Literature DB >> 23480586

Conventional MRI as a diagnostic and prognostic tool in spinal cord injury: a systemic review of its application to date and an overview on emerging MRI methods.

David W Cadotte1, Jefferson R Wilson, David Mikulis, Patrick W Stroman, Sinead Brady, Michael G Fehlings.   

Abstract

INTRODUCTION: The diagnosis and prognosis of traumatic spinal cord injury has historically relied on clinical examination whereby those presenting with severe injuries were deemed unlikely to recover and those presenting with mild injuries were deemed more likely to recover. With the widespread use of MRI to visualize traumatic injury to the spinal cord, a spectrum of previously unseen characteristics ranging from mild T2-weighted signal intensity to complete spinal cord transection is now available to aid in both the diagnosis and prognosis. AREAS COVERED: In this systematic review, the authors outline how clinical examination (using the American Spinal Injury Association standards) and MRI characteristics can be used to classify and characterize acute traumatic cervical spinal cord injury. The reader will gain an appreciation for the different magnetic resonance signal characteristics that can be used to predict a favorable or unfavorable prognosis following traumatic spinal cord injury. The accuracy of this information, in terms of sensitivity and specificity, is presented. Using likelihood ratios, the authors work through specific examples. EXPERT OPINION: The use of MRI in the evaluation of the human spinal cord has aided our understanding of the condition significantly. However, there are still several challenges that need to be met, in particular the use of MRI to detect functional abnormalities as well as structural ones. In the coming years, our ability to define damaged circuits in the spinal cord will mean that it will be possible to link structure to function in an objective non-invasive way, which will have implications for the understanding and potential treatment of spinal cord injury.

Entities:  

Year:  2011        PMID: 23480586     DOI: 10.1517/17530059.2011.556111

Source DB:  PubMed          Journal:  Expert Opin Med Diagn        ISSN: 1753-0059


  5 in total

1.  A clinical prediction model for long-term functional outcome after traumatic spinal cord injury based on acute clinical and imaging factors.

Authors:  Jefferson R Wilson; Robert G Grossman; Ralph F Frankowski; Alexander Kiss; Aileen M Davis; Abhaya V Kulkarni; James S Harrop; Bizhan Aarabi; Alexander Vaccaro; Charles H Tator; Marcel Dvorak; Christopher I Shaffrey; Susan Harkema; James D Guest; Michael G Fehlings
Journal:  J Neurotrauma       Date:  2012-07-31       Impact factor: 5.269

2.  Diffusion tensor imaging as a predictor of locomotor function after experimental spinal cord injury and recovery.

Authors:  Brian J Kelley; Noam Y Harel; Chang-Yeon Kim; Xenophon Papademetris; Daniel Coman; Xingxing Wang; Omar Hasan; Adam Kaufman; Ronen Globinsky; Lawrence H Staib; William B J Cafferty; Fahmeed Hyder; Stephen M Strittmatter
Journal:  J Neurotrauma       Date:  2014-07-08       Impact factor: 5.269

3.  Early Intravenous Infusion of Mesenchymal Stromal Cells Exerts a Tissue Source Age-Dependent Beneficial Effect on Neurovascular Integrity and Neurobehavioral Recovery After Traumatic Cervical Spinal Cord Injury.

Authors:  Reaz Vawda; Anna Badner; James Hong; Mirriam Mikhail; Alam Lakhani; Rachel Dragas; Kristiana Xhima; Tanya Barretto; Clifford L Librach; Michael G Fehlings
Journal:  Stem Cells Transl Med       Date:  2019-03-26       Impact factor: 6.940

4.  Metabolic changes in the spinal cord after brachial plexus root re-implantation.

Authors:  Carolina Kachramanoglou; Enrico De Vita; David L Thomas; Claudia A M Wheeler-Kingshott; Evelyne Balteau; Thomas Carlstedt; David Choi; Alan J Thompson; Olga Ciccarelli
Journal:  Neurorehabil Neural Repair       Date:  2012-09-06       Impact factor: 3.919

5.  Clinical Predictors of Neurological Outcome within 72 h after Traumatic Cervical Spinal Cord Injury.

Authors:  Zhi Qiu; Fangyong Wang; Yi Hong; Junwei Zhang; Hehu Tang; Xiang Li; Shudong Jiang; Zhen Lv; Shujia Liu; Shizheng Chen; Jiesheng Liu
Journal:  Sci Rep       Date:  2016-12-12       Impact factor: 4.379

  5 in total

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