Multivariate classification of structural MRI data detects chronic low back pain

An approach to the detection of pain from autonomic and cortical correlates

OBJECTIVE

To assess the value of combining brain and autonomic measures to discriminate the subjective perception of pain from other sensory-cognitive activations.

METHODS

20 healthy individuals received 2 types of tonic painful stimulation delivered to the hand: electrical stimuli and immersion in 10 Celsius degree (°C) water, which were contrasted with non-painful immersion in 15 °C water, and stressful cognitive testing. High-density electroencephalography (EEG) and autonomic measures (pupillary, electrodermal and cardiovascular) were continuously recorded, and the accuracy of pain detection based on combinations of electrophysiological features was assessed using machine learning procedures.

RESULTS

Painful stimuli induced a significant decrease in contralateral EEG alpha power. Cardiac, electrodermal and pupillary reactivities occurred in both painful and stressful conditions. Classification models, trained on leave-one-out cross-validation folds, showed low accuracy (61-73%) of cortical and autonomic features taken independently, while their combination significantly improved accuracy to 93% in individual reports.

CONCLUSIONS

Changes in cortical oscillations reflecting somatosensory salience and autonomic changes reflecting arousal can be triggered by many activating signals other than pain; conversely, the simultaneous occurrence of somatosensory activation plus strong autonomic arousal has great probability of reflecting pain uniquely.

SIGNIFICANCE

Combining changes in cortical and autonomic reactivities appears critical to derive accurate indexes of acute pain perception.

Gray matter volume of limbic brain structures during the development of chronic back pain: a longitudinal cohort study

ABSTRACT

This study set out to investigate in a population-based longitudinal cohort, whether chronification of back pain (BP) is related to structural gray matter changes in corticolimbic brain structures. Gray matter volume (GMV) was measured in participants with chronic BP (CBP, n = 168) and controls without chronic pain (n = 323) at 2 time points with an interval of 7 years (baseline t1, follow-up t2). Over this time period, participants with CBP showed an increase of GMV in the left ventral striatum, whereas controls showed a decrease. By contrast, participants with CBP had a GMV decrease in the left parahippocampal gyrus. Within the CBP group, pain duration was negatively associated with GMV in the left caudate. Those with emerging CBP had less GMV in the right entorhinal area, right amygdala, and left medial frontal cortex. Additional variables differing between those who had BP at t1 and later developed CBP or not were pain intensity, body mass index, and depression score. In sum, these findings are in accordance with the notion that limbic brain properties are both predisposing risk factors and drivers of brain reorganization during the development of CBP.

Sensorimotor Integration in Chronic Low Back Pain

OBJECTIVE

Chronic low back pain (CLBP) impacts on spine movement. Altered sensorimotor integration can be involved. Afferents from the lumbo-pelvic area might be processed differently in CLBP and impact on descending motor control. This study aimed to determine whether afferents influence the corticomotor control of paravertebral muscles in CLBP. Fourteen individuals with CLBP (11 females) and 13 pain-free controls (8 females) were tested with transcranial magnetic stimulation (TMS) to measure the motor-evoked potential [MEP] amplitude of paravertebral muscles. Noxious and non-noxious electrical stimulation, and magnetic stimulation in the lumbo-sacral area were used as afferent stimuli and triggered 20 to 200 ms prior to TMS. EMG modulation elicited by afferent stimulation alone was measured to control net motoneuron excitability. MEP/EMG ratio was used as a measure of corticospinal excitability with control of net motoneuron excitability. MEP/EMG ratio was larger at 60, 80 and 100-ms intervals in CLBP compared to controls, and afferent stimulations alone reduced EMG amplitude greater in CLBP than controls at 100 ms. Our results suggest alteration in sensorimotor integration in CLBP highlighted by a greater facilitation of the descending corticospinal input to paravertebral muscles. Our results can help to optimise interventions by better targeting mechanisms.

Bibliometric analysis of functional magnetic resonance imaging studies on chronic pain over the past 20 years

PURPOSE

The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain.

METHODS

All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023.

RESULTS

A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain.

CONCLUSIONS

This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain.

Altered cortical thickness and structural covariance networks in chronic low back pain

BACKGROUND

Despite regional brain structural changes having been reported in patients with chronic low back pain (CLBP), the topological properties of structural covariance networks (SCNs), which refer to the organization of the SCNs, remain unclear. This study applied graph theoretical analysis to explore the alterations of the topological properties of SCNs, aiming to comprehend the integration and separation of SCNs in patients with CLBP.

METHODS

A total of 38 patients with CLBP and 38 healthy controls (HCs), balanced for age and sex, were scanned using three-dimensional T1-weighted magnetic resonance imaging. The cortical thickness was extracted from 68 brain regions, according to the Desikan-Killiany atlas, and used to reconstruct the SCNs. Subsequently, graph theoretical analysis was employed to evaluate the alterations of the topological properties in the SCNs of patients with CLBP.

RESULTS

In comparison to HCs, patients with CLBP had less cortical thickness in the left superior frontal cortex. Additionally, the cortical thickness of the left superior frontal cortex was negatively correlated with the Visual Analogue Scale scores of patients with CLBP. Furthermore, patients with CLBP, relative to HCs, exhibited lower global efficiency and small-worldness, as well as a longer characteristic path length. This indicates a decline in the brain's capacity to transmit and process information, potentially impacting the processing of pain signals in patients with CLBP and contributing to the development of CLBP. In contrast, there were no significant differences in the clustering coefficient, local efficiency, nodal efficiency, nodal betweenness centrality, or nodal degree between the two groups.

CONCLUSIONS

From the regional cortical thickness to the complex brain network level, our study demonstrated changes in the cortical thickness and topological properties of the SCNs in patients with CLBP, thus aiding in a better understanding of the pathophysiological mechanisms of CLBP.

Degree centrality-based resting-state functional magnetic resonance imaging explores central mechanisms in lumbar disc herniation patients with chronic low back pain

Objective

To investigate the central mechanism of lumbar disc herniation in patients with chronic low back pain (LDHCP) using resting-state functional magnetic resonance imaging (rs-fMRI) utilizing the Degree Centrality (DC) method.

Methods

Twenty-five LDHCP and twenty-two healthy controls (HCs) were enrolled, and rs-fMRI data from their brains were collected. We compared whole-brain DC values between the LDHCP and HC groups, and examined correlations between DC values within the LDHCP group and the Visual Analogue Score (VAS), Oswestry Dysfunction Index (ODI), and disease duration. Diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curve analysis.

Results

LDHCP patients exhibited increased DC values in the bilateral cerebellum and brainstem, whereas decreased DC values were noted in the left middle temporal gyrus and right post-central gyrus when compared with HCs. The DC values of the left middle temporal gyrus were positively correlated with VAS (r = 0.416, p = 0.039) and ODI (r = 0.405, p = 0.045), whereas there was no correlation with disease duration (p > 0.05). Other brain regions showed no significant correlations with VAS, ODI, or disease duration (p > 0.05). Furthermore, the results obtained from ROC curve analysis demonstrated that the Area Under the Curve (AUC) for the left middle temporal gyrus was 0.929.

Conclusion

The findings indicated local abnormalities in spontaneous neural activity and functional connectivity in the bilateral cerebellum, bilateral brainstem, left middle temporal gyrus, and right postcentral gyrus among LDHCP patients.

