Resting-State Functional Connectivity Predicts Longitudinal Pain Symptom Change In Urologic Chronic Pelvic Pain Syndrome: A Mapp Network Study Kutch JJ1, Labus JS, Harris RE, Martucci KT, Farmer MA, Fenske S, Fling C, Ichesco E, Peltier S, Petre B, Guo W, Hou X, Stephens AJ, Mullins C, Clauw DJ, Mackey SC, Apkarian AV, Landis JR, Mayer EA; MAPP Research Network. Author information 1Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA. 2G Oppenheimer Center for Neurobiology of Stress and Resilience, Pain and Interoception Network (PAIN), David Geffen School of Medicine at UCLA, Los Angeles, CA, USA 3Department of Anesthesiology, Chronic Pain and Fatigue Research Center, University of Michigan, Ann Arbor, MI, USA. 4Department of Anesthesiology, Perioperative and Pain Medicine, Division of Pain Medicine, Stanford University Medical Center, Stanford, CA, USA. 5Department of Physiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA. 6Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA. 7Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, USA. 8Department of Biostatistics and Epidemiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 9National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA. 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 MRI (rs-fMRI) at baseline can predict longitudinal symptom change (3, 6, and 12 months post-scan) in urologic chronic pelvic pain syndrome (UCPPS). We studied 52 individuals with UCPPS (34 female, 18 male) 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). Additionally, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network (L-FPN). rs-fMRI measures appeared 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.