Fatigue in multiple sclerosis: The contribution of resting-state functional connectivity reorganization.

OBJECTIVES: To investigate resting-state functional connectivity (RS-FC) of the default-mode network (DMN) and of sensorimotor network (SMN) network in relapsing remitting (RR) multiple sclerosis (MS) patients with fatigue (F) and without fatigue(NF). METHODS: In all, 59 RRMS patients and 29 healthy controls (HC) underwent magnetic resonance imaging (MRI) protocol including resting-state fMRI (RS-fMRI). Functional connectivity of the DMN and SMN was evaluated by independent component analysis (ICA). A linear regression analysis was performed to explore whether fatigue was mainly driven by changes observed in the DMN or in the SMN. Regional gray matter atrophy was assessed by voxel-based morphometry (VBM). RESULTS: Compared to HC, F-MS patients showed a stronger RS-FC in the posterior cingulate cortex (PCC) and a reduced RS-FC in the anterior cingulated cortex (ACC) of the DMN. F-MS patients, compared to NF-MS patients, revealed (1) an increased RS-FC in the PCC and a reduced RS-FC in the ACC of the DMN and (2) an increased RS-FC in the primary motor cortex and in the supplementary motor cortex of the SMN. The regression analysis suggested that fatigue is mainly driven by RS-FC changes of the DMN. CONCLUSIONS: Fatigue in RRMS is mainly associated to a functional rearrangement of non-motor RS networks.

Reliability of quantitative magnetic susceptibility imaging metrics for cerebral cortex and major subcortical structures.

BACKGROUND AND PURPOSE: Susceptibility estimates derived from quantitative susceptibility mapping (QSM) images for the cerebral cortex and major subcortical structures are variably reported in brain magnetic resonance imaging (MRI) studies, as average of all ( µ all ${{{{\mu}}}_{{\mathrm{all}}}}$ ), absolute ( µ abs ${{{{\mu}}}_{{\mathrm{abs}}}}$ ), or positive- ( µ p ${{{{\mu}}}_{\mathrm{p}}}$ ) and negative-only ( µ n ${{{{\mu}}}_{\mathrm{n}}}$ ) susceptibility values using a region of interest (ROI) approach. This pilot study presents a reliability analysis of currently used ROI-QSM metrics and an alternative ROI-based approach to obtain voxel-weighted ROI-QSM metrics ( µ wp ${{{{\mu}}}_{{\mathrm{wp}}}}$ and µ wn ${{{{\mu}}}_{{\mathrm{wn}}}}$ ). METHODS: Ten healthy subjects underwent repeated (test-retest) 3-dimensional multi-echo gradient-echo (3DMEGE) 3 Tesla MRI measurements. Complex-valued 3DMEGE images were acquired and reconstructed with slice thicknesses of 1 and 2 mm (3DMEGE1, 3DMEGE2) along with 3DT1-weighted isometric (voxel 1 mm3) images for independent registration and ROI segmentation. Agreement, consistency, and reproducibility of ROI-QSM metrics were assessed through Bland-Altman analysis, intraclass correlation coefficient, and interscan and intersubject coefficient of variation (CoV). RESULTS: All ROI-QSM metrics exhibited good to excellent consistency and test-retest agreement with no proportional bias. Interscan CoV was higher for µ all ${{{{\mu}}}_{{\mathrm{all}}}}$ in comparison to the other metrics where it was below 15%, in both 3DMEGE1 and 3DMEGE2 datasets. Intersubject CoV for µ all ${{{{\mu}}}_{{\mathrm{all}}}}$ and µ abs ${{{{\mu}}}_{{\mathrm{abs}}}}$ exceeded 50% in all ROIs. CONCLUSIONS: Among the evaluated ROI-QSM metrics, µ all ${{{{\mu}}}_{{\mathrm{all}}}}$ and µ abs ${{{{\mu}}}_{{\mathrm{abs}}}}$ estimates were less reliable, whereas separating positive and negative values (using µ p , µ n , µ wp , µ wn ${{{{\mu}}}_{\mathrm{p}}},\ {{{{\mu}}}_{\mathrm{n}}},\ {{{{\mu}}}_{{\mathrm{wp}}}},\ {{{{\mu}}}_{{\mathrm{wn}}}}$ ) improved the reproducibility within, and the comparability between, subjects, even when reducing the slice thickness. These preliminary findings may offer valuable insights toward standardizing ROI-QSM metrics across different patient cohorts and imaging settings in future clinical MRI studies.