Pathology of pain and its implications for therapeutic interventions

Pain is estimated to affect more than 20% of the global population, imposing incalculable health and economic burdens. Effective pain management is crucial for individuals suffering from pain. However, the current methods for pain assessment and treatment fall short of clinical needs. Benefiting from advances in neuroscience and biotechnology, the neuronal circuits and molecular mechanisms critically involved in pain modulation have been elucidated. These research achievements have incited progress in identifying new diagnostic and therapeutic targets. In this review, we first introduce fundamental knowledge about pain, setting the stage for the subsequent contents. The review next delves into the molecular mechanisms underlying pain disorders, including gene mutation, epigenetic modification, posttranslational modification, inflammasome, signaling pathways and microbiota. To better present a comprehensive view of pain research, two prominent issues, sexual dimorphism and pain comorbidities, are discussed in detail based on current findings. The status quo of pain evaluation and manipulation is summarized. A series of improved and innovative pain management strategies, such as gene therapy, monoclonal antibody, brain-computer interface and microbial intervention, are making strides towards clinical application. We highlight existing limitations and future directions for enhancing the quality of preclinical and clinical research. Efforts to decipher the complexities of pain pathology will be instrumental in translating scientific discoveries into clinical practice, thereby improving pain management from bench to bedside.

Changes in brain structure and function during early aging in patients with chronic low back pain

Objective

To explore the structural and functional changes in cognition-related brain regions in patients with chronic low back pain (CLBP) at earlier ages, and explore the impact of the interaction between CLBP and age on the brain.

Methods

Seventy-six patients with CLBP were recruited and divided into "younger" age group (20-29 years, YA), "middle" age group (30-39 years, MA), and "older" age group (40-49 years, OA). All patients underwent functional magnetic resonance imaging (fMRI) as well as clinical psychological and pain-related symptoms assessments.

Results

Structural analysis showed that patients in OA group had lower gray matter (GM) volumes in the orbitofrontal cortex (OFC) bilaterally and the right superior frontal gyrus (SFG) compared to YA group. The resting-state brain activity analysis showed that amplitude of low-frequency fluctuation (ALFF) values in the bilateral postcentral gyrus and left ventral medial prefrontal cortex (mPFC) were significantly different in the OA group. The functional connectivity (FC) in the right ventral dorsolateral prefrontal cortex (DLPFC) and the right insula was significantly decreased in the OA group compared to the YA and MA groups. Likewise, the FC in the left caudal parahippocampal gyrus (PHG) and left inferior parietal lobule (IPL) were significantly lower in the MA and OA groups compared to the YA group. In addition, both the structural properties and the FC values of these brain regions were significantly correlated with age.

Conclusion

This preliminary study concludes that CLBP affects the aging process. The synergistic effects of CLBP and aging accelerate the functional and structural decline of certain areas of the brain, which not only affects pain processing, but are also may be associated with cognitive declines.

Lumbar extension peak-torque, muscle endurance and motor imagery in junior-elite basketballers with and without a history of low back pain: a pilot study

Objectives

Low back pain (LBP) is common in elite athletes. Several peripheral and central factors have been identified to be altered in non-athletic LBP populations, however whether these alterations also exist in elite athletes with LBP is unknown. The aim of this study was to determine whether elite basketballers with a history of persistent LBP perform worse than those without LBP at a lumbar muscle endurance task, a lumbar extension peak-torque task, and a lumbar motor imagery task.

Method

An observational pilot study. Twenty junior elite-level male basketballers with (n = 11) and without (n = 9) a history of persistent LBP were recruited. Athletes completed a lumbar extensor muscle endurance (Biering-Sorensen) task, two lumbar extensor peak-torque (modified Biering-Sorensen) tasks and two motor imagery (left/right lumbar and hand judgement) tasks across two sessions (48 hours apart). Performance in these tasks were compared between the groups with and without a history of LBP.

Results

Young athletes with a history of LBP had reduced lumbar extensor muscle endurance (p < 0.001), reduced lumbar extension peak-torque (p < 0.001), and were less accurate at the left/right lumbar judgement task (p = 0.02) but no less accurate at a left/right hand judgement task (p = 0.59), than athletes without a history of LBP. Response times for both left/right judgement tasks did not differ between groups (lumbar p = 0.24; hand p = 0.58).

Conclusions

Junior elite male basketballers with a history of LBP demonstrate reduced lumbar extensor muscle endurance and lumbar extension peak-torque and are less accurate at a left/right lumbar rotation judgement task, than those without LBP.

The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP.

Higher Regional Gray Matter Volume and White Matter Integrity in Individuals With Central Neuropathic Pain After Spinal Cord Injury

Spinal cord injury (SCI) is a debilitating neurological condition that often leads to central neuropathic pain (CNP). As the fundamental mechanism of CNP is not fully established, its management is one of the most challenging problems among people with SCI. To shed more light on CNP mechanisms, the aim of this cross-sectional study was to compare the brain structure between individuals with SCI and CNP and those without CNP by examining the gray matter (GM) volume and the white matter (WM) integrity. Fifty-two individuals with SCI-28 with CNP and 24 without CNP-underwent a magnetic resonance imaging (MRI) session, including a T1-weighted scan for voxel-based morphometry, and a diffusion-weighted imaging (DWI) scan for WM integrity analysis, as measured by fractional anisotropy (FA) and mean diffusivity (MD). We found significantly higher GM volume in individuals with CNP compared with pain-free individuals in the right superior (p < 0.0014) and middle temporal gyri (p < 0.0001). Moreover, individuals with CNP exhibited higher WM integrity in the splenium of the corpus callosum (p < 0.0001) and in the posterior cingulum (p < 0.0001), compared with pain-free individuals. The results suggest that the existence of CNP following SCI is associated with GM and WM structural abnormalities in regions involved in pain intensification and spread, and which may reflect maladaptive neural plasticity in CNP.

Acute pain impairs retention of locomotor learning

Despite abundant evidence that pain alters movement performance, considerably less is known about the potential effects of pain on motor learning. Some of the brain regions involved in pain processing are also responsible for specific aspects of motor learning, indicating that the two functions have the potential to interact, yet it is unclear if they do. In experiment 1, we compared the acquisition and retention of a novel locomotor pattern in young, healthy individuals randomized to either experience pain via capsaicin and heat applied to the lower leg during learning or no stimulus. On day 1, participants learned a new asymmetric walking pattern using distorted visual feedback, a paradigm known to involve mostly explicit re-aiming processes. Retention was tested 24 h later. Although there were no differences in day 1 acquisition between groups, individuals who experienced pain on day 1 demonstrated reduced retention on day 2. Furthermore, the degree of forgetting between days correlated with pain ratings during learning. In experiment 2, we examined the effects of a heat stimulus alone, which served as a control for (nonpainful) cutaneous stimulation, and found no effects on either acquisition or retention of learning. Thus, pain experienced during explicit, strategic locomotor learning interferes with motor memory consolidation processes and does so most likely through a pain mechanism and not an effect of distraction. These findings have important implications for understanding basic motor learning processes and for clinical rehabilitation, in which painful conditions are often treated through motor learning-based interventions.NEW & NOTEWORTHY Pain is a highly prevalent and burdensome experience that rehabilitation practitioners often treat using motor learning-based interventions. Here, we showed that experimental acute pain, but not a heat stimulus, during locomotor learning impaired 24-h retention of the newly learned walking pattern. The degree of retention loss was related to the perceived pain level during learning. These findings suggest important links between pain and motor learning that have significant implications for clinical rehabilitation.

Gray Matter Abnormalities in Patients with Chronic Low Back Pain: A Systematic Review and Meta-Analysis of Voxel-Based Morphometry Studies

BACKGROUND

Numerous studies utilizing voxel-based morphometry (VBM) have documented gray matter (GM) alterations in patients with chronic low back pain (CLBP) compared to healthy controls. However, the inconsistency in GM abnormalities observed across different studies has hindered their potential application as objective neuroimaging biomarkers or therapeutic targets. To address this issue, we conducted a comprehensive meta-analysis of VBM studies to identify robust GM differences between CLBP patients and healthy controls.

