Abnormal medial prefrontal cortex functional connectivity and its association with clinical symptoms in chronic low back pain

被引:107
作者
Tu, Yiheng [1 ,2 ]
Jung, Minyoung [1 ]
Gollub, Randy L. [1 ]
Napadow, Vitaly [2 ]
Gerber, Jessica [2 ]
Ortiz, Ana [1 ]
Lang, Courtney [1 ]
Mawla, Ishtiaq [1 ]
Shen, Wei [1 ]
Chan, Suk-Tak [2 ]
Wasan, Ajay D. [3 ]
Edwards, Robert R. [4 ]
Kaptchuk, Ted J. [5 ]
Rosen, Bruce [2 ]
Kong, Jian [1 ,2 ]
机构
[1] Harvard Med Sch, Massachusetts Gen Hosp, Dept Psychiat, Charlestown, MA USA
[2] Harvard Med Sch, Martinos Ctr Biomed Imaging, Massachusetts Gen Hosp, Dept Radiol, Charlestown, MA USA
[3] Univ Pittsburgh, Ctr Pain Res, Dept Anesthesiol, Pittsburgh, PA USA
[4] Harvard Med Sch, Brigham & Womens Hosp, Dept Anesthesiol Perioperat & Pain Med, Boston, MA 02115 USA
[5] Harvard Med Sch, Beth Israel Deaconess Med Ctr, Program Placebo Studies & Therapeut Encounter, Boston, MA 02115 USA
基金
美国国家卫生研究院;
关键词
Chronic low back pain; Multivariate pattern analysis; Medial prefrontal cortex; Rostral anterior cingulate cortex; Clinical symptoms; DEFAULT-MODE NETWORK; RESPONSE-INHIBITION; BRAIN CONNECTIVITY; IMAGING BIOMARKERS; SIGNAL REGRESSION; HEALTHY CONTROLS; CLASSIFICATION; DISEASE; ACUPUNCTURE; ACTIVATION;
D O I
10.1097/j.pain.0000000000001507
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Accumulating evidence has shown that complicated brain systems are involved in the development and maintenance of chronic low back pain (cLBP), but the association between brain functional changes and clinical outcomes remains unclear. Here, we used resting-state functional magnetic resonance imaging (fMRI) and multivariate pattern analysis to identify abnormal functional connectivity (FC) between the default mode, sensorimotor, salience, and central executive brain networks in cLBP and tested whether abnormal FCs are related to pain and comorbid symptoms. Fifty cLBP patients and 44 matched healthy controls (HCs) underwent an fMRI scan, from which brain networks were identified by independent component analysis. Multivariate pattern analysis, graph theory approaches, and correlation analyses were applied to find abnormal FCs that were associated with clinical symptoms. Findings were validated on a second cohort of 30 cLBP patients and 30 matched HCs. Results showed that the medial prefrontal cortex/rostral anterior cingulate cortex had abnormal FCs with brain regions within the default mode network and with other brain networks in cLBP patients. These altered FCs were also correlated with pain duration, pain severity, and pain interference. Finally, we found that resting-state FC could discriminate cLBP patients from HCs with 91% accuracy in the first cohort and 78% accuracy in the validation cohort. Our findings suggest that the medial prefrontal cortex/rostral anterior cingulate cortex may be an important hub for linking the default mode network with the other 3 networks in cLBP patients. Elucidating the altered FCs and their association with clinical outcomes will enhance our understanding of the pathophysiology of cLBP and may facilitate the development of pain management approaches.
引用
收藏
页码:1308 / 1318
页数:11
相关论文
共 71 条
[41]   Current challenges in translational pain research [J].
Mao, Jianren .
TRENDS IN PHARMACOLOGICAL SCIENCES, 2012, 33 (11) :568-573
[42]   Neuroimaging of Pain Human Evidence and Clinical Relevance of Central Nervous System Processes and Modulation [J].
Martucci, Katherine T. ;
Mackey, Sean C. .
ANESTHESIOLOGY, 2018, 128 (06) :1241-1254
[43]   The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? [J].
Murphy, Kevin ;
Birn, Rasmus M. ;
Handwerker, Daniel A. ;
Jones, Tyler B. ;
Bandettini, Peter A. .
NEUROIMAGE, 2009, 44 (03) :893-905
[44]   Intrinsic Brain Connectivity in Fibromyalgia Is Associated With Chronic Pain Intensity [J].
Napadow, Vitaly ;
LaCount, Lauren ;
Park, Kyungmo ;
As-Sanie, Sawsan ;
Clauw, Daniel J. ;
Harris, Richard E. .
ARTHRITIS AND RHEUMATISM, 2010, 62 (08) :2545-2555
[45]   Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review [J].
Orru, Graziella ;
Pettersson-Yeo, William ;
Marquand, Andre F. ;
Sartori, Giuseppe ;
Mechelli, Andrea .
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2012, 36 (04) :1140-1152
[46]   Machine learning classifiers and fMRI: A tutorial overview [J].
Pereira, Francisco ;
Mitchell, Tom ;
Botvinick, Matthew .
NEUROIMAGE, 2009, 45 (01) :S199-S209
[47]   Evidence for Hubs in Human Functional Brain Networks [J].
Power, Jonathan D. ;
Schlaggar, Bradley L. ;
Lessov-Schlaggar, Christina N. ;
Petersen, Steven E. .
NEURON, 2013, 79 (04) :798-813
[48]   Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion [J].
Power, Jonathan D. ;
Barnes, Kelly A. ;
Snyder, Abraham Z. ;
Schlaggar, Bradley L. ;
Petersen, Steven E. .
NEUROIMAGE, 2012, 59 (03) :2142-2154
[49]   The indirect pathway of the nucleus accumbens shell amplifies neuropathic pain [J].
Ren, Wenjie ;
Centeno, Maria Virginia ;
Berger, Sara ;
Wu, Ying ;
Na, Xiaodong ;
Liu, Xianguo ;
Kondapalli, Jyothisri ;
Apkarian, A. Vania ;
Martina, Marco ;
Surmeier, D. James .
NATURE NEUROSCIENCE, 2016, 19 (02) :220-+
[50]   Complex network measures of brain connectivity: Uses and interpretations [J].
Rubinov, Mikail ;
Sporns, Olaf .
NEUROIMAGE, 2010, 52 (03) :1059-1069