SCIseg: Automatic Segmentation of T2-weighted Intramedullary Lesions in Spinal Cord Injury.

Purpose: To develop a deep learning tool for the automatic segmentation of T2-weighted intramedullary lesions in spinal cord injury (SCI). Material and Methods: This retrospective study included a cohort of SCI patients from three sites enrolled between July 2002 and February 2023. A deep learning model, SCIseg, was trained in a three-phase process involving active learning for the automatic segmentation of intramedullary SCI lesions and the spinal cord. The data consisted of T2-weighted MRI acquired using different scanner manufacturers with heterogeneous image resolutions (isotropic/anisotropic), orientations (axial/sagittal), lesion etiologies (traumatic/ischemic/hemorrhagic) and lesions spread across the cervical, thoracic and lumbar spine. The segmentations from the proposed model were visually and quantitatively compared with other open-source baselines. Wilcoxon signed-rank test was used to compare quantitative MRI biomarkers (lesion volume, lesion length, and maximal axial damage ratio) computed from manual lesion masks and those obtained automatically with SCIseg predictions. Results: MRI data from 191 SCI patients (mean age, 48.1 years ± 17.9 [SD]; 142 males) were used for model training and evaluation. SCIseg achieved the best segmentation performance for both the cord and lesions. There was no statistically significant difference between lesion length and maximal axial damage ratio computed from manually annotated lesions and those obtained using SCIseg. Conclusion: Automatic segmentation of intramedullary lesions commonly seen in SCI replaces the tedious manual annotation process and enables the extraction of relevant lesion morphometrics in large cohorts. The proposed model segments lesions across different etiologies, scanner manufacturers, and heterogeneous image resolutions. SCIseg is open-source and accessible through the Spinal Cord Toolbox.

Peak Slope Ratio of the Recruitment Curves Compared to Muscle Evoked Potentials to Optimize Standing Configurations with Percutaneous Epidural Stimulation after Spinal Cord Injury.

Background: Percutaneous spinal cord epidural stimulation (pSCES) has effectively restored varying levels of motor control in persons with motor complete spinal cord injury (SCI). Studying and standardizing the pSCES configurations may yield specific motor improvements. Previously, reliance on the amplitude of the SCES-evoked potentials (EPs) was used to determine the correct stimulation configurations. Methods: We, hereby, retrospectively examined the effects of wide and narrow-field configurations on establishing the motor recruitment curves of motor units of three different agonist-antagonist muscle groups. Magnetic resonance imaging was also used to individualize SCI participants (n = 4) according to their lesion characteristics. The slope of the recruitment curves using a six-degree polynomial function was calculated to derive the slope ratio for the agonist-antagonist muscle groups responsible for standing. Results: Axial damage ratios of the spinal cord ranged from 0.80 to 0.92, indicating at least some level of supraspinal connectivity for all participants. Despite the close range of these ratios, standing motor performance was enhanced using different stimulation configurations in the four persons with SCI. A slope ratio of ≥1 was considered for the recommended configurations necessary to achieve standing. The retrospectively identified configurations using the supine slope ratio of the recruitment curves of the motor units agreed with that visually inspected muscle EPs amplitude of the extensor relative to the flexor muscles in two of the four participants. Two participants managed to advance the selected configurations into independent standing performance after using tonic stimulation. The other two participants required different levels of assistance to attain standing performance. Conclusions: The findings suggest that the peak slope ratio of the muscle agonists-antagonists recruitment curves may potentially identify the pSCES configurations necessary to achieve standing in persons with SCI.

Sagittal balance parameters measurement on cervical spine MR images based on superpixel segmentation.