METHODS

The databases including PubMed, Embase, and Web of Science were systematically searched from January 2000 to September 2022 to identify eligible neuroimaging studies. In this coordinate-based meta-analysis of VBM studies, the Seed-based d Mapping with Permutation of Subject Images method was used to quantitatively assess regional differences in GM between CLBP patients and healthy controls.

RESULTS

Thirteen VBM studies, involving a total of 574 CLBP patients and 1239 healthy controls, were included in the meta-analysis. The findings revealed that CLBP patients exhibited increased GM in the left striatum and left postcentral gyrus and decreased GM in the left superior frontal gyrus, left cerebellum, right striatum, left insula, and right middle occipital gyrus compared to healthy controls. The jackknife sensitivity analysis confirmed the robustness of these neuroimaging findings.

CONCLUSIONS

This study provides new insights into potential treatment strategies for CLBP and identifies neuroimaging biomarkers for pain chronification. These findings highlight the importance of considering regional GM abnormalities in the development of clinical interventions for CLBP.

Altered volume of the amygdala subregions in patients with chronic low back pain

Background

Neuroimaging studies have suggested a pivotal role for the amygdala involvement in chronic low back pain (CLBP). However, the relationship between the amygdala subregions and CLBP has not yet been delineated. This study aimed to analyze whether the amygdala subregions were linked to the development of CLBP.

Methods

A total of 45 patients with CLBP and 45 healthy controls (HCs) were included in this study. All subjects were asked to complete a three-dimensional T1-weighted magnetic resonance imaging (3D-T1 MRI) scan. FreeSurfer 7.3.2 was applied to preprocess the structural MRI images and segment the amygdala into nine subregions. Afterwards, comparisons were made between the two groups in terms of the volumes of the amygdala subregions. Correlation analysis is utilized to examine the relationship between the amygdala subregion and the scale scores, as well as the pain duration in patients with CLBP. Additionally, logistic regression was used to explore the risk of the amygdala and its subregions for CLBP.

Results

In comparison to HCs, patients with CLBP exhibited a significant enlargement of the left central nucleus (Ce) and left cortical nucleus (Co). Furthermore, the increased volume of the left Ce was associated with a higher risk of CLBP.

Conclusion

Our study suggests that the left Ce and left Co may be involved in the pathophysiological processes of CLBP. Moreover, the volume of the left Ce may be a biomarker for detecting the risk of CLBP.

Morphological and functional brain changes in chronic cancer-related pain: A systematic review

The purpose of this study was to perform a systematic review of the available literature on morphological and functional brain changes measured by modern neuroimaging techniques in patients suffering from chronic cancer-related pain. A systematic search was conducted in PubMed, Embase, and Web of Science using different keyword combinations. In addition, a hand search was performed on the reference lists and several databases to retrieve supplementary primary studies. Eligible articles were assessed for methodological quality and risk of bias and reviewed by two independent researchers. The search yielded only four studies, three of which used MRI and one PET-CT. None of the studies measured longitudinal morphological (i.e., gray or white matter) changes. All studies investigated functional brain changes and found differences in specific brain regions and networks between patients with chronic cancer-related pain and pain-free cancer patients or healthy volunteers. Some of these alterations were found in brain networks that also show changes in non-cancer populations with chronic pain (e.g., the default mode network and salience network). However, specific findings were inconsistent, and there was substantial variation in imaging methodology, analysis, sample size, and study quality. There is a striking lack of research on morphological brain changes in patients with chronic cancer-related pain. Moreover, only a few studies investigated functional brain changes. In the retrieved studies, there is some evidence that alterations occur in brain networks also involved in other chronic non-cancer pain syndromes. However, the low sample sizes of the studies, finding inconsistencies, and methodological heterogeneity do not allow for robust conclusions.

The Roles of Endogenous Opioids in Placebo and Nocebo Effects: From Pain to Performance to Prozac

Placebo and nocebo effects have been well documented for nearly two centuries. However, research has only relatively recently begun to explicate the neurobiological underpinnings of these phenomena. Similarly, research on the broader social implications of placebo/nocebo effects, especially within healthcare delivery settings, is in a nascent stage. Biological and psychosocial outcomes of placebo/nocebo effects are of equal relevance. A common pathway for such outcomes is the endogenous opioid system. This chapter describes the history of placebo/nocebo in medicine; delineates the current state of the literature related to placebo/nocebo in relation to pain modulation; summarizes research findings related to human performance in sports and exercise; discusses the implications of placebo/nocebo effects among diverse patient populations; and describes placebo/nocebo influences in research related to psychopharmacology, including the relevance of endogenous opioids to new lines of research on antidepressant pharmacotherapies.

Hypoconnectivity of the Amygdala in Patients with Low-Back-Related Leg Pain Linked to Individual Mechanical Pain Sensitivity: A Resting-State Functional MRI Study

Purpose

To explore resting-state functional connectivity (rsFC) of the amygdala in patients with low-back-related leg pain (LBLP).

Patients and Methods

For this prospective study, a total of 35 LBLP patients and 30 healthy controls (HCs) were included and underwent functional MRI and clinical assessments. Then, patients with LBLP were divided into acute LBLP (aLBLP) and chronic LBLP (cLBLP) subgroups. We further evaluated the between-group rsFC differences using left and right amygdala seeds in a whole-brain voxel analysis strategy. Finally, we performed correlation analysis between the rsFC values of altered regions and clinical indices.

Results

Compared to HCs, hypoconnectivity of the amygdala was observed in LBLP patients (P < 0.01, with correction). The amygdala's rsFC pattern was different between aLBLP and cLBLP patients: decreased the amygdala's FC to the right putamen, to the right paracentral lobule (PCL), or to the right posterior temporal lobe in aLBLP patients, while right amygdala to the bilateral anterior cingulate cortex (ACC) and the left postcentral gyrus (PoCG) in cLBLP patients. Correlation analysis showed that lower rsFC of the left amygdala to the right PCL was correlated with the von Frey filament (vF) test values of the left lumbar (p = 0.025) and right lumbar (p = 0.019) regions, and rsFC of the right amygdala to the left PoCG was correlated with lower vF test values of the left lumbar (p = 0.017), right lumbar spine (p = 0.003); to right PoCG was correlated with calf (p = 0.015); the rsFC of the right amygdala to bilateral ACC was negatively correlated with the pain rating index (p = 0.003).

Conclusion

LBLP patients showed amygdala hypoconnectivity, and the altered pattern of amygdala rsFC was different in the acute and chronic phases. Moreover, the amygdala hypoconnectivity was related to individual mechanical sensitivity (vF test) in LBLP patients.

Diagnosis of Chronic Musculoskeletal Pain by Using Functional Near-Infrared Spectroscopy and Machine Learning

Chronic pain (CP) has been found to cause significant alternations of the brain's structure and function due to changes in pain processing and disrupted cognitive functions, including with respect to the prefrontal cortex (PFC). However, until now, no studies have used a wearable, low-cost neuroimaging tool capable of performing functional near-infrared spectroscopy (fNIRS) to explore the functional alternations of the PFC and thus automatically achieve a clinical diagnosis of CP. In this case-control study, the pain characteristics of 19 chronic pain patients and 32 healthy controls were measured using fNIRS. Functional connectivity (FC), FC in the PFC, and spontaneous brain activity of the PFC were examined in the CP patients and compared to those of healthy controls (HCs). Then, leave-one-out cross-validation and machine learning algorithms were used to automatically achieve a diagnosis corresponding to a CP patient or an HC. The current study found significantly weaker FC, notably higher small-worldness properties of FC, and increased spontaneous brain activity during resting state within the PFC. Additionally, the resting-state fNIRS measurements exhibited excellent performance in identifying the chronic pain patients via supervised machine learning, achieving F1 score of 0.8229 using only seven features. It is expected that potential FC features can be identified, which can thus serve as a neural marker for the detection of CP using machine learning algorithms. Therefore, the present study will open a new avenue for the diagnosis of chronic musculoskeletal pain by using fNIRS and machine learning techniques.

