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BackgroundTools, such as the STarTBack Screening Tool (SBT), have been developed to identify risks of progressing to chronic disability in low back pain (LBP) patients in the primary care population. However, less is known about predictors of change in function after treatment in the specialty care population.ObjectiveWe pursued a retrospective observational cohort study involving LBP patients seen in a multidisciplinary specialty clinic to assess which features can predict change in function at follow-up.MethodsThe SBT was administered at initial visit, and a variety of patient characteristics were available in the chart including the presence of chronic overlapping pain conditions (COPCs). Patient Reported Outcomes Measurement Information System-10 (PROMIS-10) global physical health (PH) and global mental health (MH) were measured at baseline and at pragmatic time points during follow-up. Linear regression was used to estimate adjusted associations between available features and changes in PROMIS scores.Results241 patients were followed for a mean of 17.0 ± 7.5 months. Mean baseline pain was 6.7 (SD 2.1), PROMIS-10 global MH score was 44.8 (SD 9.3), and PH score was 39.4 (SD 8.6). 29.7% were low-risk on the SBT, 41.8% were medium-risk, and 28.5% were high-risk. Mean change in MH and PH scores from baseline to the follow-up questionnaire were 0.86 (SD 8.11) and 2.39 (SD 7.52), respectively. Compared to low-risk patients, high-risk patients had a mean 4.35 points greater improvement in their MH score (p= 0.004) and a mean 3.54 points greater improvement in PH score (p= 0.006). Fewer COPCs also predicted greater improvement in MH and PH.ConclusionsSBT and the presence of COPC, which can be assessed at initial presentation to a specialty clinic, can predict change in PROMIS following treatment. Effort is needed to identify other factors that can help predict change in function after treatment in the specialty care setting.

ObjectiveOne aim of the Back Pain Consortium (BACPAC) Research Program is to develop an integrated model of chronic low back pain that is informed by combined data from translational research and clinical trials. We describe efforts to maximize data harmonization and accessibility to facilitate Consortium-wide analyses.MethodsConsortium-wide working groups established harmonized data elements to be collected in all studies and developed standards for tabular and nontabular data (eg, imaging and omics). The BACPAC Data Portal was developed to facilitate research collaboration across the Consortium.ResultsClinical experts developed the BACPAC Minimum Dataset with required domains and outcome measures to be collected by use of questionnaires across projects. Other nonrequired domain-specific measures are collected by multiple studies. To optimize cross-study analyses, a modified data standard was developed on the basis of the Clinical Data Interchange Standards Consortium Study Data Tabulation Model to harmonize data structures and facilitate integration of baseline characteristics, participant-reported outcomes, chronic low back pain treatments, clinical exam, functional performance, psychosocial characteristics, quantitative sensory testing, imaging, and biomechanical data. Standards to accommodate the unique features of chronic low back pain data were adopted. Research units submit standardized study data to the BACPAC Data Portal, developed as a secure cloud-based central data repository and computing infrastructure for researchers to access and conduct analyses on data collected by or acquired for BACPAC.ConclusionsBACPAC harmonization efforts and data standards serve as an innovative model for data integration that could be used as a framework for other consortia with multiple, decentralized research programs.

BackgroundChronic low back pain (cLBP) is a complex with a heterogenous clinical presentation. A better understanding of the factors that contribute to cLBP is needed for accurate diagnosis, optimal treatment, and identification of mechanistic targets for new therapies. The Back Pain Consortium (BACPAC) Research Program provides a unique opportunity in this regard, as it will generate large clinical datasets, including a diverse set of harmonized measurements. The Theoretical Model Working Group was established to guide BACPAC research and to organize new knowledge within a mechanistic framework. This article summarizes the initial work of the Theoretical Model Working Group. It includes a three-stage integration of expert opinion and an umbrella literature review of factors that affect cLBP severity and chronicity.MethodsDuring Stage 1, experts from across BACPAC established a taxonomy for risk and prognostic factors (RPFs) and preliminary graphical depictions. During Stage 2, a separate team conducted a literature review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to establish working definitions, associated data elements, and overall strength of evidence for identified RPFs. These were subsequently integrated with expert opinion during Stage 3.ResultsThe majority (∼80%) of RPFs had little strength-of-evidence confidence, whereas seven factors had substantial confidence for either a positive association with cLBP (pain-related anxiety, serum C-reactive protein, diabetes, and anticipatory/compensatory postural adjustments) or no association with cLBP (serum interleukin 1-beta / interleukin 6, transversus muscle morphology/activity, and quantitative sensory testing).ConclusionThis theoretical perspective will evolve over time as BACPAC investigators link empirical results to theory, challenge current ideas of the biopsychosocial model, and use a systems approach to develop tools and algorithms that disentangle the dynamic interactions among cLBP factors.

