Hub disruption in patients with chronic neck pain: a graph analytical approach

Differences in the clinical presentation of chronic whiplash-associated disorders and nontraumatic neck pain: a systematic review and meta-analysis

ABSTRACT

Health outcomes may be worse for individuals with whiplash-associated disorders (WAD) compared to nontraumatic neck pain (NTNP), and clinical characteristics may differ. This systematic review examined evidence comparing WAD and NTNP in terms of pain, disability, psychological status, quality of life, measures of nociceptive processing, movement, sensorimotor, and muscle function. Studies were identified through electronic database searches and included after screening against predefined eligibility criteria. Standardized mean differences (SMD) or mean differences (MD) and 95% confidence intervals (CI) were calculated. Associations between MDs with demographics and study characteristics were explored using meta-regression. Certainty of evidence was assessed using Grades of Recommendation, Assessment, Development, and Evaluation. Sixty-one studies were eligible with 45 included in meta-analysis. Individuals with WAD reported clinically relevant higher disability (100-point Neck Disability Index MD [95% CI] 11.15 [8.63, 13.68]), greater remote cold sensitivity (SMD 0.89 [0.57, 1.21]), lower quality of life (SMD -0.96 [-1.77, -0.16]), greater depression (SMD 0.60 [0.27, 0.93]), greater local (SMD -0.56 [-1.00, -0.13]) and remote (SMD -0.50 [-0.81, -0.19]) pressure sensitivity, less cervical flexion (MD -5.30° [-7.44, -3.16]) and extension (MD -5.43° [-9.31, -1.55]), higher pain intensity (100-point numerical rating scale: MD 8.15 [5.80, 10.50]), and greater kinesiophobia (SMD 0.35 [0.11, 0.59]). No between-group differences were found for dizziness symptoms, stress, anxiety, balance, and local cold sensitivity. Meta-regression indicated that disability differences were negatively associated with age (R2 = 29.6%, P = 0.006). Certainty of evidence was mostly moderate. Individuals with chronic WAD have a worse clinical presentation compared to those with chronic NTNP, which has implications for patient assessment and management.

Changes in cerebral cortex activation during upright standing tasks in individuals with chronic neck pain: an fNIRS study

Introduction

Studies show that individuals with chronic neck pain (CNP) exhibit postural control deficits, potentially contributing to persistent and recurrent pain. However, the neural mechanisms underlying these deficits in CNP remain unexplored despite their importance for developing effective rehabilitation strategies. Therefore, this study aimed to investigate the neural activity during postural control using functional near-infrared spectroscopy (fNIRS), providing insights into the central mechanism underlying postural control deficits in individuals with CNP.

Methods

In this cross-sectional study, 10 individuals with CNP (CNP group) and 10 healthy controls (HC group) were assessed under three conditions: Task 1, standing on a force plate with eyes open and both feet; Task 2, standing on a force plate with eyes closed and both feet; Task 3, standing on a force plate with eyes closed and one foot. Cerebral cortex hemodynamic reactions, including bilateral prefrontal cortex (PFC), dorsolateral prefrontal cortex (DLPFC), pre-motor cortex and supplementary motor area (PMC/SMA), primary motor cortex (M1), and primary somatosensory cortex (S1) were measured using fNIRS. Balance parameters, including the sway area, total sway length, mean velocity, and center of pressure (COP) amplitude in the anterior-posterior (AP) and medial-lateral (ML) directions, were measured using a force plate.

Results

In Tasks 1 and 2, no differences were observed between both groups in balance parameters. However, the CNP group exhibited significantly higher activation in the left PMC/SMA (F = 4.788, p = 0.042) and M1 (F = 9.598, p = 0.006) in Task 1 and lower activation in the left (F = 4.952, p = 0.039) and right (F = 6.035, p = 0.024) PFC in Task 2 compared to that of the HC group. In Task 3, the CNP group exhibited a significantly larger COP amplitude in the AP direction (F = 7.057, p = 0.016) compared to that of the HC group. Additionally, activation in the right M1 (F = 7.873, p = 0.012) was significantly higher than in the HC group. Correlation analysis in Task 3 revealed stronger associations between the parameters in the CNP group.

Conclusion

Our findings suggest that individuals with CNP exhibit distinct patterns of cerebral cortex activities and postural control deficits. The PFC, M1, and PMC/SMA were involved in maintaining upright standing balance, and cerebral cortex changes associated with upright standing balance provide a more sensitive indicator of postural control deficits than peripheral balance parameters in individuals with CNP.

