UNASSIGNED: Literature examining magnetic resonance imaging (MRI) in acute @entity1566 ( @entity1566 ) has focused on cervical @entity1566 . Reproducible systems have been developed for MRI-based grading; however, it is unclear how they apply to @entity1566 . Our hypothesis is that MRI measures will group as coherent multivariate principal component (PC) ensembles, and that distinct PCs and individual variables will show discriminant validity for predicting @entity73 in @entity1566 . We undertook a retrospective cohort study of 25 @entity1 with acute @entity1566 who underwent MRI on admission and had American @entity3510 @entity73 ( @entity73 ) assessment at hospital discharge. Imaging variables of axial grade, sagittal grade, length of injury, @entity1317 ( @entity1317 ), maximum canal compromise (MCC), and maximum @entity1745 (MSCC) were collected. We performed an analytical workflow to detect multivariate PC patterns followed by explicit hypothesis testing to predict @entity73 at discharge. All imaging variables loaded positively on @entity22347 (64.3% of variance), which was highly related to @entity73 at discharge. MCC, MSCC, and @entity1317 also loaded positively on @entity16552 (22.7% of variance), while variables concerning cord signal abnormality loaded negatively on @entity16552 . @entity16552 was highly related to the @entity1 undergoing surgical decompression. Variables of signal abnormality were all negatively correlated with @entity73 at discharge with the highest level of correlation for axial grade as assessed with the Brain and @entity3510 (BASIC) score. A multiple variable model identified BASIC as the only statistically significant predictor of @entity73 at discharge, signifying that BASIC best captured the variance in @entity73 within our study population. Our study provides evidence of convergent validity, construct validity, and clinical predictive validity for the sampled MRI measures of @entity1566 when applied in acute thoracic and thoracolumbar @entity1566 .

Multidimensional Analysis of Magnetic Resonance Imaging Predicts Early Impairment in Thoracic and Thoracolumbar XXXX .

@entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity3510 :: ('MESH:D013124', 'Disease') :: ['Spinal Injury Center', 'Spinal Injury'] @entity22347 :: ('5167', 'Gene') :: ['PC1'] @entity1317 :: ('MESH:D057772', 'Disease') :: ['TLICS', 'thoracolumbar injury classification system'] @entity73 :: ('MESH:D003072', 'Disease') :: ['Association Impairment Scale', 'AIS', 'early impairment'] @entity1745 :: ('MESH:D013117', 'Disease') :: ['spinal cord compression'] @entity1566 :: ('MESH:D013119', 'Disease') :: ['spinal cord injury', 'thoracic SCI', 'SCI'] @entity16552 :: ('3854', 'Gene') :: ['PC2']
@entity1566 :: (MESH:D013119,Disease) :: ['Spinal Cord Injury']