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science.

BackgroundT2* relaxation times in the spinal cartilage endplate (CEP) measured using ultra-short echo time magnetic resonance imaging (UTE MRI) reflect aspects of biochemical composition that influence the CEP's permeability to nutrients. Deficits in CEP composition measured using T2* biomarkers from UTE MRI are associated with more severe intervertebral disc degeneration in patients with chronic low back pain (cLBP). The goal of this study was to develop an objective, accurate, and efficient deep-learning-based method for calculating biomarkers of CEP health using UTE images.MethodsMulti-echo UTE MRI of the lumbar spine was acquired from a prospectively enrolled cross-sectional and consecutive cohort of 83 subjects spanning a wide range of ages and cLBP-related conditions. CEPs from the L4-S1 levels were manually segmented on 6,972 UTE images and used to train neural networks utilizing the u-net architecture. CEP segmentations and mean CEP T2* values derived from manually- and model-generated segmentations were compared using Dice scores, sensitivity, specificity, Bland-Altman, and receiver-operator characteristic (ROC) analysis. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated and related to model performance.ResultsCompared with manual CEP segmentations, model-generated segmentations achieved sensitives of 0.80-0.91, specificities of 0.99, Dice scores of 0.77-0.85, area under the receiver-operating characteristic curve values of 0.99, and precision-recall (PR) AUC values of 0.56-0.77, depending on spinal level and sagittal image position. Mean CEP T2* values and principal CEP angles derived from the model-predicted segmentations had low bias in an unseen test dataset (T2* bias =0.33±2.37 ms, angle bias =0.36±2.65°). To simulate a hypothetical clinical scenario, the predicted segmentations were used to stratify CEPs into high, medium, and low T2* groups. Group predictions had diagnostic sensitivities of 0.77-0.86 and specificities of 0.86-0.95. Model performance was positively associated with image SNR and CNR.ConclusionsThe trained deep learning models enable accurate, automated CEP segmentations and T2* biomarker computations that are statistically similar to those from manual segmentations. These models address limitations with inefficiency and subjectivity associated with manual methods. Such techniques could be used to elucidate the role of CEP composition in disc degeneration etiology and guide emerging therapies for cLBP.

PurposeClinical management of disc degeneration in patients with chronic low back pain (cLBP) is hampered by the challenge of distinguishing pathologic changes relating to pain from physiologic changes related to aging. The goal of this study was to use imaging biomarkers of disc biochemical composition to distinguish degenerative changes associated with cLBP from normal aging.MethodsT1ρ MRI data were acquired from 133 prospectively enrolled subjects for this observational study (80 cLBP, 53 controls; mean ± SD age = 43.9 ± 13.4 years; 61 females, 72 males). The mean T1ρ relaxation time in the nucleus pulposus (NP-T1ρ; n = 650 discs) was used as a quantitative biomarker of disc biochemical composition. Linear regression was used to assess associations between NP-T1ρ and age, sex, spinal level, and study group, and their interactions.ResultsNP-T1ρ values were lower in cLBP patients than controls (70.8 ± 22.8 vs. 76.4 ± 22.2 ms, p = 0.009). Group differences were largest at L5-S1 (ΔT1ρcLBP-control = -11.3 ms, p