Abnormal Alterations of the White Matter Structural Network in Patients with Herpes Zoster and Postherpetic Neuralgia

PHN is one of the most common clinical complications of herpes zoster (HZ), the pathogenesis of which is unclear and poorly treated clinically, and many studies now suggest that postherpetic neuralgia (PHN) pain may be related to central neurologic mechanisms. This study aimed to investigate the white matter structural networks and changes in the organization of the rich-club in HZ and PHN. Diffusion imaging (DTI) data from 89 PHN patients, 76 HZ patients, and 66 healthy controls (HCs) were used to construct corresponding structural networks. Using graph-theoretic analysis, changes in the overall and local characteristics of the structural networks and rich-club organization were analyzed, and their correlations with clinical scales were analyzed. Compared with HCs, PHN patients had reduced global efficiency (Eg), reduced local efficiency (Eloc), a reduced clustering coefficient (Cp), a longer characteristic path length (Lp), and reduced nodal efficiency (Ne) in several brain regions, including the right posterior cingulate gyrus, the right supraoccipital gyrus, the bilateral postcentral gyrus, and the right precuneus; HZ patients had reduced Eg, a longer Lp, and reduced right orbital frontalis suprachiasmatic Ne. Moreover, HZ and PHN patients showed a significant reduction in the strength of rich-club connections. Compared with HZ patients, the intensities of the rich-club and feeder connections were lower in the PHN patients. Moreover, the changes in the structural networks and rich-club organization topology indices of the patients in the HZ and PHN patients were significantly correlated with disease duration, pain scores, and emotional changes. The structural networks of HZ and PHN patients exhibited reduced network transmission efficiency and rich-club connectivity, possibly due to structural damage to the white matter, and this was more obvious in PHN patients. The rich-club connectivity of HZ patients showed incomplete compensation in the acute pain stage.

Neuroanatomy of the nociceptive system: From nociceptors to brain networks

This chapter reviews the neuroanatomy of the nociceptive system and its functional organization. We describe three main compartments of the nervous system that underlie normal nociception and the resulting pain percept: Peripheral, Spinal Cord, and Brain. We focus on how ascending nociceptive processing streams traverse these anatomical compartments, culminating in the multidimensional experience of pain. We also describe neuropathic pain conditions, in which nociceptive processing is abnormal, not only because of the primary effects of a lesion or disease affecting peripheral nerves or the central nervous system (CNS), but also due to secondary effects on ascending pathways and brain networks. We discuss how the anatomical components (circuits/networks) reorganize under various etiologies of neuropathic pain and how these changes can give rise to pathological pain states.

Investigating the brain functional abnormalities underlying pain hypervigilance in chronic neck and shoulder pain: a resting-state fMRI study

PURPOSE

To investigate pain hypervigilance in individuals suffering from chronic neck and shoulder pain (CNSP) and its underlying brain mechanism.

METHODS

The evaluation of pain vigilance was conducted through the utilization of pain vigilance and awareness questionnaires. Voxel-wise regional homogeneity (ReHo) from 60 CNSP patients and 60 healthy controls (HCs) using resting-state fMRI data. Voxel-wise two-sample T-test was conducted to reveal the ReHo variations between CNSP and HC. Correlation analyses were utilized to reveal the connection between brain abnormalities and medical measurements. Furthermore, a mediation analysis was conducted to elucidate the pathway-linking changes in brain function with medical measurements.

RESULTS

Our present study revealed three main findings. Firstly, patients with CSNP demonstrated a heightened vigilance of pain in comparison to healthy adults, a common occurrence among individuals with chronic pain conditions. Secondly, we observed brain abnormalities in various brain regions in CSNP patients, and these alterations were associated with the extent of pain vigilance. Lastly, the pain hypervigilance impact on the severity of pain was found to be controlled by regional neural activity in the anterior cingulate cortex (ACC) in subjects with CSNP.

CONCLUSION

Our findings suggested that long-term repetitive nociceptive input caused by chronic pain further aggravates the pain intensity by impairing the vigilance-related pain processing within the anterior cingulate cortex in CNSP patients.

Altered whole-brain functional network in patients with frontal low-grade gliomas: a resting-state functional MRI study

PURPOSE

Gliomas are the most common primary brain tumor. Currently, topological alterations of whole-brain functional network caused by gliomas are not fully understood. The work here clarified the topological reorganization of the functional network in patients with unilateral frontal low-grade gliomas (LGGs).

