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Neuroimage Clin. 2015 Mar 4;7:667-77. doi: 10.1016/j.nicl.2015.02.022. eCollection 2015.

Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks.

Author information

1
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA ; Division of Medical Research, Korea Institute of Oriental Medicine, Daejeon 305-811, South Korea.
2
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.
3
Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School (HMS), Chestnut Hill, MA 02467, USA.
4
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA ; School of Medicine, Universidad de Santander, Bucaramanga, Colombia.
5
Departments of Anesthesiology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA.
6
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA ; Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School (HMS), Chestnut Hill, MA 02467, USA ; Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Yongin, 449-701, South Korea.

Abstract

Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42) and age- and sex-matched pain-free adults (N = 63). We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients.

KEYWORDS:

AAL, automated anatomical labeling; BDI, Beck depression inventory; BPI, brief pain inventory; Cerebellum; DTI, diffusion tensor imaging; FM, fibromyalgia; FSL, FMRIB software library; Fibromyalgia; HC, healthy controls; MCP, middle cerebellar peduncle; MNI, Montreal neurological institute; MRI, magnetic resonance imaging; Network; P40, the pressure level (mm Hg) for a pain intensity rating of 40/100; Pain; ROI, region of interest; SCP, superior cerebellar peduncle; SPM, statistical parametric mapping; Tractography; VBM, voxel-based morphometry; fMRI, functional MRI

PMID:
25844321
PMCID:
PMC4379388
DOI:
10.1016/j.nicl.2015.02.022
[Indexed for MEDLINE]
Free PMC Article

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