Chronic low back pain (cLBP) afflicts 8. 2% of adults in the United States, and is the leading global cause of disability. Neuropsychiatric co-morbidities including anxiety, depression, and substance abuse- are common in cLBP patients. In particular, cLBP is a risk factor for opioid addiction, as more than 50% of opioid prescriptions in the United States are for cLBP. Misuse of these prescriptions is a common precursor to addiction. While associations between cLBP and neuropsychiatric disorders are well established, causal relationships for the most part are unknown. Developing effective treatments for cLBP, and associated co-morbidities, requires identifying and understanding causal relationships. Rigorous methods for causal inference, a process for quantifying causal effects from observational data, have been developed over the past 30 years. In this review we first discuss the conceptual model of cLBP that current treatments are based on, and how gaps in causal knowledge contribute to poor clinical outcomes. We then present cLBP as a "Big Data" problem and identify how advanced analytic techniques may close knowledge gaps and improve clinical outcomes. We will focus on causal discovery, which is a data-driven method that uses artificial intelligence (AI) and high dimensional datasets to identify causal structures, discussing both constraint-based (PC and Fast Causal Inference) and score-based (Fast Greedy Equivalent Search) algorithms.

IntroductionMany studies have attempted to link multifidus (MF) fat infiltration with muscle quality and chronic low back pain (cLBP), but there is no consensus on these relationships.MethodsIn this cross-sectional cohort study, 39 cLBP patients and 18 asymptomatic controls were included. The MF muscle was manually segmented at each lumbar disc level and fat fraction (FF) measurements were taken from the corresponding advanced imaging water-fat images. We assessed the distribution patterns of MF fat from L1L2 to L5S1 and compared these patterns between groups. The sample was stratified by age, sex, body mass index (BMI), subject-reported pain intensity (VAS), and subject-reported low back pain disability (oswestry disability index, ODI).ResultsOlder patients had significantly different MF FF distribution patterns compared to older controls (p

PurposeFat infiltration (FI) of the paraspinal muscles (PSMs) measured using MRI is an aspect of muscle quality and is considered to be worse in chronic low back pain (cLBP) patients. However, there is not a clear association between paraspinal muscle FI and cLBP, leaving the clinical importance of paraspinal muscle composition unestablished. The spatial distribution of FI in the PSMs may inform mechanistic understanding of non-specific cLBP as it relates to degenerative intervertebral disc (IVD) pathology. We hypothesized that paraspinal muscle fat-mapping would reveal distinct FI distribution patterns in relation to cLBP symptoms and proximity to symptomatic IVD degeneration.MethodsFrom advanced-sequence water-fat MRI of 40 axial cLBP patients and 21 controls, we examined the spatial distribution of paraspinal muscle FI in relation to the center of rotation at the L4L5 disc. Using statistical parametric mapping, we compared FI patterns for multifidus (MF), erector spinae (ES), and psoas between patients and controls, and to the presence and severity of adjacent degenerative IVD pathology.ResultsThe spatial distribution of PSMs FI differs between PSMs and according to symptoms and the adjacent degenerative IVD pathology. Furthermore, the region of MF closest to the disc center of rotation appears most susceptible to FI in the presence of symptomatic IVD degeneration.ConclusionOur study identified spatial distribution patterns of FI in the PSMs as a potential diagnostic biomarker that may also provide granular mechanistic insights into spine biomechanics related to cLBP, as well as advancing the use of prior summary measures limited to overall muscle FI.