METHODS

A total of 45 patients with left frontal LGGs, 19 with right frontal LGGs, and 25 healthy controls (HCs) were enrolled. All the resting-state functional MRI (rs-fMRI) images of the subjects were preprocessed to construct the functional network matrix, which was used for graph theoretical analysis. A two-sample t-test was conducted to clarify the differences in global and nodal network metrics between patients and HCs. A network-based statistic approach was used to identify the altered specific pairs of regions in which functional connectivity in patients with LGGs.

RESULTS

The local efficiency, clustering coefficient, characteristic path length, and normalized characteristic path length of patients with unilateral frontal LGGs were significantly lower than HCs, while there were no significant differences of global efficiency and small-worldness between patients and HCs. Compared with the HCs, betweenness centrality, degree centrality, and nodal efficiency of several brain nodes were changed significantly in patients. Around the tumor and its adjacent areas, the inter- and intra-hemispheric connections were significantly decreased in patients with left frontal LGGs.

CONCLUSION

The patients with unilateral frontal LGGs have altered global and nodal network metrics and decreased inter- and intra-hemispheric connectivity. These topological alterations may be involved in functional impairment and compensation of patients.

Functional disruptions of the brain network in low back pain: a graph-theoretical study

PURPOSE

The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics.

METHODS

Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored.

RESULTS

At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity.

CONCLUSION

This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.

Network targets for therapeutic brain stimulation: towards personalized therapy for pain

Precision neuromodulation of central brain circuits is a promising emerging therapeutic modality for a variety of neuropsychiatric disorders. Reliably identifying in whom, where, and in what context to provide brain stimulation for optimal pain relief are fundamental challenges limiting the widespread implementation of central neuromodulation treatments for chronic pain. Current approaches to brain stimulation target empirically derived regions of interest to the disorder or targets with strong connections to these regions. However, complex, multidimensional experiences like chronic pain are more closely linked to patterns of coordinated activity across distributed large-scale functional networks. Recent advances in precision network neuroscience indicate that these networks are highly variable in their neuroanatomical organization across individuals. Here we review accumulating evidence that variable central representations of pain will likely pose a major barrier to implementation of population-derived analgesic brain stimulation targets. We propose network-level estimates as a more valid, robust, and reliable way to stratify personalized candidate regions. Finally, we review key background, methods, and implications for developing network topology-informed brain stimulation targets for chronic pain.

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.

Greater functional connectivity between the ventral frontal cortex and occipital cortex in herpes zoster patients than post-herpetic neuralgia patients

OBJECTIVE

This study aimed to compare whole brain network between herpes zoster (HZ) patients and post-herpetic neuralgia (PHN) patients, as well as to investigate the associations between whole brain network changes and pain intensity and the accuracy of classifying between different types of pain.

METHODS

PHN patients (n = 50) and HZ patients (n = 50) and healthy controls (HCs) (n = 50) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Functional connectivity and global and local graph theory metrics were calculated by using Dosenbach-160 atlas. The relationship between neuroimaging indicators and clinical scales was evaluated using correlation analysis, and receiver operating characteristic (ROC) curves evaluated the feasibility of classifying PHN and HZ patients using specific neuroimaging indicators.

RESULTS

(1) 10 greater average connectivities were found in HZ group among the default mode, frontoparietal, cingulo-opercular, sensorimotor, occipital networks (ONs), and cerebellum (p < 0.001). (2) HZ patients exhibited higher global efficiency than those in the PHN and HCs (t = 2.178, p = 0.038). (3) Multiple linear regression analyses indicated that functional connectivity between the ventral frontal cortex in the cingulo-opercular network and the occipital gyrus in the ON influenced the visual analog score pain scores (β = 4.273; p = 0.004).

CONCLUSION

The variation of functional connectivity between ventral frontal cortex in the cingulo-opercular network and occipital gyrus in the ON may be a robust neuroimaging marker of the transition from HZ to PHN patients.

ADVANCES IN KNOWLEDGE

Whole-brain network analysis may be effective in distinguishing HZ and PHN patients and predicting pain intensity.

