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Objectives: Tract-based spatial statistics (TBSS) is a diffusion tensor imaging (DTI)-based processing technique that aims to improve the objectivity and interpretability of analysis of multisubject diffusion imaging studies. This study used TBSS to measure quantitative changes in brain white matter structures following spinal cord injury (SCI). Methods: Eighteen SCI subjects aged 8-20 years old (mean age, 16.5 years) were scanned using a conventional single-shot EPI DTI protocol using a 3.0T Siemens MR scanner. All participants underwent a complete International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination to determine the level and severity of injury. Five participants were classified as American Spinal Injury Association Impairment Scale (AIS) A, nine as AIS B, and four as AIS C/D. Imaging parameters used for data collection were as follows: 20 directions, b = 1000 s/mm 2 , voxel size = 1.8 mm x 1.8 mm, slice thickness = 5 mm, TE = 95 ms, TR = 4300 ms, slices = 30, TA = 4:45 min. To generate TBSS, nonparametric permutation tests were used for voxel-wise statistical analysis of the fractional anisotropy (FA) skeletons between AIS groups. A two-tailed t test was applied to extract voxels with significant differences at p < .05. Results: Notable significant changes occurred throughout the corticospinal, spinothalamic, and dorsal column/medial lemniscus tracts. Altered regions in the temporal, occipital, and parietal lobes were also identified. Conclusion: These results suggest that white matter structures are altered differently between people with different AIS classifications. TBSS has the potential to serve as a screening tool to identify white matter changes in regions of interest., Competing Interests: Conflicts of Interest Dr. Mulcahey reports grants from NINDS and from Craig H Neilsen Foundation during the conduct of the study. The other authors report no conflicts of interest., (© 2021 American Spinal Injury Association.)

Purpose: To develop ability levels and descriptions to interpret Pediatric Spinal Cord Injury Activity Measure (PEDI-SCI AM) and Pediatric Measure of Participation (PMoP) scores., Methods: Mixed-methods approach to 1.) create item maps using PEDI-SCI AM and PMoP calibration data; 2.) employ bookmarking methods and an iterative consensus process including semi-structured interviews, focus groups and surveys to establish PEDI-SCI AM and PMoP level score cut-points and descriptions; 3.) use calibration sample data to examine mean score differences across levels [analyses of variance (ANOVAs)] and assess the sample distribution (%) across levels; 4.) repeat in a separate validation sample; 5.) develop level descriptions. Throughout the mixed methods approach, the sample participants include children with spinal cord injury (SCI), parents of children with SCI, and professionals who work with children with SCI., Results: Four or five ability levels were identified for each PEDI-SCI AM and PMoP domain along with descriptions for each level. ANOVA results revealed significant overall differences for level mean scores and pairwise comparisons (p < 0.05). Consensus (>80%) was achieved for all PEDI-SCI AM and some PMoP level descriptions., Conclusion: PEDI-SCI AM and PMoP score cut-points identify different levels of activity and participation among children with SCI. These levels and descriptions provide clinical relevance for PEDI-SCI and PMoP numeric scores.

Study Design: Psychometric study., Objective: To validate the GRASSP in pediatric SCI populations and establish the lower age of test administration., Setting: United States: Pennsylvania, Maryland, Illinois, Michigan, California, Texas., Methods: Mean, SD and range of scores were calculated and examined for known-group differences. Test-retest reliability was measured by the intra-class correlation, concurrent validity of the GRASSP against the SCIM, SCIM-SS, and the CUE-Q was measured by the Spearman correlation., Results: GRASSP scores differed between participants with motor complete and incomplete injuries (p = <0.0001-0.036). Test-retest reliability was strong (ICC = 0.99). Weak correlation with the total SCIM (r = 0.33-0.66), and moderate to strong correlation with the SCIM-SC (r = 37-0.70) and CUE-Q (r = 0.40-0.84)., Conclusion: Results support the validity of the GRASSP and provide evidence that the scores are reliable when administered to children. The GRASSP sensory and strength subtests are recommended for children beginning at 6 years of age, and the GRASSP prehension performance/ability subtest for children beginning at 8 years of age. Normative data are needed for the performance components of the GRASSP.