Introduction: Magnetic Resonance Imaging (MRI) is essential in diagnosing cervical spondylosis, providing detailed visualization of osseous and soft tissue structures in the cervical spine. However, manual measurements hinder the assessment of cervical spine sagittal balance, leading to time-consuming and error-prone processes. This study presents the Pyramid DBSCAN Simple Linear Iterative Cluster (PDB-SLIC), an automated segmentation algorithm for vertebral bodies in T2-weighted MR images, aiming to streamline sagittal balance assessment for spinal surgeons. Method: PDB-SLIC combines the SLIC superpixel segmentation algorithm with DBSCAN clustering and underwent rigorous testing using an extensive dataset of T2-weighted mid-sagittal MR images from 4,258 patients across ten hospitals in China. The efficacy of PDB-SLIC was compared against other algorithms and networks in terms of superpixel segmentation quality and vertebral body segmentation accuracy. Validation included a comparative analysis of manual and automated measurements of cervical sagittal parameters and scrutiny of PDB-SLIC's measurement stability across diverse hospital settings and MR scanning machines. Result: PDB-SLIC outperforms other algorithms in vertebral body segmentation quality, with high accuracy, recall, and Jaccard index. Minimal error deviation was observed compared to manual measurements, with correlation coefficients exceeding 95%. PDB-SLIC demonstrated commendable performance in processing cervical spine T2-weighted MR images from various hospital settings, MRI machines, and patient demographics. Discussion: The PDB-SLIC algorithm emerges as an accurate, objective, and efficient tool for evaluating cervical spine sagittal balance, providing valuable assistance to spinal surgeons in preoperative assessment, surgical strategy formulation, and prognostic inference. Additionally, it facilitates comprehensive measurement of sagittal balance parameters across diverse patient cohorts, contributing to the establishment of normative standards for cervical spine MR imaging.

A Single Dermatome Clinical Prediction Rule for Independent Walking 1 Year After Spinal Cord Injury.

OBJECTIVE: To derive and validate a simple, accurate CPR to predict future independent walking ability after SCI at the bedside that does not rely on motor scores and is predictive for those initially classified in the middle of the SCI severity spectrum. DESIGN: Retrospective cohort study. Binary variables were derived, indicating degrees of sensation to evaluate predictive value of pinprick and light touch variables across dermatomes. The optimal single sensory modality and dermatome was used to derive our CPR, which was validated on an independent dataset. SETTING: Analysis of SCI Model Systems dataset. PARTICIPANTS: Individuals with traumatic SCI. The data of 3679 participants (N=3679) were included with 623 participants comprising the derivation dataset and 3056 comprising the validation dataset. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Self-reported ability to walk both indoors and outdoors. RESULTS: Pinprick testing at S1 over lateral heels, within 31 days of SCI, accurately identified future independent walkers 1 year after SCI. Normal pinprick in both lateral heels provided good prognosis, any pinprick sensation in either lateral heel provided fair prognosis, and no sensation provided poor prognosis. This CPR performed satisfactorily in the middle SCI severity subgroup. CONCLUSIONS: In this large multi-site study, we derived and validated a simple, accurate CPR using only pinprick sensory testing at lateral heels that predicts future independent walking after SCI.

Evaluating tissue injury in cervical spondylotic myelopathy with spinal cord MRI: a systematic review.

