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Wednesday, March 23, 2016

Reproducibility of Resting State Connectivity in Patients with Stable Multiple Sclerosis

Abstract


Given increasing efforts to use resting-state fMRI (rfMRI) as a biomarker of disease progression in multiple sclerosis (MS) we here explored the reproducibility of longitudinal rfMRI over three months in patients with clinically and radiologically stable MS. To pursue this aim, two approaches were applied in nine rfMRI networks: First, the intraclass correlation coefficient (ICC 3,1) was assessed for the mean functional connectivity maps across the entire network and a region of interest (ROI). Second, the ratio of overlap between Z-thresholded connectivity maps for each network was assessed. We quantified between-session functional reproducibility of rfMRI for 20 patients with stable MS and 14 healthy controls (HC). Nine rfMRI networks (RSNs) were examined at baseline and after 3 months of follow-up: three visual RSNs, the default-mode network, sensorimotor-, auditory-, executive control, and the left and right fronto-parietal RSN. ROI analyses were constrained to thresholded overlap masks for each individual (Z>0) at baseline and follow-up.In both stable MS and HC mean functional connectivity across the entire network did not reach acceptable ICCs for several networks (ICC<0.40) but we found a high reproducibility of ROI ICCs and of the ratio of overlap. ROI ICCs of all nine networks were between 0.98 and 0.99 for HC and ranged from 0.88 to 0.99 in patients with MS, respectively. The ratio of overlap for all networks was similar for both groups, ranging from 0.60 to 0.75.Our findings attest to a high reproducibility of rfMRI networks not only in HC but also in patients with stable MS when applying ROI analysis. This supports the utility of rfMRI to monitor functional changes related to disease progression or therapeutic interventions in MS.

Introduction

Multiple sclerosis (MS) is an inflammatory, neurodegenerative disease [13] and the major cause for non-traumatic disability in young adults [4]. Physical and cognitive deficits of MS have been related not only to structural damage but also to functional imbalance in and between brain networks [5]. Therefore, the study of functional changes of the brain by fMRI holds great promise to better understand the pathophysiologic mechanisms of the disease and their modification by therapeutic interventions [6]. Given recent increasing propositions to use resting-state fMRI (rfMRI) as a biomarker of disease progression and to monitor and/or predict motor and cognitive function in MS [79], we here explored the reproducibility of rfMRI over three months in patients with stable MS and compared findings to healthy controls.
RfMRI allows the investigation of changes within and across multiple functional networks without bias of task performance, adherence or subject effort and is increasingly used in patient cohorts [10,11]. Independent component analysis (ICA) has emerged as a powerful tool for exploring rfMRI data in both healthy and brain-diseased populations [12].
A high test-retest reproducibility of fMRI data is a pre-requisite for their application in clinical practice and clinical populations [1315]. Comparing group activation maps is not ideal for establishing reproducibility of fMRI signals [16], as the step of statistical thresholding of images can exaggerate very small differences between maps [17]. Hence, computing intraclass correlation coefficients (ICCs) is frequently recommended to assess fMRI reproducibility [18,19].




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