Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study.
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.
aDivision of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA bG Oppenheimer Center for Neurobiology of Stress and Resilience, Pain and Interoception Network (PAIN), David Geffen School of Medicine at UCLA, Los Angeles, CA, USA cDepartment of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Ann Arbor, MI, USA dDepartment of Anesthesiology, Perioperative and Pain Medicine, Division of Pain Medicine, Stanford University Medical Center, Stanford, CA, USA eDepartment of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA fNeuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA gFunctional MRI Laboratory, University of Michigan, Ann Arbor, MI, USA hDepartment of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA iNational Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA.
Jason J
JJ
Kutch
Jennifer S
JS
Labus
Richard E
RE
Harris
Katherine T
KT
Martucci
Melissa A
MA
Farmer
Sonja
S
Fenske
Connor
C
Fling
Eric
E
Ichesco
Scott
S
Peltier
Bogdan
B
Petre
Wensheng
W
Guo
Xiaoling
X
Hou
Alisa J
AJ
Stephens
Chris
C
Mullins
Daniel J
DJ
Clauw
Sean C
SC
Mackey
A Vania
AV
Apkarian
J Richard
JR
Landis
Emeran A
EA
Mayer
D000328:Adult; D001921:Brain / Q000503:physiopathology*; D059350:Chronic Pain / Q000175:diagnosis / Q000503:physiopathology*; D063132:Connectome; D018450:Disease Progression; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D008297:Male; D009415:Nerve Net / Q000503:physiopathology*; D017699:Pelvic Pain / Q000175:diagnosis / Q000517:prevention & control*; D011177:Postal Service; D015203:Reproducibility of Results; D012146:Rest; D012680:Sensitivity and Specificity; D013577:Syndrome; D014570:Urologic Diseases / Q000175:diagnosis / Q000503:physiopathology*