higher (p<0.001) muscle density values (70.2±9.2 mg/cm3) compared with threshold-based edge detection segmentation (1.77%-4.06% error, 67.4±10.3 mg/cm3). This was particularly true for adults with SCI (precision error improved by 1.56% and 2.64% for muscle area and density, respectively). However, both methods still provided acceptable precision with error well under 5%. Bland-Altman analyses showed that the major discrepancies between the segmentation methods were found mostly among participants with SCI where more muscle fat infiltration was present. When examining a population where fatty infiltration into muscle is expected, the watershed algorithm is recommended for muscle density and area measurement to enable the detection of smaller change effect sizes.

Background/Objective: Elevated aortic arterial stiffness (aortic pulse wave velocity: aPWV) is an independent coronary artery disease predictor among the general population. The purpose of this study was to: (1) report aPWV values in a representative cohort of patients with spinal cord injury (SCI); (2) to compare aPWV values in people with SCI based on neurological level of injury; and (3) to contrast the reported aPWV values with available normal values for the general population. Methods: Adults with chronic SCI (n = 87) were divided into two groups (TETRA group, n = 37 and PARA group, n = 50). aPWV and potential confounders of aPWV were assessed. Analysis of covariance was used for comparisons between groups and adjusted for the confounders. Subjects' aPWV values were contrasted with reference values for general population determined by "The Reference value for arterial stiffness' collaboration" and prevalence of abnormal aPWV defined as greater than or equal to the age-specific 90th percentile was reported. Results: Prevalence of abnormal aPWV in the cohort was 25.3%. After adjusting for covariates, the mean aPWV values were significantly different between two groups (TETRA: 8.0 (95% confidence interval (CI): 7.5-8.6) m/ second, PARA: 9.0 (95% CI: 8.5-9.4) m/second, P = 0.010). The prevalence of abnormal aPWV was significantly higher in the PARA group (36%) compared to the TETRA group (11%) (P = 0.012). Conclusions: One-quarter of the total cohort had an abnormal aPWV. Subjects with paraplegia had higher aPWV values and a higher frequency of abnormal aPWV than subjects with tetraplegia. Elevated aPWV in people with SCI, particularly those with paraplegia, may impart significant adverse cardiovascular consequences.