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Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study.

Publication ,  Journal Article
Bagarinao, E; Johnson, KA; Martucci, KT; Ichesco, E; Farmer, MA; Labus, J; Ness, TJ; Harris, R; Deutsch, G; Apkarian, VA; Mayer, EA; Clauw, DJ ...
Published in: Pain
December 2014

Neuroimaging studies have shown that changes in brain morphology often accompany chronic pain conditions. However, brain biomarkers that are sensitive and specific to chronic pelvic pain (CPP) have not yet been adequately identified. Using data from the Trans-MAPP Research Network, we examined the changes in brain morphology associated with CPP. We used a multivariate pattern classification approach to detect these changes and to identify patterns that could be used to distinguish participants with CPP from age-matched healthy controls. In particular, we used a linear support vector machine (SVM) algorithm to differentiate gray matter images from the 2 groups. Regions of positive SVM weight included several regions within the primary somatosensory cortex, pre-supplementary motor area, hippocampus, and amygdala were identified as important drivers of the classification with 73% overall accuracy. Thus, we have identified a preliminary classifier based on brain structure that is able to predict the presence of CPP with a good degree of predictive power. Our regional findings suggest that in individuals with CPP, greater gray matter density may be found in the identified distributed brain regions, which are consistent with some previous investigations in visceral pain syndromes. Future studies are needed to improve upon our identified preliminary classifier with integration of additional variables and to assess whether the observed differences in brain structure are unique to CPP or generalizable to other chronic pain conditions.

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Published In

Pain

DOI

EISSN

1872-6623

Publication Date

December 2014

Volume

155

Issue

12

Start / End Page

2502 / 2509

Location

United States

Related Subject Headings

  • Surveys and Questionnaires
  • Psychiatric Status Rating Scales
  • Pelvic Pain
  • Middle Aged
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Follow-Up Studies
  • Female
  • Chronic Pain
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bagarinao, E., Johnson, K. A., Martucci, K. T., Ichesco, E., Farmer, M. A., Labus, J., … Mackey, S. (2014). Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study. Pain, 155(12), 2502–2509. https://doi.org/10.1016/j.pain.2014.09.002
Bagarinao, Epifanio, Kevin A. Johnson, Katherine T. Martucci, Eric Ichesco, Melissa A. Farmer, Jennifer Labus, Timothy J. Ness, et al. “Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study.Pain 155, no. 12 (December 2014): 2502–9. https://doi.org/10.1016/j.pain.2014.09.002.
Bagarinao E, Johnson KA, Martucci KT, Ichesco E, Farmer MA, Labus J, et al. Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study. Pain. 2014 Dec;155(12):2502–9.
Bagarinao, Epifanio, et al. “Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study.Pain, vol. 155, no. 12, Dec. 2014, pp. 2502–09. Pubmed, doi:10.1016/j.pain.2014.09.002.
Bagarinao E, Johnson KA, Martucci KT, Ichesco E, Farmer MA, Labus J, Ness TJ, Harris R, Deutsch G, Apkarian VA, Mayer EA, Clauw DJ, Mackey S. Preliminary structural MRI based brain classification of chronic pelvic pain: A MAPP network study. Pain. 2014 Dec;155(12):2502–2509.

Published In

Pain

DOI

EISSN

1872-6623

Publication Date

December 2014

Volume

155

Issue

12

Start / End Page

2502 / 2509

Location

United States

Related Subject Headings

  • Surveys and Questionnaires
  • Psychiatric Status Rating Scales
  • Pelvic Pain
  • Middle Aged
  • Magnetic Resonance Imaging
  • Image Processing, Computer-Assisted
  • Humans
  • Follow-Up Studies
  • Female
  • Chronic Pain