Topology of pain networks in patients with temporomandibular disorder and pain-free controls with and without concurrent experimental pain: A pilot study

Temporomandibular disorders (TMD) involve chronic pain in the masticatory muscles and jaw joints, but the mechanisms underlying the pain are heterogenous and vary across individuals. In some cases, structural, functional, and metabolic changes in the brain may underlie the condition. In the present study, we evaluated the functional connectivity between 86 regions of interest (ROIs), which were chosen based on previously reported neuroimaging studies of pain and differences in brain morphology identified in an initial surface-based morphometry analysis. Our main objectives were to investigate the topology of the network formed by these ROIs and how it differs between individuals with TMD and chronic pain (n = 16) and pain-free control participants (n = 12). In addition to a true resting state functional connectivity scan, we also measured functional connectivity during a 6-min application of a noxious cuff stimulus applied to the left leg. Our principal finding is individuals with TMD exhibit more suprathreshold correlations (higher nodal degree) among all ROIs but fewer "hub" nodes (i.e., decreased betweenness centrality) across conditions and across all pain pathways. These results suggest is this pain-related network of nodes may be "over-wired" in individuals with TMD and chronic pain compared to controls, both at rest and during experimental pain.

Rich-club reorganization and related network disruptions are associated with the symptoms and severity in classic trigeminal neuralgia patients

BACKGROUND

Alterations in white matter microstructure and functional activity have been demonstrated to be involved in the central nervous system mechanism of classic trigeminal neuralgia (CTN). However, the rich-club organization and related topological alterations in the CTN brain networks remain unclear.

METHODS

We simultaneously collected diffusion-tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with CTN (9 males, mean age = 54.59 years) and 34 matched healthy controls (HCs) (12 males, mean age = 54.97 years) to construct structural networks (SNs) and functional networks (FNs). Rich-club organization was determined separately based on each group's SN and different kinds of connections. For both network types, we calculated the basic connectivity properties (network density and strength) and topological properties (global/local/nodal efficiency and small worldness). Moreover, SN-FN coupling was obtained. The relationships between all those properties and clinical measures were evaluated.

RESULTS

Compared to their FN, the SN of CTN patients was disrupted more severely, including its topological properties (reduced network efficiency and small-worldness), and a decrease in network density and strength was observed. Patients showed reorganization of the rich-club architecture, wherein the nodes with decreased nodal efficiency in the SN were mainly non-hub regions, and the local connections were closely related to altered global efficiency and whole brain coupling. While the cortical-subcortical connections of feeder were found to be strengthened in the SN of patients, the coupling between networks increased in all types of connections. Finally, disease severity (duration, pain intensity, and affective alterations) was negatively correlated with coupling (rich-club, feeder, and whole brain) and network strength (the rich-club of the SN and local connections of the FN). A positive correlation was only found between pain intensity and the coupling of local connections.

CONCLUSIONS

The SN of patients with CTN may be more vulnerable. Accompanied by the reorganization of the rich-club, the less efficient network communication and the impaired functional dynamics were largely attributable to the dysfunction of non-hub regions. As compensation, the pain transmission pathway of feeder connections involving in pain processing and emotional regulation may strengthen. The local and feeder sub-networks may serve as potential biomarkers for diagnosis or prognosis.

Transcriptional and cellular signatures of cortical morphometric remodelling in chronic pain

ABSTRACT

Chronic pain is a highly debilitating and difficult to treat condition, which affects the structure of the brain. Although the development of chronic pain is moderately heritable, how disease-related alterations at the microscopic genetic architecture drive macroscopic brain abnormalities is currently largely unknown. Here, we examined alterations in morphometric similarity (MS) and applied an integrative imaging transcriptomics approach to identify transcriptional and cellular correlates of these MS changes, in 3 independent small cohorts of patients with distinct chronic pain syndromes (knee osteoarthritis, low back pain, and fibromyalgia) and age-matched and sex-matched pain-free controls. We uncover a novel pattern of cortical MS remodelling involving mostly small-to-medium MS increases in the insula and limbic cortex (none of these changes survived stringent false discovery rate correction for the number of regions tested). This pattern of changes is different from that observed in patients with major depression and cuts across the boundaries of specific pain syndromes. By leveraging transcriptomic data from Allen Human Brain Atlas, we show that cortical MS remodelling in chronic pain spatially correlates with the brain-wide expression of genes related to pain and broadly involved in the glial immune response and neuronal plasticity. Our findings bridge levels to connect genes, cell classes, and biological pathways to in vivo imaging correlates of chronic pain. Although correlational, our data suggest that cortical remodelling in chronic pain might be shaped by multiple elements of the cellular architecture of the brain and identifies several pathways that could be prioritized in future genetic association or drug development studies.

