• NeuroImage. Clinical · Jan 2016

    Review

    Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI.

    • Allan R Martin, Izabela Aleksanderek, Julien Cohen-Adad, Zenovia Tarmohamed, Lindsay Tetreault, Nathaniel Smith, David W Cadotte, Adrian Crawley, Howard Ginsberg, David J Mikulis, and Michael G Fehlings.
    • Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada.
    • Neuroimage Clin. 2016 Jan 1; 10: 192-238.

    BackgroundA recent meeting of international imaging experts sponsored by the International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 state-of-the-art MRI techniques with potential to transform the field of spinal cord imaging by elucidating elements of the microstructure and function: diffusion tensor imaging (DTI), magnetization transfer (MT), myelin water fraction (MWF), MR spectroscopy (MRS), and functional MRI (fMRI). However, the progress toward clinical translation of these techniques has not been established.MethodsA systematic review of the English literature was conducted using MEDLINE, MEDLINE-in-Progress, Embase, and Cochrane databases to identify all human studies that investigated utility, in terms of diagnosis, correlation with disability, and prediction of outcomes, of these promising techniques in pathologies affecting the spinal cord. Data regarding study design, subject characteristics, MRI methods, clinical measures of impairment, and analysis techniques were extracted and tabulated to identify trends and commonalities. The studies were assessed for risk of bias, and the overall quality of evidence was assessed for each specific finding using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.ResultsA total of 6597 unique citations were identified in the database search, and after full-text review of 274 articles, a total of 104 relevant studies were identified for final inclusion (97% from the initial database search). Among these, 69 studies utilized DTI and 25 used MT, with both techniques showing an increased number of publications in recent years. The review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. Most of the studies were exploratory in nature, lacking a priori hypotheses and showing a high (72%) or moderately high (20%) risk of bias, due to issues with study design, acquisition techniques, and analysis methods. The acquisitions for each technique varied widely across studies, rendering direct comparisons of metrics invalid. The DTI metric fractional anisotropy (FA) had the strongest evidence of utility, with moderate quality evidence for its use as a biomarker showing correlation with disability in several clinical pathologies, and a low level of evidence that it identifies tissue injury (in terms of group differences) compared with healthy controls. However, insufficient evidence exists to determine its utility as a sensitive and specific diagnostic test or as a tool to predict clinical outcomes. Very low quality evidence suggests that other metrics also show group differences compared with controls, including DTI metrics mean diffusivity (MD) and radial diffusivity (RD), the diffusional kurtosis imaging (DKI) metric mean kurtosis (MK), MT metrics MT ratio (MTR) and MT cerebrospinal fluid ratio (MTCSF), and the MRS metric of N-acetylaspartate (NAA) concentration, although these results were somewhat inconsistent.ConclusionsState-of-the-art spinal cord MRI techniques are emerging with great potential to improve the diagnosis and management of various spinal pathologies, but the current body of evidence has only showed limited clinical utility to date. Among these imaging tools DTI is the most mature, but further work is necessary to standardize and validate its use before it will be adopted in the clinical realm. Large, well-designed studies with a priori hypotheses, standardized acquisition methods, detailed clinical data collection, and robust automated analysis techniques are needed to fully demonstrate the potential of these rapidly evolving techniques.

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