PURPOSE: Cervical Spondylotic Myelopathy (CSM) is a degenerative condition that leads to loss of cervical spinal cord (CSC) integrity. Various spinal cord Magnetic Resonance Imaging (MRI) methods can identify and characterize the extent of this damage. This systematic review aimed to evaluate the diagnostic, biomarker, and predictive utilities of different spinal cord MRI methods in clinical research studies of CSM. The aim was to provide a comprehensive understanding of the progress in this direction for future studies and effective diagnosis and management of CSM. METHODS: A comprehensive literature search was conducted on PubMed and EMBASE from 2010 to 2022 according to PRISMA guidelines. Studies with non-human subjects, less than 3T magnetic field strength, non-clinical design, or not quantitatively focusing on the structural integrity of CSC were excluded. The extracted data from each study included demographics, disease severity, MRI machine characteristics, quantitative metrics, and key findings in terms of diagnostic, biomarker, and predictive utilities of each MRI method. The risk of bias was performed using the guide from AHRQ. The quality of evidence was assessed separately for each type of utility for different MRI methods using GRADE. RESULTS: Forty-seven studies met the inclusion criteria, utilizing diffusion-weighted imaging (DTI) (n = 39), magnetization transfer (MT) (n = 6), MR spectroscopy (n = 3), and myelin water imaging (n = 1), as well as a combination of MRI methods (n = 12). The metric fractional anisotropy (FA) showed the highest potential in all facets of utilities, followed by mean diffusivity. Other promising metrics included MT ratio and intracellular volume fraction, especially in multimodal studies. However, the level of evidence for these promising metrics was low due to a small number of studies. Some studies, mainly DTI, also reported the usefulness of spinal cord MRI in mild CSM. CONCLUSIONS: Spinal cord MRI methods can potentially facilitate the diagnosis and management of CSM by quantitatively interrogating the structural integrity of CSC. DTI is the most promising MRI method, and other techniques have also shown promise, especially in multimodal configurations. However, this field is in its early stages, and more studies are needed to establish the usefulness of spinal cord MRI in CSM.

Reduced Spinal Cord Gray Matter in Patients with Fibromyalgia Using Opioids Long-term.

Objective: Chronic pain involves alterations in brain gray matter volume (GMV). Moreover, opioid medications are known to reduce GMV in numerous brain regions involved in pain processing. However, no research has evaluated (1) chronic pain-related GMV alterations in the spinal cord or (2) the effect of opioids on spinal cord GMV. Accordingly, this study evaluated spinal cord GMV in health controls and patients with fibromyalgia who were using and not using opioids long-term. Methods: We analyzed average C5 - C7 GMV of the spinal cord dorsal and ventral horns in separate female cohorts of healthy controls (HC, n = 30), fibromyalgia patients not using opioids (FMN, n = 31), and fibromyalgia patients using opioids long-term (FMO, n = 27). To assess the effect of group on average dorsal and ventral horn GMV, we conducted a one-way multivariate analysis of covariance. Results: After controlling for age, we observed a significant effect of group on ventral horn GMV (p = 0.03, η2 = 0.09), and on dorsal horn GMV (p = 0.05, η2 = 0.08). Tukey's posthoc comparisons showed that, compared to HC participants, FMOs had significantly lower ventral (p = 0.01) and dorsal (p = 0.02) GMVs. Among FMOs only, ventral horn GMV was significantly positively associated with pain severity and interference, and both dorsal and ventral GMVs were significantly positively associated with cold pain tolerance. Conclusion: Long-term opioid use may impact sensory processing in fibromyalgia via gray matter changes within the cervical spinal cord.

Isolating Neurologic Deficits in Cervical Spondylotic Myelopathy: A Case-Controlled Study, Using the NIH Toolbox Motor Battery.

