Literature DB >> 26414451

Multidimensional Analysis of Magnetic Resonance Imaging Predicts Early Impairment in Thoracic and Thoracolumbar Spinal Cord Injury.

Marc C Mabray1, Jason F Talbott1,2, William D Whetstone3,2, Sanjay S Dhall4,2, David B Phillips4,2, Jonathan Z Pan5,2, Geoffrey T Manley4,2, Jacqueline C Bresnahan4,2, Michael S Beattie4,2, Jenny Haefeli4,2, Adam R Ferguson4,2,6.   

Abstract

Literature examining magnetic resonance imaging (MRI) in acute spinal cord injury (SCI) has focused on cervical SCI. Reproducible systems have been developed for MRI-based grading; however, it is unclear how they apply to thoracic SCI. 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 early impairment in thoracic SCI. We undertook a retrospective cohort study of 25 patients with acute thoracic SCI who underwent MRI on admission and had American Spinal Injury Association Impairment Scale (AIS) assessment at hospital discharge. Imaging variables of axial grade, sagittal grade, length of injury, thoracolumbar injury classification system (TLICS), maximum canal compromise (MCC), and maximum spinal cord compression (MSCC) were collected. We performed an analytical workflow to detect multivariate PC patterns followed by explicit hypothesis testing to predict AIS at discharge. All imaging variables loaded positively on PC1 (64.3% of variance), which was highly related to AIS at discharge. MCC, MSCC, and TLICS also loaded positively on PC2 (22.7% of variance), while variables concerning cord signal abnormality loaded negatively on PC2. PC2 was highly related to the patient undergoing surgical decompression. Variables of signal abnormality were all negatively correlated with AIS at discharge with the highest level of correlation for axial grade as assessed with the Brain and Spinal Injury Center (BASIC) score. A multiple variable model identified BASIC as the only statistically significant predictor of AIS at discharge, signifying that BASIC best captured the variance in AIS within our study population. Our study provides evidence of convergent validity, construct validity, and clinical predictive validity for the sampled MRI measures of SCI when applied in acute thoracic and thoracolumbar SCI.

Entities:  

Keywords:  BASIC; MRI; T2 hyperintensity; TLICS; spinal cord injury; thoracic

Mesh:

Year:  2016        PMID: 26414451      PMCID: PMC4876497          DOI: 10.1089/neu.2015.4093

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  53 in total

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Review 3.  Common data elements for spinal cord injury clinical research: a National Institute for Neurological Disorders and Stroke project.

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Journal:  Spinal Cord       Date:  2015-02-10       Impact factor: 2.772

4.  Vascular mechanisms in the pathophysiology of human spinal cord injury.

Authors:  C H Tator; I Koyanagi
Journal:  J Neurosurg       Date:  1997-03       Impact factor: 5.115

5.  Magnetic resonance imaging related to neurologic outcome in cervical spinal cord injury.

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Journal:  Arch Phys Med Rehabil       Date:  1993-09       Impact factor: 3.966

6.  Magnetic resonance imaging of acute cervical spine trauma. Correlation with severity of neurologic injury.

Authors:  D M Schaefer; A Flanders; B E Northrup; H T Doan; J L Osterholm
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7.  Diffusion tensor imaging as a predictor of locomotor function after experimental spinal cord injury and recovery.

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Review 8.  Translational spinal cord injury research: preclinical guidelines and challenges.

Authors:  Paul J Reier; Michael A Lane; Edward D Hall; Y D Teng; Dena R Howland
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9.  Acute spinal cord injury: MR imaging at 1.5 T.

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Journal:  Radiology       Date:  1987-09       Impact factor: 11.105

10.  Longitudinal comparison of two severities of unilateral cervical spinal cord injury using magnetic resonance imaging in rats.

Authors:  Georgeta Mihai; Yvette S Nout; C Amy Tovar; Brandon A Miller; Petra Schmalbrock; Jacqueline C Bresnahan; Michael S Beattie
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Authors:  D B McCoy; J F Talbott; Michael Wilson; M D Mamlouk; J Cohen-Adad; Mark Wilson; J Narvid
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-15       Impact factor: 3.825

2.  Multivariate Analysis of MRI Biomarkers for Predicting Neurologic Impairment in Cervical Spinal Cord Injury.

Authors:  J Haefeli; M C Mabray; W D Whetstone; S S Dhall; J Z Pan; P Upadhyayula; G T Manley; J C Bresnahan; M S Beattie; A R Ferguson; J F Talbott
Journal:  AJNR Am J Neuroradiol       Date:  2016-12-22       Impact factor: 3.825

3.  Data Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data.

Authors:  Bridget E Hawkins; J Russell Huie; Carlos Almeida; Jiapei Chen; Adam R Ferguson
Journal:  J Neurotrauma       Date:  2019-03-29       Impact factor: 5.269

4.  An observation of the clinical efficacy of combining Riluzole with mannitol and hyperbaric oxygen in treating acute spinal cord injury.

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5.  A functional outcome prediction model of acute traumatic spinal cord injury based on extreme gradient boost.

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Journal:  J Orthop Surg Res       Date:  2022-10-12       Impact factor: 2.677

Review 6.  Improving Diagnostic Workup Following Traumatic Spinal Cord Injury: Advances in Biomarkers.

Authors:  Simon Schading; Tim M Emmenegger; Patrick Freund
Journal:  Curr Neurol Neurosci Rep       Date:  2021-07-16       Impact factor: 5.081

7.  Tissue bridges predict recovery after traumatic and ischemic thoracic spinal cord injury.

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  7 in total

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