Altered Brain Topological Property Associated With Anxiety in Experimental Orthodontic Pain

BACKGROUND

Orthodontic pain is orofacial pain caused by tooth movement. Anxiety is a strong predictor of the severity of such pain, but little is known about the underlying neuropsychological mechanisms of such effects. The purpose of this study was to investigate the effect of orthodontic pain on brain functional networks and to define the mediating role of anxiety in orthodontic pain and brain function.

METHODS

Graph theory-based network analyses were applied to brain functional magnetic resonance imaging data from 48 healthy participants exposed to 24 h orthodontic pain stimuli and 49 healthy controls without any stimulation.

RESULTS

In the experimental orthodontic pain stimulation, brain functional networks retained a small-world organization. At the regional level, the nodal centrality of ipsilateral brain nodes to the pain stimulus was enhanced; in contrast the nodal centrality of contralateral brain areas was decreased, especially the right mid-cingulate cortex, which is involved in pain intensity coding. Furthermore, anxiety mediated the relationship between nodal efficiency of mid-cingulate cortex and pain severity.

CONCLUSION

The results illuminate the neural mechanisms of orthodontic pain by revealing unbalanced hemispherical brain function related to the unilateral pain stimulation, and reveal clinically exploitable evidence that anxiety mediates the relationship between nodal function of right mid-cingulate cortex and orthodontic pain.

Functional Disruptions of the Brain in Low Back Pain: A Potential Imaging Biomarker of Functional Disability

Chronic low back pain (LBP) is one of the leading causes of disability worldwide. While LBP research has largely focused on the spine, many studies have demonstrated a restructuring of human brain architecture accompanying LBP and other chronic pain states. Brain imaging presents a promising source for discovering noninvasive biomarkers that can improve diagnostic and prognostication outcomes for chronic LBP. This study evaluated graph theory measures derived from brain resting-state functional connectivity (rsFC) as prospective noninvasive biomarkers of LBP. We also proposed and tested a hybrid feature selection method (Enet-subset) that combines Elastic Net and an optimal subset selection method. We collected resting-state functional MRI scans from 24 LBP patients and 27 age-matched healthy controls (HC). We then derived graph-theoretical features and trained a support vector machine (SVM) to classify patient group. The degree centrality (DC), clustering coefficient (CC), and betweenness centrality (BC) were found to be significant predictors of patient group. We achieved an average classification accuracy of 83.1% (p < 0.004) and AUC of 0.937 (p < 0.002), respectively. Similarly, we achieved a sensitivity and specificity of 87.0 and 79.7%. The classification results from this study suggest that graph matrices derived from rsFC can be used as biomarkers of LBP. In addition, our findings suggest that the proposed feature selection method, Enet-subset, might act as a better technique to remove redundant variables and improve the performance of the machine learning classifier.

Enhanced amygdala-frontal operculum functional connectivity during rest in women with chronic neck pain: Associations with impaired conditioned pain modulation

BACKGROUND

Chronic neck pain is a leading cause of disability worldwide, affecting the lives of millions of people. Research investigating functional brain alterations in relation to somatosensory function is necessary to better understand mechanisms underlying pain development and maintenance in individuals with chronic neck pain, yet remains scarce. This case-control study aimed to examine resting-state functional connectivity alterations and associations with pain outcomes, self-reported central sensitization-related symptoms and quantitative sensory testing (QST) measures in patients with chronic non-traumatic (idiopathic/CINP) neck pain and chronic traumatic (whiplash associated/CWAD) neck pain compared to pain-free controls.

METHODS

Resting-state functional magnetic resonance images were acquired in 107 female participants (38 CINP, 37 CWAD, 32 healthy controls). After data pre-processing, seed-to-seed analyses were conducted focusing on resting-state functional connectivity involving pre-defined regions of interest that have previously been observed to be structurally or functionally altered and/or associated with pain-related measures in this patient population.

RESULTS

Findings demonstrate enhanced left amygdala functional coupling during rest with the left frontal operculum in women with CINP and CWAD compared to controls. This increased resting-state functional connectivity was associated with more self-reported symptoms related to central sensitization and decreased efficacy of conditioned pain modulation. Furthermore, enhanced connectivity between the left amygdala and left frontal orbital cortex, and between the left pallidum and the left frontal operculum was observed only in patients with CWAD compared to healthy controls. In patients, additional associations between local hyperalgesia and enhanced connectivity between the left superior parietal cortex and the left and right precentral gyrus were found.

