Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study. Issue 6 (June 2017)
- Record Type:
- Journal Article
- Title:
- Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study. Issue 6 (June 2017)
- Main Title:
- Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome
- Authors:
- Kutch, Jason J.
Labus, Jennifer S.
Harris, Richard E.
Martucci, Katherine T.
Farmer, Melissa A.
Fenske, Sonja
Fling, Connor
Ichesco, Eric
Peltier, Scott
Petre, Bogdan
Guo, Wensheng
Hou, Xiaoling
Stephens, Alisa J.
Mullins, Chris
Clauw, Daniel J.
Mackey, Sean C.
Apkarian, A. Vania
Landis, J. Richard
Mayer, Emeran A. - Abstract:
- Abstract : Abstract: Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks. AbstractAbstract : Abstract: Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks. Abstract : Supplemental Digital Content is Available in the Text.The strength of frontoparietal functional connectivity during a baseline resting-state functional resonance imaging scan predicts multimonth symptom trends in patients with urologic chronic pelvic pain syndrome. … (more)
- Is Part Of:
- Pain. Volume 158:Issue 6(2017)
- Journal:
- Pain
- Issue:
- Volume 158:Issue 6(2017)
- Issue Display:
- Volume 158, Issue 6 (2017)
- Year:
- 2017
- Volume:
- 158
- Issue:
- 6
- Issue Sort Value:
- 2017-0158-0006-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-06
- Subjects:
- Neuroimaging -- Prediction -- Chronic pain -- Urologic pain
Pain -- Periodicals
Douleur -- Périodiques
Anesthésie -- Périodiques
Pain
Electronic journals
Periodicals
Electronic journals
616.0472 - Journal URLs:
- http://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=toc&D=yrovft&AN=00006396-000000000-00000 ↗
http://www.sciencedirect.com/science/journal/03043959 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/03043959 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/03043959 ↗
http://journals.lww.com/pain/pages/default.aspx ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1097/j.pain.0000000000000886 ↗
- Languages:
- English
- ISSNs:
- 0304-3959
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6333.795000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5997.xml