Protocol of identical exercise programs with and without specific breathing techniques for the treatment of chronic non-specific low back pain: randomized feasibility trial with two-month follow-up

BACKGROUND

Chronic low back pain (CLBP) is a leading cause of disability globally. Exercise therapies are one of the commonly prescribed treatment options for CLBP. The specific exercise therapies for CLBP most commonly target movement dysfunction, but seldom brain-based pain modulation. Exercise therapies with specific breathing techniques (SBTs) have been shown to influence and enhance brain-based structural and functional pain modulation.

AIMS AND OBJECTIVES

To assess the feasibility of the SBTs protocol, eligibility criteria, randomization, and dropout rates. To quantify the changes in patient outcome measures and choose the most relevant measure for larger-scale study. To quantify self-adherence levels to home exercise and monitor and record possible pain medication and other treatment modality usage, and adverse events during exercise.

DESIGN

A parallel randomised analyst-blinded feasibility trial with two-month follow-up.

OUTCOME MEASURES

Feasibility related to aims and objectives. Multiple pain- and health-related patient-reported outcome measures of pain intensity, disability, central sensitization, anxiety, kinesiophobia, catastrophising, self-efficacy, sleep quality, quality of life, and health and well-being status. Exercise adherence, pain medication and other treatment modality usage, and possible adverse events related to exercises will be monitored and recorded.

METHODS

Thirty participants will be randomized to movement control exercise with SBTs (15 subjects in experimental group) or movement control exercise without SBTs (15 subjects in control group) in private chiropractic practice setting with two-month follow-up. Trial registration number; NCT05268822.

DISCUSSION

The clinical difference in effectiveness between practically identical exercise programs in uniform study settings with or without SBTs has not been studied before. This study aims to inform feasibility and help determine whether progression to a full-scale trial is worthwhile.

Identifying body awareness-related brain network changes after Spring Forest Qigong™ practice or P.Volve low-intensity exercise in adults with chronic low back pain: a feasibility Phase I Randomized Clinical Trial

Background

Chronic low back pain (cLBP) affects the quality of life of 52 million Americans and leads to an enormous personal and economic burden. A multidisciplinary approach to cLBP management is recommended. Since medication has limited efficacy and there are mounting concerns about opioid addiction, the American College of Physicians and American Pain Society recommend non-pharmacological interventions, such as mind and body approaches (e.g., Qigong, yoga, Tai Chi) before prescribing medications. Of those, Qigong practice might be most accessible given its gentle movements and because it can be performed standing, sitting, or lying down. The three available Qigong studies in adults with cLBP showed that Qigong reduced pain more than waitlist and equally well than exercise. Yet, the duration and/or frequency of Qigong practice were low (<12 weeks or less than 3x/week). The objectives of this study were to investigate the feasibility of practicing Spring Forest Qigong™ or performing P.Volve low intensity exercises 3x/week for 12 weeks, feasibility of recruitment, data collection, delivery of the intervention as intended, as well as identify estimates of efficacy on brain function and behavioral outcomes after Qigong practice or exercise. To our knowledge, this is the first study investigating the feasibility of the potential effect of Qigong on brain function in adults with cLBP.

Methods

We conducted a feasibility Phase I Randomized Clinical Trial. Of the 36 adults with cLBP recruited between January 2020 and June 2021, 32 were enrolled and randomized to either 12 weeks of remote Spring Forest Qigong™ practice or remote P.Volve low-intensity exercises. Participants practiced at least 3x/week for 41min/session with online videos. Our main outcome measures were the Numeric Pain Rating Scale (highest, average, and lowest cLBP pain intensity levels in the prior week), assessed weekly and fMRI data (resting-state and task-based fMRI tasks: pain imagery, kinesthetic imagery of a Qigong movement, and robot-guided shape discrimination). We compared baseline resting-state connectivity and brain activation during fMRI tasks in adults with cLBP with data from a healthy control group (n=28) acquired in a prior study. Secondary outcomes included measures of function, disability, body awareness, kinesiophobia, balance, self-efficacy, core muscle strength, and ankle proprioceptive acuity with a custom-build device.

Results

Feasibility of the study design and methods was demonstrated with 30 participants completing the study (94% retention) and reporting high satisfaction with the programs; 96% adherence to P.Volve low-intensity exercises, and 128% of the required practice intensity for Spring Forest Qigong™ practice. Both groups saw promising reductions in low back pain (effect sizes Cohen's d =1.01-2.22) and in most other outcomes ( d =0.90-2.33). Markers of ankle proprioception were not significantly elevated in the cLBP group after the interventions. Brain imaging analysis showed weaker parietal operculum and insula network connectivity in adults with cLBP (n=26), compared to data from a healthy control group (n=28). The pain imagery task elicited lower brain activation of insula, parietal operculum, angular gyrus and supramarginal gyrus at baseline in adults with cLBP than in healthy adults. Adults with cLBP had lower precentral gyrus activation than healthy adults for the Qigong movement and robot task at baseline. Pre-post brain function changes showed individual variability: Six (out of 13) participants in the Qigong group showed increased activation in the parietal operculum, angular gyrus, supramarginal gyrus, and precentral gyrus during the Qigong fMRI task.

Interpretation

Our data indicate the feasibility and acceptability of using Spring Forest Qigong™ practice or P.Volve low-intensity exercises for cLBP relief showing promising results in terms of pain relief and associated symptoms. Our brain imaging results indicated brain function improvements after 12 weeks of Qigong practice in some participants, pointing to the need for further investigation in larger studies.

Trial registration number

ClinicalTrials.gov: NCT04164225 .

Synaptic Plasticity in the Pain-Related Cingulate and Insular Cortex

Cumulative animal and human studies have consistently demonstrated that two major cortical regions in the brain, namely the anterior cingulate cortex (ACC) and insular cortex (IC), play critical roles in pain perception and chronic pain. Neuronal synapses in these cortical regions of adult animals are highly plastic and can undergo long-term potentiation (LTP), a phenomenon that is also reported in brain areas for learning and memory (such as the hippocampus). Genetic and pharmacological studies show that inhibiting such cortical LTP can help to reduce behavioral sensitization caused by injury as well as injury-induced emotional changes. In this review, we will summarize recent progress related to synaptic mechanisms for different forms of cortical LTP and their possible contribution to behavioral pain and emotional changes.

The Roles of Imaging Biomarkers in the Management of Chronic Neuropathic Pain

Chronic neuropathic pain (CNP) affects around 10% of the general population and has a significant social, emotional, and economic impact. Current diagnosis techniques rely mainly on patient-reported outcomes and symptoms, which leads to significant diagnostic heterogeneity and subsequent challenges in management and assessment of outcomes. As such, it is necessary to review the approach to a pathology that occurs so frequently, with such burdensome and complex implications. Recent research has shown that imaging methods can detect subtle neuroplastic changes in the central and peripheral nervous system, which can be correlated with neuropathic symptoms and may serve as potential markers. The aim of this paper is to review available imaging methods used for diagnosing and assessing therapeutic efficacy in CNP for both the preclinical and clinical setting. Of course, further research is required to standardize and improve detection accuracy, but available data indicate that imaging is a valuable tool that can impact the management of CNP.

Mindfulness-Based Stress Reduction, Cognitive Behavioral Therapy, and Acupuncture in Chronic Low Back Pain: Protocol for Two Linked Randomized Controlled Trials

BACKGROUND

Nonpharmacologic mind-body therapies have demonstrated efficacy in low back pain. However, the mechanisms underlying these therapies remain to be fully elucidated.