Background and Objectives: Patients with cervical spondylotic myelopathy (CSM) have motor impairments, including weakness, imbalance, and loss of dexterity. The reliable assessment of these symptoms is critical for treatment decisions. This study aimed to determine, for the first time, the use of the NIH Toolbox motor battery (NIHTBm) in the objective assessment of motor deficits in patients with CSM. Methods: Patients with symptoms and MRI evidence of CSM and age-matched healthy controls (HC), with no evidence of spinal disorder or surgery were included in this case-control study based on our inclusion and exclusion criteria. We performed motor tests, dexterity, gait speed, grip strength, and balance tests, using the NIHTBm in patients with CSM and HCs. Motor impairment rates were determined in patients with CSM based on the NIHTBm scores. We determined the association between NIHTBm scores and patient-reported outcome scores; patient-reported outcome measures (the modified Japanese Orthopedic Association [mJOA] and Nurick grade) to determine the association. One-way analysis of variance was used to analyze group differences and the Spearman rank correlation to determine the relationship between assessment scores. Results: We enrolled 24 patients with CSM with a mean age (SD) of 57.96 (10.61) years and 24 age-matched HCs with a mean age (SD) of 53.17 (6.04) years in this study. Overall, we observed a significant decrease in the motor function T-scores mean (SD): dexterity 31.54 (14.82) vs 51.54 (9.72), grip strength 32.00 (17.47) vs 56.79 (8.46), balance 27.58 (16.65) vs 40.21 (6.35), and gait speed 0.64 (0.18) vs 0.99 (0.17) m/s, in patients with CSM compared with that in HCs. The lower extremity dysfunction scores on the NIHTBm, balance (ρ = -0.67) and gait speed (ρ = -0.62), were associated with higher Nurick grades. We observed a similar but weaker association with the Nurick grades and NIHTBm tests: dexterity (ρ = -0.49) and grip strength (ρ = -0.31) scores. The total motor mJOA showed a positive but weak association with NIHTBm scores, gait speed (ρ = 0.38), balance (ρ = 0.49), grip strength (ρ = 0.41), and dexterity (ρ = 0.45). Discussion: Patients with CSM had significantly lower NIHTBm scores compared with HCs. The results from the NIHTBm are consistent with the clinical presentation of CSM showing patients have motor impairments in both upper and lower extremities. As a neurologic-specific scale, NIHTBm should be used in the evaluation and clinical management of patients with CSM.

Predicting Outdoor Walking 1 Year After Spinal Cord Injury: A Retrospective, Multisite External Validation Study.

BACKGROUND AND PURPOSE: Predicting future outdoor walking ability after spinal cord injury (SCI) is important, as this is associated with community engagement and social participation. A clinical prediction rule (CPR) was derived for predicting outdoor walking 1 year after SCI. While promising, this CPR has not been validated, which is necessary to establish its clinical value. The objective of this study was to externally validate the CPR using a multisite dataset. METHODS: This was a retrospective analysis of US SCI Model Systems data from 12 centers. L3 motor score, L5 motor score, and S1 sensory score were used as predictor variables. The dataset was split into testing and training datasets. The testing dataset was used as a holdout dataset to provide an unbiased estimate of prediction performance. The training dataset was used to determine the optimal CPR threshold through a "leave-one-site-out" cross-validation framework. The primary outcome was self-reported outdoor walking ability 1 year after SCI. RESULTS: A total of 3721 participants' data were included. Using the optimal CPR threshold (CPR ≥ 33 threshold value), we were able to predict outdoor walking 1 year with high cross-validated accuracy and prediction performance. For the entire dataset, area under receiver operator characteristic curve was 0.900 (95% confidence interval: 0.890-0.910; P < 0.0001). DISCUSSION AND CONCLUSIONS: The outdoor walking CPR has been externally validated. Future research should conduct a clinical outcomes and cost-benefit impact analysis for implementing this CPR. Our results support that clinicians may use this 3-variable CPR for prediction of future outdoor walking ability.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A411 ).

The influence of conventional T2 MRI indices in predicting who will walk outside one year after spinal cord injury.

Context/Objective: Magnetic resonance imaging (MRI) indices of spinal cord damage are predictive of future motor function after spinal cord injury (SCI): hyperintensity length, midsagittal tissue bridges, and Brain and Spinal Injury Center (BASIC) scores. Whether these indices are predictive of outdoor walking after SCI is unknown. The primary purpose was to see if these MRI indices predict the ability to walk outdoors one-year after SCI. The secondary purpose was to determine if MRI indices provide additional predictive value if initial lower extremity motor scores are available.Design: Retrospective. Clinical T2-weighted MRIs were used to quantify spinal cord damage. Three MRI indices were calculated: midsagittal ventral tissue bridges, hyperintensity length, BASIC scores.Setting: Academic hospital.Participants: 129 participants with cervical SCI.Interventions: Inpatient rehabilitation.Outcomes Measures: One year after SCI, participants self-reported their outdoor walking ability.Results: Midsagittal ventral tissue bridges, hyperintensity length, and BASIC scores significantly correlated with outdoor walking ability (R = 0.34, P < 0.001; R = -0.25, P < 0.01; Rs = -0.35, P < 001, respectively). Using midsagittal ventral tissue bridges and hyperintensity length, the final adjusted R2 for model 1 = 0.19. For model 2, the adjusted R2 using motor scores alone = 0.81 and MRI variables were non-significant. All five participants with observable intramedullary hemorrhage reported they were unable to walk one block outdoors.Conclusions: The MRI indices were significant predictors of outdoor walking ability, but when motor scores were available, this was the strongest predictor and neither midsagittal tissue bridges nor hyperintensity length contributed additional value. MRI indices may be a quick and convenient supplement to physical examination when motor testing is unavailable.