PurposeThe paraspinal muscles (PSM) are a key feature potentially related to low back pain (LBP), and their structure and composition can be quantified using MRI. Most commonly, quantifying PSM measures across individual muscles and individual spinal levels renders numerous separate metrics that are analyzed in isolation. However, comprehensive multivariate approaches would be more appropriate for analyzing the PSM within an individual. To establish and test these methods, we hypothesized that multivariate summaries of PSM MRI measures would associate with the presence of LBP symptoms (i.e., pain intensity).MethodsWe applied hierarchical multiple factor analysis (hMFA), an unsupervised integrative method, to clinical PSM MRI data from unique cohort datasets including a longitudinal cohort of astronauts with pre- and post-spaceflight data and a cohort of chronic LBP subjects and asymptomatic controls. Three specific use cases were investigated: (1) predicting longitudinal changes in pain using combinations of baseline PSM measures; (2) integrating baseline and post-spaceflight MRI to assess longitudinal change in PSM and how it relates to pain; and (3) integrating PSM quality and adjacent spinal pathology between LBP patients and controls.ResultsOverall, we found distinct complex relationships with pain intensity between particular muscles and spinal levels. Subjects with high asymmetry between left and right lean muscle composition and differences between spinal segments PSM quality and structure are more likely to increase in pain reported outcome after prolonged time in microgravity. Moreover, changes in PSM quality and structure between pre and post-spaceflight relate to increase in pain after prolonged microgravity. Finally, we show how unsupervised hMFA recapitulates previous research on the association of CEP damage and LBP diagnostic.ConclusionOur analysis considers the spine as a multi-segmental unit as opposed to a series of discrete and isolated spine segments. Integrative and multivariate approaches can be used to distill large and complex imaging datasets thereby improving the clinical utility of MRI-based biomarkers, and providing metrics for further analytical goals, including phenotyping.

PurposeThe composition of the subchondral bone marrow and cartilage endplate (CEP) could affect intervertebral disc health by influencing vertebral perfusion and nutrient diffusion. However, the relative contributions of these factors to disc degeneration in patients with chronic low back pain (cLBP) have not been quantified. The goal of this study was to use compositional biomarkers derived from quantitative MRI to establish how CEP composition (surrogate for permeability) and vertebral bone marrow fat fraction (BMFF, surrogate for perfusion) relate to disc degeneration.MethodsMRI data from 60 patients with cLBP were included in this prospective observational study (28 female, 32 male; age = 40.0 ± 11.9 years, 19-65 [mean ± SD, min-max]). Ultra-short echo-time MRI was used to calculate CEP T2* relaxation times (reflecting biochemical composition), water-fat MRI was used to calculate vertebral BMFF, and T1ρ MRI was used to calculate T1ρ relaxation times in the nucleus pulposus (NP T1ρ, reflecting proteoglycan content and degenerative grade). Univariate linear regression was used to assess the independent effects of CEP T2* and vertebral BMFF on NP T1ρ. Mixed effects multivariable linear regression accounting for age, sex, and BMI was used to assess the combined relationship between variables.ResultsCEP T2* and vertebral BMFF were independently associated with NP T1ρ (p = 0.003 and 0.0001, respectively). After adjusting for age, sex, and BMI, NP T1ρ remained significantly associated with CEP T2* (p = 0.0001) but not vertebral BMFF (p = 0.43).ConclusionPoor CEP composition plays a significant role in disc degeneration severity and can affect disc health both with and without deficits in vertebral perfusion.

PurposeThis study explores the biomechanics underlying the sit-to-stand (STS) functional maneuver in chronic LBP patients to understand how different spinal disorders and levels of pain severity relate to unique compensatory biomechanical behaviors. This work stands to further our understanding of the relationship between spinal loading and symptoms in LBP patients.MethodsWe collected in-clinic motion data from 44 non-specific LBP (NS-LBP) and 42 spinal deformity LBP (SD-LBP) patients during routine clinical visits. An RGB-depth camera tracked 3D joint positions from the frontal view during unassisted, repeated STS maneuvers. Patient-reported outcomes (PROs) for back pain (VAS) and low back disability (ODI) were collected during the same clinical visit.ResultsBetween patient groups, SD-LBP patients had 14.3% greater dynamic sagittal vertical alignment (dSVA) and 10.1% greater peak spine torque compared to NS-LBP patients (p