OBJECTIVE

In response to these knowledge gaps, the Stanford Center for Low Back Pain-a collaborative, National Institutes of Health P01-funded, multidisciplinary research center-was established to investigate the common and distinct biobehavioral mechanisms of three mind-body therapies for chronic low back pain: cognitive behavioral therapy (CBT) that is used to treat pain, mindfulness-based stress reduction (MBSR), and electroacupuncture. Here, we describe the design and implementation of the center structure and the associated randomized controlled trials for characterizing the mechanisms of chronic low back pain treatments.

METHODS

The multidisciplinary center is running two randomized controlled trials that share common resources for recruitment, enrollment, study execution, and data acquisition. We expect to recruit over 300 chronic low back pain participants across two projects and across different treatment arms within each project. The first project will examine pain-CBT compared with MBSR and a wait-list control group. The second project will examine real versus sham electroacupuncture. We will use behavioral, psychophysical, physical measure, and neuroimaging techniques to characterize the central pain modulatory and emotion regulatory systems in chronic low back pain at baseline and longitudinally. We will characterize how these interventions impact these systems, characterize the longitudinal treatment effects, and identify predictors of treatment efficacy.

RESULTS

Participant recruitment began on March 17, 2015, and will end in March 2023. Recruitment was halted in March 2020 due to COVID-19 and resumed in December 2021.

CONCLUSIONS

This center uses a comprehensive approach to study chronic low back pain. Findings are expected to significantly advance our understanding in (1) the baseline and longitudinal mechanisms of chronic low back pain, (2) the common and distinctive mechanisms of three mind-body therapies, and (3) predictors of treatment response, thereby informing future delivery of nonpharmacologic chronic low back pain treatments.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02503475; https://clinicaltrials.gov/ct2/show/NCT02503475.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/37823.

Neuroimaging Assessment of Pain

Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.

Structural, Functional and Neurochemical Cortical Brain Changes Associated with Chronic Low Back Pain

Chronic low back pain (CLBP) is one of the most prevalent musculoskeletal disorders, being one of the leading contributors to disability worldwide and involving an important economic and social burden. Up to 90% of CLBP is non-specific (not associated with specific injuries), with a chronicity expectation estimated at 10%. Currently, motivational and emotional central circuits are being investigated due to their role in CLBP persistency and chronification. Therefore, this narrative review aimed to summarize the evidence regarding the cortical brain changes described for proposing novel multidisciplinary approaches. Novel advances in neuroimaging techniques demonstrated structural (e.g., decrease in the grey matter located at the dorsolateral prefrontal cortex), functional (e.g., connectivity impairments in those areas involved in pain processing), and neurochemical changes (e.g., decrease in cerebral metabolites). In addition, significant changes were found in the primary somatosensory and motor cortex, contributing to the alteration of low back muscles activation and function.

Reflections of the sensory findings in the central nervous system in patients with neuropathic pain

This study aimed to evaluate whether there was a difference in functional magnetic resonance imaging (fMRI) findings in patients who were found having hyperalgesia or hypoesthesia according to Quantitative Sensory Tests (QST). Forty participants were included in the study: 20 with neuropathic pain (NP) due to cervical disc pathology (NP group) and 20 healthy volunteers. After obtaining the socio-demographic and clinical data of the participants, the painDETECT questionnaire was administered, followed by QST analysis to show the presence of hypoesthesia and/or hyperalgesia, and fMRI examinations, which included sensory stimulation of both extremities. Sensory threshold tests were found to be higher in the NP group compared with the healthy volunteers, and the heat pain threshold was found to be lower in the tests showing pain thresholds in the intergroup analyses (p < 0.05). The changes described were found in both painful and non-painful limbs. In the hypoesthetic NP group, a lower somatosensory cortex activity was found in non-painful limbs compared with the healthy volunteers (p < 0.05). In the unilateral hyperalgesic NP group, a lower somatosensory cortex activity was found on the painful side, and if the hyperalgesia was widespread, lower blood oxygen-level-dependent activity was also found in the operculum and insular cortex (p < 0.05). The patients with different phenotypes of NP had different activities in the areas related to the processing of pain, and were more prominent in patients with widespread hyperalgesia. Studies with larger numbers of patients are required for a definite statement.

Individually unique dynamics of cortical connectivity reflect the ongoing intensity of chronic pain

ABSTRACT

Chronic pain diseases are characterised by an ongoing and fluctuating endogenous pain, yet it remains to be elucidated how this is reflected by the dynamics of ongoing functional cortical connections.Here, we investigated the cortical encoding of 20 chronic back pain patients and 20 chronic migraineurs in four repeated fMRI sessions. A brain parcellation approach subdivided the whole brain into 408 regions. Linear mixed effects models were fitted for each pair of brain regions to explore the relationship between the dynamic cortical connectivity and the observed trajectory of the patients' ratings of fluctuating endogenous pain.Overall, we found that periods of high and increasing pain were predominantly related to low cortical connectivity. The change of pain intensity in chronic back pain was subserved by connections in left parietal opercular regions, right insular regions, as well as large parts of the parietal, cingular and motor cortices. The change of pain intensity direction in chronic migraine was reflected by decreasing connectivity between the anterior insular cortex and orbitofrontal areas, as well as between the PCC and frontal and ACC regions.Interestingly, the group results were not mirrored by the individual patterns of pain-related connectivity, which is suggested to deny the idea of a common neuronal core problem for chronic pain diseases. The diversity of the individual cortical signatures of chronic pain encoding results adds to the understanding of chronic pain as a complex and multifaceted disease. The present findings support recent developments for more personalised medicine.

Brain Imaging Biomarkers for Chronic Pain

The prevalence of chronic pain has reached epidemic levels. In addition to personal suffering chronic pain is associated with psychiatric and medical co-morbidities, notably substance misuse, and a huge a societal cost amounting to hundreds of billions of dollars annually in medical cost, lost wages, and productivity. Chronic pain does not have a cure or quantitative diagnostic or prognostic tools. In this manuscript we provide evidence that this situation is about to change. We first start by summarizing our current understanding of the role of the brain in the pathogenesis of chronic pain. We particularly focus on the concept of learning in the emergence of chronic pain, and the implication of the limbic brain circuitry and dopaminergic signaling, which underly emotional learning and decision making, in this process. Next, we summarize data from our labs and from other groups on the latest brain imaging findings in different chronic pain conditions focusing on results with significant potential for translation into clinical applications. The gaps in the study of chronic pain and brain imaging are highlighted in throughout the overview. Finally, we conclude by discussing the costs and benefits of using brain biomarkers of chronic pain and compare to other potential markers.

Functional brain rewiring and altered cortical stability in ulcerative colitis

Despite recent advances, there is still a major need to better understand the interactions between brain function and chronic gut inflammation and its clinical implications. Alterations in executive function have previously been identified in several chronic inflammatory conditions, including inflammatory bowel diseases. Inflammation-associated brain alterations can be captured by connectome analysis. Here, we used the resting-state fMRI data from 222 participants comprising three groups (ulcerative colitis (UC), irritable bowel syndrome (IBS), and healthy controls (HC), N = 74 each) to investigate the alterations in functional brain wiring and cortical stability in UC compared to the two control groups and identify possible correlations of these alterations with clinical parameters. Globally, UC participants showed increased functional connectivity and decreased modularity compared to IBS and HC groups. Regionally, UC showed decreased eigenvector centrality in the executive control network (UC < IBS < HC) and increased eigenvector centrality in the visual network (UC > IBS > HC). UC also showed increased connectivity in dorsal attention, somatomotor network, and visual networks, and these enhanced subnetwork connectivities were able to distinguish UC participants from HCs and IBS with high accuracy. Dynamic functional connectome analysis revealed that UC showed enhanced cortical stability in the medial prefrontal cortex (mPFC), which correlated with severe depression and anxiety-related measures. None of the observed brain changes were correlated with disease duration. Together, these findings are consistent with compromised functioning of networks involved in executive function and sensory integration in UC.