Greater muscle volume and muscle fat infiltrate in the deep cervical spine extensor muscles (multifidus with semispinalis cervicis) in individuals with chronic idiopathic neck pain compared to age and sex-matched asymptomatic controls: a cross-sectional study.

Muscle size and composition (muscle volume and muscle fat infiltrate [MFI]) may provide insight into possible mechanisms underpinning chronic idiopathic neck pain, a common condition with no definitive underlying pathology. In individuals with chronic idiopathic neck pain > 3 months and age- and sex-matched asymptomatic controls, muscle volumes of levator scapulae, multifidus including semispinalis cervicis (MFSS), semispinalis capitis, splenius capitis including splenius cervicis (SCSC), sternocleidomastoid and longus colli from C3 through T1 were quantified from magnetic resonance imaging. Between-group differences were determined using linear mixed models, accounting for side (left or right), muscle, spinal level, sex, age, and body mass index (BMI). Individuals with pain had greater muscle volume (mean difference 76.8mm3; 95% CI 26.6-127.0; p = .003) and MFI (2.3%; 0.2-4.5; p = .034) of the MFSS compared to matched controls with no differences in relative volume, accounting for factors associated with the outcomes: muscle, spinal level, side (left had smaller volume, relative volume and MFI than right), sex (females had less volume and relative volume than males), age (older age associated with less relative volume and greater MFI), and BMI (higher BMI associated with greater muscle volume and MFI). Greater MFI in individuals with chronic idiopathic neck pain suggests a possible underlying mechanism contributing to neck pain. Perspective: These findings suggest MFI in the MFSS may be radiologic sign, potentially identifying patients with a less favourable prognosis. Future studies are needed to confirm this finding and determine if MFI is a contributor to the development or persistence of neck pain, or consequence of neck pain.

Effects of variability in manually contoured spinal cord masks on fMRI co-registration and interpretation.

Functional magnetic resonance imaging (fMRI) of the human spinal cord (SC) is a unique non-invasive method for characterizing neurovascular responses to stimuli. Group-analysis of SC fMRI data involves co-registration of subject-level data to standard space, which requires manual masking of the cord and may result in bias of group-level SC fMRI results. To test this, we examined variability in SC masks drawn in fMRI data from 21 healthy participants from a completed study mapping responses to sensory stimuli of the C7 dermatome. Masks were drawn on temporal mean functional image by eight raters with varying levels of neuroimaging experience, and the rater from the original study acted as a reference. Spatial agreement between rater and reference masks was measured using the Dice Similarity Coefficient, and the influence of rater and dataset was examined using ANOVA. Each rater's masks were used to register functional data to the PAM50 template. Gray matter-white matter signal contrast of registered functional data was used to evaluate the spatial normalization accuracy across raters. Subject- and group-level analyses of activation during left- and right-sided sensory stimuli were performed for each rater's co-registered data. Agreement with the reference SC mask was associated with both rater (F(7, 140) = 32.12, P < 2 × 10-16, η2 = 0.29) and dataset (F(20, 140) = 20.58, P < 2 × 10-16, η2 = 0.53). Dataset variations may reflect image quality metrics: the ratio between the signal intensity of spinal cord voxels and surrounding cerebrospinal fluid was correlated with DSC results (p < 0.001). As predicted, variability in the manually-drawn masks influenced spatial normalization, and GM:WM contrast in the registered data showed significant effects of rater and dataset (rater: F(8, 160) = 23.57, P < 2 × 10-16, η2 = 0.24; dataset: F(20, 160) = 22.00, P < 2 × 10-16, η2 = 0.56). Registration differences propagated into subject-level activation maps which showed rater-dependent agreement with the reference. Although group-level activation maps differed between raters, no systematic bias was identified. Increasing consistency in manual contouring of spinal cord fMRI data improved co-registration and inter-rater agreement in activation mapping, however our results suggest that improvements in image acquisition and post-processing are also critical to address.