CONCLUSIONS

In line with our hypotheses, patients with CWAD showed the most pronounced alterations in resting-state functional connectivity, encompassing subcortical limbic (amygdala) and basal ganglia (pallidum), and ventral frontal regions (frontal operculum, orbitofrontal cortex) when compared to CINP and controls. Findings are generally in line with the idea of a continuum, in absence of significant group differences across CINP and CWAD. Enhanced amygdala-frontal operculum functional connectivity was the most robust and only connectivity pair in the cluster that was associated with QST (i.e., dynamic QST; endogenous pain inhibition), and that was observed in both patient groups. In addition, independent of group differences, enhanced resting-state functional connectivity between superior parietal cortex (involved in attention) and primary motor cortex was associated with static QST (i.e., greater local hyperalgesia). Taken together, our findings show a key role for enhanced amygdala-ventral frontal circuitry in chronic neck pain, and its association with diminished endogenous pain inhibition further emphasizes the link between cognitive-affective and sensory modulations of pain in women with chronic non-traumatic and traumatic neck pain.

Magnetic Resonance Spectroscopy Assessment of Brain Metabolite Concentrations in Individuals With Chronic Whiplash-associated Disorder: A Cross-sectional Study

OBJECTIVES

Pathophysiologic mechanisms underpinning ongoing pain in whiplash-associated disorder (WAD) are not well understood, however, alterations in brain morphology and function have been observed in this population and in other chronic pain conditions. This study investigated metabolite profiles of brain regions in people with chronic WAD compared with controls.

MATERIALS AND METHODS

Thirty-eight individuals with chronic WAD (mean [SD] age, 39.5 [11.3] years, 23 female individuals) and 16 pain-free controls (38.9 [12.7] years, 11 female individuals) underwent multivoxel brain magnetic resonance spectroscopy. At the anterior cingulate cortex (ACC), primary motor cortex (1MC), and somatosensory cortex (SSC), ratios of metabolite concentrations were calculated for N-acetylaspartate (NAA), creatine (Cr), choline (Cho), myo-inositol (Ins), and glutamate/glutamine (Glx). Chronic WAD group participants completed clinical questionnaires and cold and pressure pain threshold assessment. Data were analyzed with hypothesis testing and Spearman correlations (P≥0.05), with Benjamini-Hochberg corrections (5% false discovery rate).

RESULTS

No group differences were observed for NAA:Cr, NAA:Cho, Cr:Cho, Glx:NAA, Glx:Cr, Glx:Cho, Ins:NAA, Ins:Cr, Ins:Cho or Ins:Glx for left or right ACC, 1MC, or SSC following correction for multiple comparisons. No significant correlations were observed between metabolite ratios and any clinical variable.

DISCUSSION

These results suggest that ongoing pain and disability in this population may not be underpinned by metabolite aberrations in the brain regions examined. Further research is required to progress our understanding of cortical contributions to neurophysiologic mechanisms in chronic WAD.

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.

Reorganization of functional brain network architecture in chronic osteoarthritis pain

Osteoarthritis (OA) manifests with chronic pain, motor impairment, and proprioceptive changes. However, the role of the brain in the disease is largely unknown. Here, we studied brain networks using the mathematical properties of graphs in a large sample of knee and hip OA (KOA, n = 91; HOA, n = 23) patients. We used a robust validation strategy by subdividing the KOA data into discovery and testing groups and tested the generalizability of our findings in HOA. Despite brain global topological properties being conserved in OA, we show there is a network wide pattern of reorganization that can be captured at the subject‐level by a single measure, the hub disruption index. We localized reorganization patterns and uncovered a shift in the hierarchy of network hubs in OA: primary sensory and motor regions and parahippocampal gyrus behave as hubs and insular cortex loses its central placement. At an intermediate level of network structure, frontoparietal and cingulo‐opercular modules showed preferential reorganization. We examined the association between network properties and clinical correlates: global disruption indices and isolated degree properties did not reflect clinical parameters; however, by modeling whole brain nodal degree properties, we identified a distributed set of regions that reliably predicted pain intensity in KOA and generalized to hip OA. Together, our findings reveal that while conserving global topological properties, brain network architecture reorganizes in OA, at both global and local scale. Network connectivity related to OA pain intensity is dissociated from the major hub disruptions, challenging the extent of dependence of OA pain on nociceptive signaling.