Association between temporal summation and conditioned pain modulation in chronic low back pain: baseline results from 2 clinical trials

Introduction

Temporal summation (TS) and conditioned pain modulation (CPM) represent different aspects of central pain processing. Their relationship and differential performance within distinct body locations are not well understood.

Objectives

To examine the association between TS and CPM in chronic low back pain and the influence of testing location on this relationship.

Methods

We analyzed baseline data from 2 clinical trials on participants with chronic low back pain (n = 264; 47.3% female; mean age = 41 years, SD = 12; mean pain = 5.3/10, SD = 1.4). Measures used included questionnaires assessing pain and negative affect, phasic thermal TS at the hand (thenar) and the lower back (lumbar), followed by CPM that included a thermal testing stimulus (Heat-6, the temperature where pain rating is 6/10) and a cold-pressor conditioning stimulus. Nonparametric, proportional odds logistic regression was used to model thenar, and separately, lumbar TS, using CPM, Heat-6, negative affect, and demographics.

Results

Our models revealed a small association (βs = 0.17, P = 0.01) between reduced CPM and heightened TS at both testing sites, regardless of demographics or negative affect.

Conclusion

Results suggest a modest association between TS and CPM, irrespective of anatomical testing location, demographics, and negative affect. These findings will help improve the methodology and interpretation of TS and CPM measurement in clinical pain populations.

Investigating the specificity of the neurologic pain signature against breathlessness and finger opposition

ABSTRACT

Brain biomarkers of pain, including pain-predictive "signatures" based on brain activity, can provide measures of neurophysiological processes and potential targets for interventions. A central issue relates to the specificity of such measures, and understanding their current limits will both advance their development and explore potentially generalizable properties of pain to other states. Here, we used 2 data sets to test the neurologic pain signature (NPS), an established pain neuromarker. In study 1, brain activity was measured using high-field functional magnetic resonance imaging (7T fMRI, N = 40) during 5 to 25 seconds of experimental breathlessness (induced by inspiratory resistive loading), conditioned breathlessness anticipation, and finger opposition. In study 2, we assessed anticipation and breathlessness perception (3T, N = 19) under blinded saline (placebo) and remifentanil administration. The NPS responded to breathlessness, anticipation, and finger opposition, although no direct comparisons with painful events were possible. Local NPS patterns in anterior or midinsula, S2, and dorsal anterior cingulate responded to breathlessness and finger opposition and were reduced by remifentanil. Local NPS responses in the dorsal posterior insula did not respond to any manipulations. Therefore, significant global NPS activity alone is not specific for pain, and we offer insight into the overlap between NPS responses, breathlessness, and somatomotor demand.

The brain's structural differences between postherpetic neuralgia and lower back pain

The purpose is to explore the brain's structural difference in local morphology and between-region networks between two types of peripheral neuropathic pain (PNP): postherpetic neuralgia (PHN) and lower back pain (LBP). A total of 54 participants including 38 LBP and 16 PHN patients were enrolled. The average pain scores were 7.6 and 7.5 for LBP and PHN. High-resolution structural T1 weighted images were obtained. Both grey matter volume (GMV) and morphological connectivity (MC) were extracted. An independent two-sample t-test with false discovery rate (FDR) correction was used to identify the brain regions where LBP and PHN patients showed significant GMV difference. Next, we explored the differences of MC network between LBP and PHN patients and detected the group differences in network properties by using the two-sample t-test and FDR correction. Compared with PHN, LBP patients had significantly larger GMV in temporal gyrus, insula and fusiform gyrus (p < 0.05). The LBP cohort had significantly stronger MC in the connection between right precuneus and left opercular part of inferior frontal gyrus (p < 0.05). LBP patients had significantly stronger degree in left anterior cingulate gyrus and left rectus gyrus (p < 0.05) while had significantly weaker degree than PHN patients in left orbital part of middle frontal gyrus, left supplementary motor area and left superior parietal lobule (p < 0.05). LBP and PHN patients had significant differences in the brain's GMV, MC, and network properties, which implies that different PNPs have different neural mechanisms concerning pain modulation.

Relative contributions of the nervous system, spinal tissue and psychosocial health to non-specific low back pain: Multivariate meta-analysis

BACKGROUND AND OBJECTIVES

Nervous system, psychosocial and spinal tissue biomarkers are associated with non-specific low back pain (nsLBP), though relative contributions are unclear.

DATABASES AND DATA TREATMENT

MEDLINE, EMBASE, CINAHL, PsycINFO and SPORTDiscus were searched up to 25 March 2020. Related reviews and reference lists were also screened. Observational studies examining structural and functional nervous system biomarkers (e.g. quantitative sensory tests, structural and functional brain measures), psychosocial factors (e.g. mental health, catastrophizing) and structural spinal imaging biomarkers (e.g. intervertebral disc degeneration, paraspinal muscle size) between nsLBP and pain-free controls were included. For multivariate meta-analysis, two of three domains were required in each study. Random-effects pairwise and multivariate meta-analyses were performed. GRADE approach assessed evidence certainty. Newcastle-Ottawa scale assessed risk of bias. Main outcomes were the effect size difference of domains between nsLBP and pain-free controls.

RESULTS

Of 4519 unique records identified, 33 studies (LBP = 1552, referents = 1322) were meta-analysed. Psychosocial state (Hedges' g [95%CI]: 0.90 [0.69-1.10], p < 0.001) in nsLBP showed larger effect sizes than nervous system (0.31 [0.13-0.49], p < 0.001; difference: 0.61 [0.36-0.86], p < 0.001) and spine imaging biomarkers (0.55 [0.37-0.73], p < 0.001; difference: 0.36 [0.04-0.67], p = 0.027). The relationship between domains changes depending on if pain duration is acute or chronic.

CONCLUSIONS

Psychosocial effect sizes in nsLBP are greater than that for spinal imaging and nervous system biomarkers. Limitations include cross-sectional design of studies included and inference of causality. Future research should investigate the clinical relevance of these effect size differences in relation to pain intensity and disability.

STUDY REGISTRATION

PROSPERO-CRD42020159188.

SIGNIFICANCE

Spinal imaging (e.g. intervertebral disc degeneration), psychosocial (e.g. depression) and nervous system (e.g. quantitative sensory tests, structural and functional brain measures) biomarkers contribute to non-specific low back pain. However, psychosocial factors may be more compromised than nervous system and spinal imaging biomarkers. This relationship depends on if the pain is acute or chronic. These findings underscore that the 'non-specific' label in back pain should be reconsidered, and more specific multidimensional categories evaluated to guide patient management.

Decoding pain from brain activity

Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.

Low Somatosensory Cortex Excitability in the Acute Stage of Low Back Pain Causes Chronic Pain

Determining the mechanistic causes of complex biopsychosocial health conditions such as low back pain (LBP) is challenging, and research is scarce. Cross-sectional studies demonstrate altered excitability and organization of the somatosensory and motor cortex in people with acute and chronic LBP, however, no study has explored these mechanisms longitudinally or attempted to draw causal inferences. Using sensory evoked potential area measurements and transcranial magnetic stimulation derived map volume we analyzed somatosensory and motor cortex excitability in 120 adults experiencing acute LBP. Following multivariable regression modelling with adjustment for confounding, we identified lower primary (OR = 2.08, 95% CI = 1.22-3.57) and secondary (OR = 2.56, 95% CI = 1.37-4.76) somatosensory cortex excitability significantly increased the odds of developing chronic pain at 6-month follow-up. Corticomotor excitability in the acute stage of LBP was associated with higher pain intensity at 6-month follow-up (B = -0.15, 95% CI: -0.28 to -0.02) but this association did not remain after confounder adjustment. These data provide evidence that low somatosensory cortex excitability in the acute stage of LBP is a cause of chronic pain. PERSPECTIVE: This prospective longitudinal cohort study design identified low sensorimotor cortex excitability during the acute stage of LBP in people who developed chronic pain. Interventions that target this proposed mechanism may be relevant to the prevention of chronic pain.

