Structural connectivity changes in the cerebral pain matrix in burning mouth syndrome: a multi-shell, multi-tissue-constrained spherical deconvolution model analysis.

Purpose: Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome. Previous studies have attempted to determine the brain connectivity features in BMS using functional and structural magnetic resonance imaging. However, no study has investigated the structural connectivity using multi-shell...

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Publicado en:Neuroradiology Vol. 63; no. 12; pp. 2005 - 2013
Autores principales: Kurokawa, Ryo, Kamiya, Kouhei, Inui, Shohei, Kato, Shimpei, Suzuki, Fumio, Amemiya, Shiori, Shinozaki, Takahiro, Takanezawa, Daiki, Kohashi, Ryutarou, Abe, Osamu
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Dec2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2021
      vid: 63
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00234-021-02732-9
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        atl: Structural connectivity changes in the cerebral pain matrix in burning mouth syndrome: a multi-shell, multi-tissue-constrained spherical deconvolution model analysis.
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        au:
          Kurokawa, Ryo
          Kamiya, Kouhei
          Inui, Shohei
          Kato, Shimpei
          Suzuki, Fumio
          Amemiya, Shiori
          Shinozaki, Takahiro
          Takanezawa, Daiki
          Kohashi, Ryutarou
          Abe, Osamu
        affil: Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
      sug:
        subj:
          Burning Mouth Syndrome
          Pain
          Brain
          Magnetic Resonance Imaging
          Human
          Matched Case Control
          Algorithms
          T-Tests
          Amygdala
          Frontal Lobe
      ab: Purpose: Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome. Previous studies have attempted to determine the brain connectivity features in BMS using functional and structural magnetic resonance imaging. However, no study has investigated the structural connectivity using multi-shell, multi-tissue-constrained spherical deconvolution (MSMT-CSD), anatomically constrained tractography (ACT), and spherical deconvolution informed filtering of tractograms (SIFT). Therefore, this study aimed to assess the differences in brain structural connectivity of patients with BMS and healthy controls using probabilistic tractography with these methods, and graph analysis. Methods: Fourteen patients with BMS and 11 age- and sex-matched healthy volunteers underwent 3-T magnetic resonance imaging. MSMT-CSD-based probabilistic structural connectivity was computed using the second-order integration over fiber orientation distributions algorithm based on nodes set in 84 anatomical cortical regions with ACT and SIFT. A t-test was performed for comparisons between the BMS and healthy control brain networks. Results: The betweenness centrality was significantly higher in the left insula, right amygdala, and right lateral orbitofrontal cortex and significantly lower in the right inferotemporal cortex in the BMS group than that in healthy controls. However, no significant difference was found in the clustering coefficient, node degree, and small-worldness between the two groups. Conclusion: Graph analysis of brain probabilistic structural connectivity, based on diffusion imaging using an MSMT-CSD model with ACT and SIFT, revealed alterations in the regions comprising the pain matrix and medial pain ascending pathway. These results highlight the emotional-affective profile of BMS, which is a type of chronic pain syndrome.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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