Towards defining muscular regions of interest from axial magnetic resonance imaging with anatomical cross-reference: a scoping review of lateral hip musculature.

BACKGROUND: Measures of hip muscle morphology and composition (e.g., muscle size and fatty infiltration) are possible with magnetic resonance imaging (MRI). Standardised protocols or guidelines do not exist for evaluation of hip muscle characteristics, hindering reliable and valid inter-study analysis. This scoping review aimed to collate and synthesise MRI methods for measuring lateral hip muscle size and fatty infiltration to inform the future development of standardised protocols. METHODS: Five electronic databases (Medline, CINAHL, Embase, SportsDISCUS and AMED) were searched. Healthy or musculoskeletal pain populations that used MRI to assess lateral hip muscle size and fatty infiltration were included. Lateral hip muscles of interest included tensor fascia late (TFL), gluteus maximus, gluteus medius, and gluteus minimus. Data on MRI parameters, axial slice location, muscle size and fatty infiltrate measures were collected and analysed. Cross referencing for anatomical locations were made between MRI axial slice and E-12 anatomical plastinate sections. RESULTS: From 2684 identified publications, 78 studies contributed data on volume (n = 31), cross sectional area (CSA) (n = 24), and fatty infiltration (n = 40). Heterogeneity was observed for MRI parameters and anatomical boundaries scrutinizing hip muscle size and fatty infiltration. Seven single level axial slices were identified that provided consistent CSA measurement, including three for both gluteus maximus and TFL, and four for both gluteus medius and minimus. For assessment of fatty infiltration, six axial slice locations were identified including two for TFL, and four for each of the gluteal muscles. CONCLUSIONS: Several consistent anatomical levels were identified for single axial MR slice to facilitate muscle size and fatty infiltration muscle measures at the hip, providing the basis for reliable and accurate data synthesis and improvements in the validity of future between studies analyses. This work establishes the platform for standardised methods for the MRI assessment of lateral hip musculature and will aid in the examination of musculoskeletal conditions around the hip joint. Further studies into whole muscle measures are required to further optimise methodological parameters for hip muscle assessment.

Improving the measurement of intrinsic foot muscle morphology and composition from high-field (7T) magnetic resonance imaging.

Magnetic resonance imaging (MRI) can be used to quantify intrinsic foot muscle morphology and composition. Due to the high spatial resolution required to adequately capture the architecturally complex anatomy, manual segmentation is time consuming and not clinically feasible. The aim of this study was to evaluate if a reduced number of MRI slices can be used to accurately estimate intrinsic foot muscle volume and composition. A three-dimensional 2-point Dixon sequence of the whole foot was acquired at 7-Tesla for thirteen asymptomatic individuals and twenty individuals with plantar heel pain. Slice intervals of 2, 3, 5, 10, 15 and 30 were used to calculate alternative muscle volume and composition, and were compared to reference values calculated from every available slice. Agreement between methods was assessed by calculating mean differences and 95% limits of agreement, and inspection of Bland -Altman plots. In both groups, slice intervals of 2, 3 and 5 provided excellent precision for all muscles (measurement error < 1%). Larger slice intervals of 10, 15 and 30 provided excellent precision for some muscles, but for other muscles (e.g. small forefoot muscles), error was up to 7.3%. Bland-Altman plots showed no systematic measurement bias. This study provides a quantitative basis for selecting a reduced number of slices to measure intrinsic foot muscle volume and composition from MRI. A slice interval of 10 may provide a balance between efficiency (36 mins vs. 6 h) and accuracy (error < 2.4%) across all intrinsic foot muscles in asymptomatic individuals and those with plantar heel pain.