Machine Learning for Predicting Individual Severity of Blepharospasm Using Diffusion Tensor Imaging

Accumulating diffusion tensor imaging (DTI) evidence suggests that white matter abnormalities evaluated by local diffusion homogeneity (LDH) or fractional anisotropy (FA) occur in patients with blepharospasm (BSP), both of which are significantly correlated with disease severity. However, whether the individual severity of BSP can be identified using these DTI metrics remains unknown. We aimed to investigate whether a combination of machine learning techniques and LDH or FA can accurately identify the individual severity of BSP. Forty-one patients with BSP were assessed using the Jankovic Rating Scale and DTI. The patients were assigned to non-functionally and functionally limited groups according to their Jankovic Rating Scale scores. A machine learning scheme consisting of beam search and support vector machines was designed to identify non-functionally versus functionally limited outcomes, with the input features being LDH or FA in 68 white matter regions. The proposed machine learning scheme with LDH or FA yielded an overall accuracy of 88.67 versus 85.19% in identifying non-functionally limited versus functionally limited outcomes. The scheme also identified a sensitivity of 91.40 versus 85.87% in correctly identifying functionally limited outcomes, a specificity of 83.33 versus 83.67% in accurately identifying non-functionally limited outcomes, and an area under the curve of 93.7 versus 91.3%. These findings suggest that a combination of LDH or FA measurements and a sophisticated machine learning scheme can accurately and reliably identify the individual disease severity in patients with BSP.

Deep Brain Stimulation of the Subgenual Cingulate Cortex for the Treatment of Chronic Low Back Pain

OBJECTIVES

Despite converging basic scientific and clinical evidence of the link between chronic pain and depression, existing therapies do not often take advantage of this overlap. Here, we provide a critical review of the literature that highlights the intersection in brain networks between chronic low back pain (CLBP) and depression and discuss findings from previous deep brain stimulation (DBS) studies for pain. Based on a multidimensional model of pain processing and the connectivity of the subgenual cingulate cortex (SCC) with areas that are implicated in both CLBP and depression, we propose a novel approach to the treatment of CLBP using DBS of the SCC.

MATERIALS AND METHODS

A narrative review with literature assessment.

RESULTS

CLBP is associated with a shift away from somatosensory representation toward brain regions that mediate emotional processes. There is a high degree of overlap between these regions and those involved in depression, including the anterior cingulate cortex, medial prefrontal cortex, nucleus accumbens, and amygdala. Whereas targets sites from previous DBS trials for pain were not anatomically positioned to engage these areas and their associated networks, the SCC is structurally connected to all of these regions and as well as others involved in mediating sensory, cognitive, and affective processing in CLBP.

CONCLUSIONS

CLBP and depression share a common underlying brain network interconnected by the SCC. Current data and novel technology provide an optimal opportunity to develop clinically effective trials of SCC DBS for CLBP.

Machine Learning in Chronic Pain Research: A Scoping Review

Given the high prevalence and associated cost of chronic pain, it has a significant impact on individuals and society. Improvements in the treatment and management of chronic pain may increase patients’ quality of life and reduce societal costs. In this paper, we evaluate state-of-the-art machine learning approaches in chronic pain research. A literature search was conducted using the PubMed, IEEE Xplore, and the Association of Computing Machinery (ACM) Digital Library databases. Relevant studies were identified by screening titles and abstracts for keywords related to chronic pain and machine learning, followed by analysing full texts. Two hundred and eighty-seven publications were identified in the literature search. In total, fifty-three papers on chronic pain research and machine learning were reviewed. The review showed that while many studies have emphasised machine learning-based classification for the diagnosis of chronic pain, far less attention has been paid to the treatment and management of chronic pain. More research is needed on machine learning approaches to the treatment, rehabilitation, and self-management of chronic pain. As with other chronic conditions, patient involvement and self-management are crucial. In order to achieve this, patients with chronic pain need digital tools that can help them make decisions about their own treatment and care.

Predicting Individual Pain Thresholds From Morphological Connectivity Using Structural MRI: A Multivariate Analysis Study

Pain sensitivity is highly variable among individuals, and it is clinically important to predict an individual’s pain sensitivity for individualized diagnosis and management of pain. Literature has shown that pain sensitivity is associated with regional structural features of the brain, but it remains unclear whether pain sensitivity is also related to structural brain connectivity. In the present study, we investigated the relationship between pain thresholds and morphological connectivity (MC) inferred from structural MRI based on data of 221 healthy participants. We found that MC was highly predictive of an individual’s pain thresholds and, importantly, it had a better prediction performance than regional structural features. We also identified a number of most predictive MC features and confirmed the crucial role of the prefrontal cortex in the determination of pain sensitivity. These results suggest the potential of using structural MRI-based MC to predict an individual’s pain sensitivity in clinical settings, and hence this study has important implications for diagnosis and treatment of pain.

Structural and functional brain abnormalities in postherpetic neuralgia: A systematic review of neuroimaging studies

In recent decades, an increasing number of neuroimaging studies utilizing magnetic resonance imaging (MRI) have explored the differential effects of postherpetic neuralgia (PHN) on brain structure and function. We systematically reviewed and integrated the findings from relevant neuroimaging studies in PHN patients. A total of 15 studies with 16 datasets were ultimately included in the present study, which were categorized by the different neuroimaging modalities. The results revealed that PHN was closely associated with structural/microstructural and functional abnormalities of the brain mainly located in the 'pain matrix', including the thalamus, insula, parahippocampus, amygdala, dorsolateral prefrontal cortex, precentral gyrus and inferior parietal lobe, as well as other regions, such as the precuneus, lentiform nucleus and brainstem. Furthermore, a disruption of multiple networks, including the default-mode network, salience network and limbic system, may contribute to the neurophysiological mechanisms underlying PHN. The findings indicate that the cerebral abnormalities of PHN were not restricted to the pain matrix but extended to other regions, profoundly affecting the regulation and moderation of pain processing in PHN. Future prospective and longitudinal neuroimaging studies with larger samples will elucidate the progressive trajectory of neural changes in the pathophysiological process of PHN.

Multi-modal biomarkers of low back pain: A machine learning approach

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Widespread differences in cortical thickness (CT) were observed in patients with low back pain.

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Changes in CT correlated with self-reported clinical scores of pain and emotion.

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Changes in resting state fMRI metrics of functional networks.

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Support vector machines separated low back pain patients from controls with a high performance.

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Multi-modal biomarkers can be useful when identifying personalized treatments for low back pain.

