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. 2017 Dec 21:18:15-30.
doi: 10.1016/j.nicl.2017.12.029. eCollection 2018.

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

Karina Tatu  1 , Tommaso Costa  2 , Andrea Nani  3 , Matteo Diano  4 , Danilo G Quarta  5 , Sergio Duca  6 , A Vania Apkarian  7 , Peter T Fox  8 , Franco Cauda  1
Affiliations

How do morphological alterations caused by chronic pain distribute across the brain? A meta-analytic co-alteration study

Karina Tatu et al. Neuroimage Clin. .

Abstract
in English, Italian

•In chronic pain, gray matter (GM) alterations are not distributed randomly across the brain.•The pattern of co-alterations resembles that of brain connectivity.•The alterations' distribution partly rely on the pathways of functional connectivity.•This method allows us to identify tendencies in the distribution of GM co-alteration related to chronic pain.

It was recently suggested that in brain disorders neuronal alterations does not occur randomly, but tend to form patterns that resemble those of cerebral connectivity. Following this hypothesis, we studied the network formed by co-altered brain regions in patients with chronic pain. We used a meta-analytical network approach in order to: i) find out whether the neuronal alterations distribute randomly across the brain; ii) find out (in the case of a non-random pattern of distribution) whether a disease-specific pattern of brain co-alterations can be identified and characterized in terms of altered areas (nodes) and propagation links between them (edges); iii) verify whether the co-alteration pattern overlaps with the pattern of functional connectivity; iv) describe the topological properties of the co-alteration network and identify the highly connected nodes that are supposed to have a pre-eminent role in the diffusion timing of neuronal alterations across the brain. Our results indicate that: i) gray matter (GM) alterations do not occur randomly; ii) a symptom-related pattern of structural co-alterations can be identified for chronic pain; iii) this co-alteration pattern resembles the pattern of brain functional connectivity; iv) within the co-alteration network a set of highly connected nodes can be identified.This study provides further support to the hypothesis that neuronal alterations may spread according to the logic of a network-like diffusion suggesting that this type of distribution may also apply to chronic pain.

Keywords: Chronic pain; Co-alteration network; Network analysis; Neuronal alterations; Pathoconnectomics; Voxel-based morphometry.

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Figures

Fig. 1
Fig. 1
Workflow pipeline.
Fig. 2
Fig. 2
GM anatomical likelihood estimation results. MRI alterations (i.e., gray matter increase/decrease) identified meta-analytically in chronic pain patients. The illustration summarizes the results of the anatomical likelihood estimation (ALE) analysis of all the papers involved in this study. ALE maps were computed at a FDR corrected threshold of p < 0.05, with a minimum cluster size of k > 100 mm3. Colors from red to yellow show gray matter increases, colors from blue to green show gray matter decreases. Images are shown using the right-left radiologic convention and standard Talairach space. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 3
Fig. 3
Spherical ROIs (nodes) representing regions of GM decrease (a) and GM increase (b).
Fig. 4
Fig. 4
Functional connectivity and co-alteration networks for a) GM decrease and b) GM increase.
Fig. 5
Fig. 5
Highest degree areas in the co-alteration network. For each highly connected node, the figure shows the total number of connections, the number of inter-hemispheric connections, and the number of intra-hemispheric connections.
Fig. 6
Fig. 6
Gray matter co-alteration network. The nodes represent regions of gray matter decrease. The size and color of the nodes reflect their degree value. Small sizes correspond to low degrees.
Fig. 7
Fig. 7
Gray matter co-alteration network. The nodes represent regions of gray matter increase. The size and color of the nodes reflect their degree value. Small sizes correspond to low degrees.
Fig. 8
Fig. 8
Gray matter co-alteration network for both GM decrease and GM increase. The size and color of the nodes reflect their degree values. Small sizes correspond to low degree values. r: right; l: left.
Fig. 9
Fig. 9
Graphical illustration of nodes corresponding to GM decrease. Nodes with the same degree value are arranged at the same level. Highest degree nodes are at the top of the figure and lowest degree nodes are at the bottom. r: right; l: left.
Fig. 10
Fig. 10
GM decrease. Graphical illustration of highly connected nodes with their intra- and inter-hemispheric connections and their first neighbors.
See this image and copyright information in PMC

References

    1. Abdelnour F., Voss H.U., Raj A. Network diffusion accurately models the relationship between structural and functional brain connectivity networks. NeuroImage. 2014;90:335–347. - PMC - PubMed
    1. Agostini A., Benuzzi F., Filippini N., Bertani A., Scarcelli A., Farinelli V., Marchetta C., Calabrese C., Rizzello F., Gionchetti P., Ercolani M., Campieri M., Nichelli P. New insights into the brain involvement in patients with Crohn's disease: a voxel-based morphometry study. Neurogastroenterol. Motil. 2013;25(2):147–e182. - PubMed
    1. Apkarian A.V. The brain in chronic pain: clinical implications. Pain Manag. 2011;1:577–586. - PMC - PubMed
    1. Apkarian A.V., Sosa Y., Sonty S., Levy R.M., Harden R.N., Parrish T.B., Gitelman D.R. Chronic back pain is associated with decreased prefrontal and thalamic gray matter density. J. Neurosci. 2004;24:10410–10415. - PMC - PubMed
    1. Apkarian A.V., Hashmi J.A., Baliki M.N. Pain and the brain: specificity and plasticity of the brain in clinical chronic pain. Pain. 2011;152:S49–64. - PMC - PubMed

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