Chronic pain domains and their relationship to personality, abilities, and brain networks

Differential pain perception among females with or without nonspecific chronic low back pain and comorbid insomnia: a quantitative sensory testing analysis

ABSTRACT

Sleep disturbance is a prevalent condition in individuals with chronic low back pain (CLBP). Despite a strong association between the 2 conditions, the potential mechanisms underlying the role of sleep disturbance in CLBP remain unclear. This case-control study aimed to examine pain perception among females with or without nonspecific CLBP and comorbid insomnia. One hundred females were recruited (mean age: 34.3 ± 11.4 years), with 25 individuals with concomitant CLBP and insomnia (CLBP+I), 25 with CLBP (CLBP+), 25 with insomnia (Insomnia+), and 25 healthy controls. All participants completed self-report questionnaires and quantitative sensory testing (QST). Our study found that CLBP+I exhibited lower mechanical pain and pressure pain thresholds (PPT) in both painful and nonpainful areas and impaired conditioned pain modulation (CPM) as compared to healthy controls. Similar findings were found in PPT at the back and CPM when compared to CLBP+. However, no significant differences were noted in thermal pain thresholds and temporal summation of pain across the 4 groups. Furthermore, CLBP+I and Insomnia+ displayed higher levels of functional disability, maladaptive beliefs, and negative mood than CLBP+ or healthy controls. There were significant increases in pain sensitivity to pressure stimuli, decreases in descending pain inhibitory effects, and higher levels of maladaptive psychological status in CLBP+I compared to CLBP+. These findings underscore the importance of incorporating sleep assessments as a routine practice in treating CLBP cases. Future studies are warranted to validate our findings in males, establish the diagnostic and prognostic value of QST, and probe the neurophysiological mechanisms in comorbid conditions.

The Efficacy and Brain Network Mechanism of Acupuncture for Knee Osteoarthritis: A Study Protocol for Randomized Controlled Neuroimaging Trial

Purpose

Knee osteoarthritis (KOA) is a prevalent degenerative bone and joint disease observed in clinical practice. While acupuncture has demonstrated efficacy in treating KOA, the central mechanisms underlying its effects remain ambiguous. Recently, functional magnetic resonance imaging (fMRI) has been extensively applied in studying the brain mechanisms of acupuncture analgesia. Currently, network analysis based on brain connectomics is a focal point in acupuncture imaging research. Therefore, this study uses KOA as the research vehicle, focuses on the abnormal connectivity patterns of brain functional networks, and integrates clinical pain assessments to thoroughly investigate the central mechanisms of acupuncture therapeutic effects on KOA.

Patients and Methods

In this parallel, randomized, sham-controlled neuroimaging trial, 60 KOA patients will be randomly divided into the acupuncture group and sham acupuncture group in a 1:1 ratio, treated three times weekly for a total of 12 sessions. Patients will undergo clinical symptom assessments and cranial fMRI scans at baseline (-1-0 weeks), post-treatment (4 weeks), and at the follow-up (16 weeks). Forty healthy subjects will be recruited for observation, with a single MRI scan conducted only at baseline (-1-0 week). The primary efficacy indicator will be the change in NRS score after four weeks of treatment, with secondary outcomes including WOMAC, STAI, and safety assessments. fMRI observations will employ independent component analysis, brain network construction, and functional connectivity, complemented by Pearson correlation analysis to explore the relationship between brain responses and clinical improvements.

Conclusion

This study will initially uncover how acupuncture intervention for chronic KOA pain centrally regulates and exerts therapeutic effects through the modulation of abnormal brain network functional connectivity patterns, with a demonstrated long-term effect.

Ethics and Dissemination

This study has been approved by the ethics committee of Shandong University of Traditional Chinese Medicine Affiliated Hospital ((2024) Lunshen No. (028) - KY).

Clinical Trial Registration

This study has been approved by registered in the Chinese Clinical Trial Registry (ChiCTR2400083695).

Body mass index associated with respiration predicts motion in resting-state functional magnetic resonance imaging scans

Decreasing body mass index (BMI) reduces head motion in resting-state fMRI (rs-fMRI) data. Yet, the mechanism by which BMI affects head motion remains poorly understood. Understanding how BMI interacts with respiration to affect head motion can improve head motion reduction strategies. A total of 254 patients with back pain were included in this study, each of whom had two visits (interval time = 13.85 ± 7.81 weeks) during which two consecutive re-fMRI scans were obtained. We investigated the relationships between head motion and demographic and pain-related characteristics-head motion was reliable across scans and correlated with age, pain intensity, and BMI. Multiple linear regression models determined that BMI was the main determinant in predicting head motion. BMI was also associated with two features derived from respiration signal. Anterior-posterior and superior-inferior motion dominated both overall motion magnitude and the coupling between motion and respiration. BMI interacted with respiration to influence motion only in the pitch dimension. These findings indicate that BMI should be a critical parameter in both study designs and analyses of fMRI data.

The effect of psychological factors on pain outcomes: lessons learned for the next generation of research

Big data and machine learning techniques offer opportunities to investigate the effects of psychological factors on pain outcomes. Nevertheless, these advances can only deliver when the quality of the data is high and the underpinning causal assumptions are considered. We argue that there is room for improvement and identify some challenges in the evidence base concerning the effect of psychological factors on the development and maintenance of chronic pain. As a starting point, 3 basic tenets of causality are taken: (1) cause and effect differ from each other, (2) the cause precedes the effect within reasonable time, and (3) alternative explanations are ruled out. Building on these tenets, potential problems and some lessons learned are provided that the next generation of research should take into account. In particular, there is a need to be more explicit and transparent about causal assumptions in research. This will lead to better research designs, more appropriate statistical analyses, and constructive discussions and productive tensions that improve our science.

Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach

ABSTRACT

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Neuraxial drug delivery in pain management: An overview of past, present, and future

Activation of neuraxial nociceptive linkages leads to a high level of encoding of the message that is transmitted to the brain and that can initiate a pain state with its attendant emotive covariates. As we review here, the encoding of this message is subject to a profound regulation by pharmacological targeting of dorsal root ganglion and dorsal horn systems. Though first shown with the robust and selective modulation by spinal opiates, subsequent work has revealed the pharmacological and biological complexity of these neuraxial systems and points to several regulatory targets. Novel therapeutic delivery platforms, such as viral transfection, antisense and targeted neurotoxins, point to disease-modifying approaches that can selectively address the acute and chronic pain phenotype. Further developments are called for in delivery devices to enhance local distribution and to minimize concentration gradients, as frequently occurs with the poorly mixed intrathecal space. The field has advanced remarkably since the mid-1970s, but these advances must always address the issues of safety and tolerability of neuraxial therapy.