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Semin. Arthritis Rheum. · Dec 2017
ReviewMultivariate pattern analysis utilizing structural or functional MRI-In individuals with musculoskeletal pain and healthy controls: A systematic review.
- Ashley Smith, Marina López-Solà, Katie McMahon, Ashley Pedler, and Michele Sterling.
- Recover Injury Research Centre, NHMRC CRE in Recovery Following Road Traffic Injury, Menzies Health Institute QLD, Griffith University, Gold Coast Campus, Southport, Queensland 4125, Australia. Electronic address: ashley.smith@griffith.edu.au.
- Semin. Arthritis Rheum. 2017 Dec 1; 47 (3): 418-431.
ObjectiveThe purpose of this systematic review is to systematically review the evidence relating to findings generated by multivariate pattern analysis (MVPA) following structural or functional magnetic resonance imaging (fMRI) to determine if this analysis is able to: a) Discriminate between individuals with musculoskeletal pain and healthy controls, b) Predict pain perception in healthy individuals stimulated with a noxious stimulus compared to those stimulated with a non-noxious stimulus.MethodsMEDLINE, CINAHL, Embase, PEDro, Google Scholar, Cochrane library and Web of Science were systematically screened for relevant literature using different combinations of keywords regarding structural and functional MRI analysed with MVPA, both in individuals with musculoskeletal pain and healthy controls. Reference lists of included articles were hand-searched for additional literature. Eligible articles were assessed on risk of bias and reviewed by two independent researchers.ResultsThe search query returned 18 articles meeting the inclusion criteria. Methodological quality varied from poor to good. Seven studies investigated the ability of machine-learning algorithms to differentiate patient groups from healthy control participants. Overall, the review demonstrated that MVPA can discriminate between individuals with MSK pain and healthy controls with an overall accuracy ranging from 53% to 94%. Twelve studies utilized healthy control participants (using them as their own controls), during experimental pain paradigms aimed to investigate the ability of machine-learning to differentiate individuals stimulated with noxious stimuli from those stimulated with non-noxious stimuli, with 'pain' detection rates ranging from 60% to 94%. However, significant heterogeneity in patient conditions, study methodology and brain imaging techniques resulted in various findings that make study comparisons and formal conclusions challenging.ConclusionThere is preliminary and emerging evidence that MVPA analyses of structural or functional MRI are able to discriminate between patients and healthy controls, and also discriminate between noxious and non-noxious stimulation. No prospective studies were found in this review to allow determination of the prognostic or diagnostic capabilities or treatment responsiveness of these analyses. Future studies would also benefit from combining various behavioural, genotype and phenotype data into analyses to assist with development of sensitive and specific signatures that could guide future individualized patient treatment options and evaluate how treatments exert their effects.Copyright © 2017 Elsevier Inc. All rights reserved.
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