Background contextFor chronic low back pain, the causal mechanisms between pathological features from imaging and patient symptoms are unclear. For instance, disc herniations can often be present without symptoms. There remains a need for improved knowledge of the pathophysiological mechanisms that explore spinal tissue damage and clinical manifestations of pain and disability. Spaceflight and astronaut health provides a rare opportunity to study potential low back pain mechanisms longitudinally. Spaceflight disrupts diurnal loading on the spine and several lines of evidence indicate that astronauts are at a heightened risk for low back pain and disc herniation following spaceflight.PurposeTo examine the relationship between prolonged exposure to microgravity and the elevated incidence of postflight disc herniation, we conducted a longitudinal study to track the spinal health of twelve NASA astronauts before and after approximately 6 months in space. We hypothesize that the incidence of postflight disc herniation and low back complaints associates with spaceflight-included muscle atrophy and pre-existing spinal pathology.Study designThis is a prospective longitudinal study.Patient sampleOur sample included a cohort of twelve astronaut crewmembers.Outcome measuresFrom 3T MRI, we quantified disc water content (ms), disc degeneration (Pfirrmann grade), vertebral endplate irregularities, facet arthropathy and/ fluid, high intensity zones, disc herniation, multifidus total cross-sectional area (cm2), multifidus lean muscle cross-sectional area (cm2), and muscle quality/composition (%). From quantitative fluoroscopy we quantified, maximum flexion-extension ROM (°), maximum lateral bending ROM (°), and maximum translation (%). Lastly, patient outcomes and clinical notes were used for identifying postflight symptoms associated with disc herniations from 3T MRI.MethodsAdvanced imaging data from 3T MRI were collected at three separate time points in relation to spending six months in space: (1) within a year before launch ("pre-flight"), (2) within a week after return to Earth ("post-flight"), and (3) between 1 and 2 months after return to Earth ("recovery"). Fluoroscopy of segmental kinematics was collected at preflight and postflight timepoints. We assessed the effect of spaceflight and postflight recovery on longitudinal changes in spinal structure and function, as well as differences between crew members who did and did not present a symptomatic disc herniation following spaceflight.ResultsHalf of our astronauts (n=6) experienced new symptoms associated with a new or previously asymptomatic lumbar disc protrusion or extrusion following spaceflight. We observed decreased multifidus muscle quality following spaceflight in the lower lumbar spine, with a reduced percentage of lean muscle at L4L5 (-6.2%, p=.009) and L5S1 (-7.0%, p=.006) associated with the incidence of new disc herniation. Additionally, we observed reduced lumbar segment flexion-extension ROM for L2L3 (-17.2%, p=.006) and L3L4 (-20.5%, p=.02) following spaceflight, and furthermore that reduced ROM among the upper three lumbar segments (-24.1%, p=.01) associated with the incidence of disc herniation. Existing endplate pathology was most prevalent in the upper lumbar spine and associated with reduced segmental ROM (-20.5%, p=.02).ConclusionsIn conclusion from a 10-year study investigating the effects of spaceflight on the lumbar spine and risk for disc herniation, we found the incidence of lumbar disc herniation following spaceflight associates with compromised multifidus muscle quality and spinal segment kinematics, as well as pre-existing spinal endplate irregularities. These findings suggest differential effects of spinal stiffness and muscle loss in the upper versus lower lumbar spine regions that may specifically provoke risk for symptomatic disc herniation in the lower lumbar spine following spaceflight. Results from this study provide a unique longitudinal assessment of mechanisms and possible risk factors for developing disc herniations and related low back pain. Furthermore, these findings will help inform physiologic countermeasures to maintain spinal health in astronauts during long-duration missions in space.

Chronic low back pain (LBP) is a leading cause of disability and opioid prescriptions worldwide, representing a significant medical and socioeconomic problem. Clinical heterogeneity of LBP limits accurate diagnosis and precise treatment planning, culminating in poor patient outcomes. A current priority of LBP research is the development of objective, multidimensional assessment tools that subgroup LBP patients based on neurobiological pain mechanisms, to facilitate matching patients with the optimal therapies. Using unsupervised machine learning on full body biomechanics, including kinematics, dynamics, and muscle forces, captured with a marker-less depth camera, this study identified a forward-leaning sit-to-stand strategy (STS) as a discriminating movement biomarker for LBP subjects. A forward-leaning STS strategy, as opposed to a vertical rise strategy seen in the control participants, is less efficient and results in increased spinal loads. Inefficient STS with the subsequent higher spinal loading may be a biomarker of poor motor control in LBP patients as well as a potential source of the ongoing symptomology.

