• Benedikt Sundermann, Markus Burgmer, Esther Pogatzki-Zahn, Markus Gaubitz, Christoph Stüber, Erik Wessolleck, Gereon Heuft, and Bettina Pfleiderer.
• Department of Clinical Radiology, University Hospital Münster, Albert-Schweitzer-Campus 1, Gebäude A1, 48149 Münster, North Rhine-Westphalia, Germany. Electronic address: benedikt.sundermann@ukmuenster.de.
• Acad Radiol. 2014 Mar 1; 21 (3): 369-77.

Rationale And ObjectivesThe combination of functional magnetic resonance imaging (fMRI) of the brain with multivariate pattern analysis (MVPA) has been proposed as a possible diagnostic tool. Goal of this investigation was to identify potential functional connectivity (FC) differences in the salience network (SN) and default mode network (DMN) between fibromyalgia syndrome (FMS), rheumatoid arthritis (RA), and controls (HC) and to evaluate the diagnostic applicability of derived pattern classification approaches.Materials And MethodsThe resting period during an fMRI examination was retrospectively analyzed in women with FMS (n = 17), RA (n = 16), and HC (n = 17). FC was calculated for SN and DMN subregions. Classification accuracies of discriminative MVPA models were evaluated with cross-validation: (1) inferential test of a single method, (2) explorative model optimization.ResultsNo inferentially tested model was able to classify subjects with statistically significant accuracy. However, the diagnostic ability for the differential diagnostic problem exhibited a trend to significance (accuracy: 69.7%, P = .086). Optimized models in the explorative analysis reached accuracies up to 73.5% (FMS vs. HC), 78.8% (RA vs. HC), and 78.8% (FMS vs. RA) whereas other models performed at or below chance level. Comparable support vector machine approaches performed above average for all three problems.ConclusionsObserved accuracies are not sufficient to reliably differentiate between FMS and RA for diagnostic purposes. However, some indirect evidence in support of the feasibility of this approach is provided. This exploratory analysis constitutes a fundamental model optimization effort to be based on in further investigations.Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

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