Allan R. Martin1, Izabela Aleksanderek1, Julien Cohen-Adad2, Zenovia Tarmohamed3, Lindsay Tetreault1, Nathaniel Smith4, David W. Cadotte1, Adrian Crawley5, Howard Ginsberg1, David J. Mikulis5, and Michael G. Fehlings1
1Neurosurgery, University of Toronto, Toronto, ON, Canada, 2Electrical Engineering, Polytechnique Montreal, Montreal, QC, Canada, 3Royal College of Surgeons Ireland, Dublin, Ireland, 4McMaster University, Hamilton, ON, Canada, 5Medical Imaging, University of Toronto, Toronto, ON, Canada
Synopsis
5 state-of-the-art spinal
cord MRI techniques have been identified with great clinical potential. This systematic
review finds trends in the technical methods employed and measures the progress
of these techniques toward clinical translation. 104 studies were identified,
with 69 DTI, 25 MT, 1 MWF, 11 MRS, and 8 fMRI studies. The DTI metric FA has
the strongest evidence of utility, correlating with disability in numerous spinal
conditions. 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.Purpose
A recent meeting of
international imaging experts sponsored by the International Spinal Research
Trust (ISRT) and the Wings for Life Foundation (WfL) 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).
1,2
This review was designed to identify all relevant studies, summarize trends and
commonalities of the methods employed, and determine the progress of these
techniques in terms of clinical translation.
Methods
A
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. Studies were required to include at
least 24 subjects in total and at least 12 with a specific pathological
diagnosis. Two reviewers independently performed title/abstract review,
full-text review, and data extraction, with discrepancies resolved by
discussion. 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.
Results
A 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 included (97% from the electronic
search) (Figure 1). Among these, 69 studies utilized DTI and 25 used MT, with
both techniques showing increased publications in recent years (Figure 2). The
review also identified 1 MWF study, 11 MRS studies, and 8 fMRI studies. A total
of 10 studies employed more than one advanced imaging technique, with 6
combining DTI and MT, 3 using DTI and MRS, and 1 employing DTI and fMRI. 16 of
the DTI studies performed fibre tractography and 62 extracted metrics from
regions of interest (ROIs), with 9 performed both types of analysis. Pathological
conditions studied included multiple sclerosis (MS) (43 studies), cervical
spondylotic myelopathy (CSM) (26 studies), amyotrophic lateral sclerosis (ALS)
(11 studies), chronic spinal cord injury (SCI) (7 studies), non-specific compressive
myelopathy (6 studies), non-specific myelitis (5 studies), acute SCI (3
studies), syringomyelia (3 studies), and neuro-myelitis optica (NMO) (2
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 (Table 1). 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.
Discussion
State-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. The majority of research to
date has a high risk of bias related to technical factors and a paucity of
carefully designed clinical studies. 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.
Conclusions
The
development of MRI techniques that can non-invasively characterize the
microstructure and function of the spinal cord offers the possibility of
improved diagnostic accuracy and clinical management of patients with various
neurological disorders affecting the spine. 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.
Acknowledgements
No acknowledgement found.References
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