PurposeVertebral endplate bone marrow lesions ("Modic changes", MC) are associated with chronic low back pain (CLBP). Bone marrow composition in MC is poorly understood. The goals of this study were to: (1) measure bone marrow fat fraction (BMF) in CLBP patients with MC using water-fat MRI and (2) assess the relationship between BMF measurements and patient-reported clinical characteristics.MethodsIn this cross-sectional study, 42 CLBP patients (men, n = 21; age, 48 ± 12.4 years) and 18 asymptomatic controls (men, n = 10; 42.7 ± 12.8 years) underwent 3 T MRI between January 2016 and July 2018. Imaging consisted of T1- and T2-weighted sequences to evaluate MC and spoiled gradient-recalled echo sequence with asymmetric echoes and least-squares fitting to measure BMF. BMF was compared between vertebrae with and without MC using mixed effects models. The relationship between the BMF measurements and patient-reported disability scores was examined using regression.ResultsTwenty-seven subjects (26 CLBP, 1 control) had MC, and MC presence coincided with significantly altered BMF. In MC 1, BMF was lower than endplates without MC (absolute difference -22.3%; p

Abstract Background The criteria for deciding who should be admitted first from a waiting list to a forensic secure hospital are not necessarily the same as those for assessing need. Criteria were drafted qualitatively and tested in a prospective 'real life' observational study over a 6-month period. Methods A researcher rated all those presented at the weekly referrals meeting using the DUNDRUM-1 triage security scale and the DUNDRUM-2 triage urgency scale. The key outcome measure was whether or not the individual was admitted. Results Inter-rater reliability and internal consistency for the DUNDRUM-2 were acceptable. The DUNDRUM-1 triage security score and the DUNDRUM-2 triage urgency score correlated r = 0.663. At the time of admission, after a mean of 23.9 (SD35.9) days on the waiting list, those admitted had higher scores on the DUNDRUM-2 triage urgency scale than those not admitted, with no significant difference between locations (remand or sentenced prisoners, less secure hospitals) at the time of admission. Those admitted also had higher DUNDRUM-1 triage security scores. At baseline the receiver operating characteristic area under the curve for a combined score was the best predictor of admission while at the time of admission the DUNDRUM-2 triage urgency score had the largest AUC (0.912, 95% CI 0.838 to 0.986). Conclusions The triage urgency items and scale add predictive power to the decision to admit. This is particularly true in maintaining equitability between those referred from different locations.

Abstract Background The assessment of those presenting to prison in-reach and court diversion services and those referred for admission to mental health services is a triage decision, allocating the patient to the appropriate level of therapeutic security. This is a critical clinical decision. We set out to improve on unstructured clinical judgement. We collated qualitative information and devised an 11 item structured professional judgment instrument for this purpose then tested for validity. Methods All those assessed following screening over a three month period at a busy remand committals prison (n = 246) were rated in a retrospective cohort design blind to outcome. Similarly, all those admitted to a mental health service from the same prison in-reach service over an overlapping two year period were rated blind to outcome (n = 100). Results The 11 item scale had good internal consistency (Cronbach's alpha = 0.95) and inter-rater reliability. The scale score did not correlate with the HCR-20 'historical' score. For the three month sample, the receiver operating characteristic area under the curve (AUC) for those admitted to hospital was 0.893 (95% confidence interval 0.843 to 0.943). For the two year sample, AUC distinguished at each level between those admitted to open wards, low secure units or a medium/high secure service. Open wards v low secure units AUC = 0.805 (95% CI 0.680 to 0.930); low secure v medium/high secure AUC = 0.866, (95% CI 0.784 to 0.949). Item to outcome correlations were significant for all 11 items. Conclusions The DUNDRUM-1 triage security scale and its items performed to criterion levels when tested against the real world outcome. This instrument can be used to ensure consistency in decision making when deciding who to admit to secure forensic hospitals. It can also be used to benchmark admission thresholds between services and jurisdictions. In this study we found some divergence between assessed need and actual placement. This provides fertile ground for future research as well as practical assistance in assessing unmet need, auditing case mix and planning care pathways.