Chronic low back pain (LBP) is a very common health problem worldwide and a major cause of disability. Yet, the lack of quantifiable metrics on which to base clinical decisions leads to imprecise treatments, unnecessary surgery and reduced patient outcomes. Although, the focus of LBP has largely focused on the spine, the literature demonstrates a robust reorganization of the human brain in the setting of LBP. Brain neuroimaging holds promise for the discovery of biomarkers that will improve the treatment of chronic LBP. In this study, we report on morphological changes in cerebral cortical thickness (CT) and resting-state functional connectivity (rsFC) measures as potential brain biomarkers for LBP. Structural MRI scans, resting state functional MRI scans and self-reported clinical scores were collected from 24 LBP patients and 27 age-matched healthy controls (HC). The results suggest widespread differences in CT in LBP patients relative to HC. These differences in CT are correlated with self-reported clinical summary scores, the Physical Component Summary and Mental Component Summary scores. The primary visual, secondary visual and default mode networks showed significant age-corrected increases in connectivity with multiple networks in LBP patients. Cortical regions classified as hubs based on their eigenvector centrality (EC) showed differences in their topology within motor and visual processing regions. Finally, a support vector machine trained using CT to classify LBP subjects from HC achieved an average classification accuracy of 74.51%, AUC = 0.787 (95% CI: 0.66–0.91). The findings from this study suggest widespread changes in CT and rsFC in patients with LBP while a machine learning algorithm trained using CT can predict patient group. Taken together, these findings suggest that CT and rsFC may act as potential biomarkers for LBP to guide therapy.

Common and distinct neural representations of aversive somatic and visceral stimulation in healthy individuals

Different pain types may be encoded in different brain circuits. Here, we examine similarities and differences in brain processing of visceral and somatic pain. We analyze data from seven fMRI studies (N = 165) and five types of pain and discomfort (esophageal, gastric, and rectal distension, cutaneous thermal stimulation, and vulvar pressure) to establish and validate generalizable pain representations. We first evaluate an established multivariate brain measure, the Neurologic Pain Signature (NPS), as a common nociceptive pain system across pain types. Then, we develop a multivariate classifier to distinguish visceral from somatic pain. The NPS responds robustly in 98% of participants across pain types, correlates with perceived intensity of visceral pain and discomfort, and shows specificity to pain when compared with cognitive and affective conditions from twelve additional studies (N = 180). Pre-defined signatures for non-pain negative affect do not respond to visceral pain. The visceral versus the somatic classifier reliably distinguishes somatic (thermal) from visceral (rectal) stimulation in both cross-validation and independent cohorts. Other pain types reflect mixtures of somatic and visceral patterns. These results validate the NPS as measuring a common core nociceptive pain system across pain types, and provide a new classifier for visceral versus somatic pain.

Magnetic resonance imaging for chronic pain: diagnosis, manipulation, and biomarkers

Pain is a multidimensional subjective experience with biological, psychological, and social factors. Whereas acute pain can be a warning signal for the body to avoid excessive injury, long-term and ongoing pain may be developed as chronic pain. There are more than 100 million people in China living with chronic pain, which has raised a huge socioeconomic burden. Studying the mechanisms of pain and developing effective analgesia approaches are important for basic and clinical research. Recently, with the development of brain imaging and data analytical approaches, the neural mechanisms of chronic pain have been widely studied. In the first part of this review, we briefly introduced the magnetic resonance imaging and conventional analytical approaches for brain imaging data. Then, we reviewed brain alterations caused by several chronic pain disorders, including localized and widespread primary pain, primary headaches and orofacial pain, musculoskeletal pain, and neuropathic pain, and present meta-analytical results to show brain regions associated with the pathophysiology of chronic pain. Next, we reviewed brain changes induced by pain interventions, such as pharmacotherapy, neuromodulation, and acupuncture. Lastly, we reviewed emerging studies that combined advanced machine learning and neuroimaging techniques to identify diagnostic, prognostic, and predictive biomarkers in chronic pain patients.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

Effects of spinal cord stimulation on voxel-based brain morphometry in patients with failed back surgery syndrome

OBJECTIVE

Despite the clinical effectiveness of Spinal Cord Stimulation (SCS), potential structural brain modifications have not been explored. Our aim was to identify structural volumetric changes during subsensory SCS, in patients with Failed Back Surgery Syndrome (FBSS).

METHODS

In this cohort study, twenty-two FBSS patients underwent a magnetic resonance imaging protocol before SCS and 3 months after SCS. Clinical parameters were correlated with volumetric changes, calculated with voxel-based morphometry.

RESULTS

After 3 months, a significant volume decrease was found in the inferior frontal gyrus, precuneus, cerebellar posterior lobe and middle temporal gyrus. Significant increases were found in the inferior temporal gyrus, precentral gyrus and the middle frontal gyrus after SCS. Additionally, significant increases in volume of superior frontal and parietal white matter and a significant decrease in volume of white matter underlying the premotor/middle frontal gyrus were revealed after SCS. A significant correlation was highlighted between white matter volume underlying premotor/middle frontal gyrus and leg pain relief.

CONCLUSIONS

This study revealed for the first time that SCS is able to induce volumetric changes in gray and white matter, suggesting the reversibility of brain alterations after chronic pain treatment.

SIGNIFICANCE

Volumetric brain alterations are observable after 3 months of subsensory SCS in FBSS patients.

Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews

Artificial intelligence and machine learning (AI/ML) could enhance the ability to detect patterns of clinical characteristics in low-back pain (LBP) and guide treatment. We conducted three systematic reviews to address the following aims: (a) review the status of AI/ML research in LBP, (b) compare its status to that of two established LBP classification systems (STarT Back, McKenzie). AI/ML in LBP is in its infancy: 45 of 48 studies assessed sample sizes <1000 people, 19 of 48 studies used ≤5 parameters in models, 13 of 48 studies applied multiple models and attained high accuracy, 25 of 48 studies assessed the binary classification of LBP versus no-LBP only. Beyond the 48 studies using AI/ML for LBP classification, no studies examined use of AI/ML in prognosis prediction of specific sub-groups, and AI/ML techniques are yet to be implemented in guiding LBP treatment. In contrast, the STarT Back tool has been assessed for internal consistency, test-retest reliability, validity, pain and disability prognosis, and influence on pain and disability treatment outcomes. McKenzie has been assessed for inter- and intra-tester reliability, prognosis, and impact on pain and disability outcomes relative to other treatments. For AI/ML methods to contribute to the refinement of LBP (sub-)classification and guide treatment allocation, large data sets containing known and exploratory clinical features should be examined. There is also a need to establish reliability, validity, and prognostic capacity of AI/ML techniques in LBP as well as its ability to inform treatment allocation for improved patient outcomes and/or reduced healthcare costs.

The Role of the Cerebellum in Pain Perception: A Brain SPECT Perfusion Study in Patients with Burn Injuries

BACKGROUND AND PURPOSE

Virtual reality (VR) is a promising tool for distraction analgesia. This study aims to compare brain perfusion patterns while patients were undergoing burn wound care in two conditions-VR distraction and control (NoVR).

METHODS

With IRB approval, four patients hospitalized for acute burn care (three males and one female) participated in the study. All patients underwent wound care on two consecutive days; 1 day with standard analgesia and adjunctive VR, and the other day with standard analgesia alone, otherwise the wound care was very similar. Tc-99m ethyl cysteinate dimer was injected during wound care at the time of peak pain. Subjective patient reports on a 0-10 scale of pain intensity, time spent thinking about pain, and "fun" as well as opioid equivalent usage were analyzed. Voxel by voxel subtraction analysis of brain perfusion Single Photon Emission Computed Tomography (SPECT) images was performed at the group level. Statistical significance threshold was defined as P < .05.

RESULTS

Mean group subjective scores (VR, NoVR, statistical significance, and P-value) were observed for maximal pain intensity (9.0, 8.8, insignificant, and P = .809), time spent thinking about pain (5.2, 10.0, significant, and P = .015), and fun (6.0, 2.5, significant, and P = .012). Subtraction group analysis demonstrated VR-induced modulation of brain activity with statistically significant relative suppression of cerebellar activation in the VR compared to intense cerebellar activation in the NoVR environments.

CONCLUSION

Relative decrease in cerebellar perfusion based on stringent statistical threshold in the VR environment combined with improved subjective pain experience supports the hypotheses on the role of cerebellum in perception of noxious stimuli.