Dataset Information

Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

ABSTRACT: Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state functional connectivity (rsFC) of the default mode, salience, central executive, and sensorimotor networks in chronic pain patients, but their role as predictors of treatment responsiveness has not yet been explored. In this study, we used machine learning approaches to test if pre-treatment rsFC can predict responses to both real and sham acupuncture treatments in cLBP patients. Fifty cLBP patients participated in 4?weeks of either real (N?=?24, age?=?39.0?±?12.6, 16 females) or sham acupuncture (N?=?26, age?=?40.0?±?13.7, 15 females) treatment in a single-blinded trial, and a resting-state fMRI scan prior to treatment was used in data analysis. Both real and sham acupuncture can produce significant pain reduction, with those receiving real treatment experiencing greater pain relief than those receiving sham treatment. We found that pre-treatment rsFC could predict symptom changes with up to 34% and 29% variances for real and sham treatment, respectively, and the rsFC characteristics that were significantly predictive for real and sham treatment differed. These results suggest a potential way to predict treatment responses and may facilitate the development of treatment plans that optimize time, cost, and available resources.

SUBMITTER: Tu Y

PROVIDER: S-EPMC6551557 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

Tu Yiheng Y Ortiz Ana A Gollub Randy L RL Cao Jin J Gerber Jessica J Lang Courtney C Park Joel J Wilson Georgia G Shen Wei W Chan Suk-Tak ST Wasan Ajay D AD Edwards Robert R RR Napadow Vitaly V Kaptchuk Ted J TJ Rosen Bruce B Kong Jian J

NeuroImage. Clinical 20190528

Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for cLBP are often unsatisfactory, and effectiveness varies widely across patients. Recent neuroimaging studies have demonstrated abnormal resting-state functional connectivity (rsFC) of the default mode, salience, central executive, and sensorimotor networks in chronic pain patients, but their role as predictors of treatment responsiveness has not yet been explored. In this study, we used machine le ...[more]

PMID: 31176295

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Project description:The underlying mechanism of pain reduction by acupuncture is still unclear, because acupuncture treatment involves multidimensional factors. In this study, we investigated the differential influence of acupuncture components on brain functional connectivity and on pain reduction. We used a specific form of sham acupuncture (phantom acupuncture; PHNT), which only has a needling-credibility (a belief that they were treated with real acupuncture needles), while real acupuncture (REAL) has a somatosensory needling stimulation, as well as a needling-credibility. Forty-three patients with low back pain were randomized into the REAL group (n = 25) and the PHNT group (n = 18). They underwent two pain steady-state fMRI runs implemented by a low back extension (LBE) pain model (lifting the low back using air-cuff inflation) before and after REAL or PHNT stimulation. Subjective pain ratings, perceived throughout the LBE runs due to the posture, were reported (LBEpain). The regions of interest (ROI) were (1) the main nodes of the default mode network (DMN) - the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), (2) the main nodes of the salience network (SN) - the anterior/posterior insular cortices (a/pINS), and (3) the low back-specific region of sensorimotor network (SMN), S1back. Significant reductions in LBEpain were observed in both groups (REAL = -1.02 ± 1.53, PHNT = -1.26 ± 2.20). In REAL group, decreased LBEpain was positively correlated with decreased functional connectivity between the mPFC and pINS (r = 0.58, P < 0.05). Reduced LBEpain in PHNT was negatively correlated with increased PCC-aINS connectivity (r = -0.48, P < 0.05) and tended toward positive correlation with decreased S1back-pINS connectivity (r = 0.44, P = 0.07). Our findings might suggest different brain mechanisms of observed pain reduction; REAL seems to involve detachment of the self from the sensory aspect of pain, while PHNT does to shift attention to self and disengages physical pain processing hubs. This exploratory study proposes a sham methodology to dissociate the influence of different acupuncture components in acupuncture research. Further studies need to be followed with more elaborated hypothesis, study design, and analysis considering various cognitive/affective factors for better understanding of brain mechanisms of pain reduction regarding the different acupuncture aspects.

Dataset Information

Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

Publications

Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

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