Vertebral endplate bone marrow lesions, visualized on magnetic resonance imaging (MRI) as Modic changes (MC), are associated with chronic low back pain (cLBP). Since guidelines recommend against routine spinal MRI for cLBP in primary care, MC may be underdiagnosed. Serum biomarkers for MC would allow early diagnosis, inform clinical care decisions, and supplement treatment monitoring. We aimed to discover biomarkers in the blood serum that correlate with MC pathophysiological processes. For this single-site cross-sectional study, we recruited 54 subjects with 38 cLBP patients and 16 volunteers without a history of LBP. All subjects completed an Oswestry Disability Index (ODI) questionnaire and 10-cm Visual Analog Score (VAS) for LBP (VASback) and leg pain. Lumbar T1-weighted and fat-saturated T2-weighted MRI were acquired at 3T and used for MC classification in each endplate. Blood serum was collected on the day of MRI. Biomarkers related to disc resorption and bone marrow fibrosis were analyzed with enzyme-linked immune-absorbent assays. The concentration of biomarkers between no MC and any type of MC (AnyMC), MC1, and MC2 were compared. The Area Under the Curve (AUC) of the Receiver Operating Characteristics were calculated for each biomarker and for bivariable biomarker models. We found that biomarkers related to type III and type IV collagen degradation and formation tended to correlate with the presence of MC (p = 0.060-0.088). The bivariable model with the highest AUC was PRO-C3 + C4M and had a moderate diagnostic value for AnyMC in cLBP patients (AUC = 0.73, specificity = 78.9%, sensitivity = 73.7%). In conclusion, serum biomarkers related to the formation and degradation of type III and type IV collagen, which are key molecules in bone marrow fibrosis, correlated with MC presence. Bone marrow fibrosis may be an important pathophysiological process in MC that should be targeted in larger biomarker and treatment studies.

PurposeThe positive association between low back pain and MRI evidence of vertebral endplate bone marrow lesions, often called Modic changes (MC), offers the exciting prospect of diagnosing a specific phenotype of chronic low back pain (LBP). However, imprecision in the reporting of MC has introduced substantial challenges, as variations in both imaging equipment and scanning parameters can impact conspicuity of MC. This review discusses key methodological factors that impact MC classification and recommends guidelines for more consistent MC reporting that will allow for better integration of research into this LBP phenotype.MethodsNon-systematic literature review.ResultsThe high diagnostic specificity of MC classification for a painful level contributes to the significant association observed between MC and LBP, whereas low and variable sensitivity underlies the between- and within-study variability in observed associations. Poor sensitivity may be owing to the presence of other pain generators, to the limited MRI resolution, and to the imperfect reliability of MC classification, which lowers diagnostic sensitivity and thus influences the association between MC and LBP. Importantly, magnetic field strength and pulse sequence parameters also impact detection of MC. Advances in pulse sequences may improve reliability and prove valuable for quantifying lesion severity.ConclusionsComparison of MC data between studies can be problematic. Various methodological factors impact detection and classification of MC, and the lack of reporting guidelines hinders interpretation and comparison of findings. Thus, it is critical to adopt imaging and reporting standards that codify acceptable methodological criteria. These slides can be retrieved under Electronic Supplementary Material.

BackgroundThere is an interplay between the intervertebral disc (IVD) and the adjacent bone marrow that may play a role in the development of IVD degeneration and might influence chronic lower back pain (CLBP).PurposeTo apply novel quantitative MRI techniques to assess the relationship between vertebral bone marrow fat (BMF) and biochemical changes in the adjacent IVD.Study typeProspective.SubjectsForty-six subjects (26 female and 20 male) with a mean age of 47.3 ± 12.0 years.Field strength/sequence3 T MRI; a combined T1ρ and T2 mapping pulse sequence and a 3D spoiled gradient recalled sequence with six echoes and iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) reconstruction algorithm.AssessmentUsing quantitative MRI, the vertebral BMF fraction was measured as well as the biochemical composition (proteoglycan and collagen content) of the IVD. Furthermore, clinical Pfirrmann grading, Oswestry disability index (ODI), and visual analog scale (VAS) was assessed.Statistical testsMixed random effects models accounting for multiple measurements per subject were used to assess the relationships between disc measurements and BMF.ResultsThe relationships between BMF (mean) and T1ρ /T2 (mean and SD) were significant, with P