Spinal Cord Tissue Bridges Validation Study: Predictive Relationships With Sensory Scores Following Cervical Spinal Cord Injury.

Background: Using magnetic resonance imaging (MRI), widths of ventral tissue bridges demonstrated significant predictive relationships with future pinprick sensory scores, and widths of dorsal tissue bridges demonstrated significant predictive relationships with future light touch sensory scores, following spinal cord injury (SCI). These studies involved smaller participant numbers, and external validation of their findings is warranted. Objectives: The purpose of this study was to validate these previous findings using a larger independent data set. Methods: Widths of ventral and dorsal tissue bridges were quantified using MRI in persons post cervical level SCI (average 3.7 weeks post injury), and pinprick and light touch sensory scores were acquired at discharge from inpatient rehabilitation (average 14.3 weeks post injury). Pearson product-moments were calculated and linear regression models were created from these data. Results: Wider ventral tissue bridges were significantly correlated with pinprick scores (r = 0.31, p < 0.001, N = 136) and wider dorsal tissue bridges were significantly correlated with light touch scores (r = 0.31, p < 0.001, N = 136) at discharge from inpatient rehabilitation. Conclusion: This retrospective study's results provide external validation of previous findings, using a larger sample size. Following SCI, ventral tissue bridges hold significant predictive relationships with future pinprick sensory scores and dorsal tissue bridges hold significant predictive relationships with future light touch sensory scores.

Preventive Supplementation of Omega-3 Reduces Pain and Pro-inflammatory Cytokines in a Mouse Model of Complex Regional Pain Syndrome Type I.

Complex regional pain syndrome type I (CRPS-I) is a condition that responds poorly to treatments. The role of omega-3 fatty acids in the treatment of inflammatory disorders is well described in the literature; however, few studies have evaluated its therapeutic benefits in different types of pain. We evaluated the potential antihyperalgesic and anti-inflammatory effects of preventive omega-3 supplementation in an animal model of CRPS-I. In experiment 1, Swiss female mice were supplemented for 30 days with omega-3 before the induction of the CRPS-I model and 14 days after. Mechanical hyperalgesia was evaluated at baseline and from the 4th to the 14th day after CPRS-I induction along with open field locomotor activity after 30 days of supplementation. In experiment 2, Swiss female mice were supplemented for 30 days with omega-3 and then subjected to the CRPS-I model. Twenty-four hours later the animals were euthanized, and tissue samples of the spinal cord and right posterior paw muscle were taken to measure pro-inflammatory cytokine TNF and IL-1ß concentrations. Omega-3 supplementation produced antihyperalgesic and anti-inflammatory effects, as well as reducing pro-inflammatory cytokine concentrations, without altering the animals' locomotion. No open field locomotor changes were found. The 30-day supplementation at the tested dose was effective in the CRPS-I model.

Utilization of Mid-Thigh Magnetic Resonance Imaging to Predict Lean Body Mass and Knee Extensor Strength in Obese Adults.

Purpose: To train and test a machine learning model to automatically measure mid-thigh muscle cross-sectional area (CSA) to provide rapid estimation of appendicular lean mass (ALM) and predict knee extensor torque of obese adults. Methods: Obese adults [body mass index (BMI) = 30-40 kg/m2, age = 30-50 years] were enrolled for this study. Participants received full-body dual-energy X-ray absorptiometry (DXA), mid-thigh MRI, and completed knee extensor and flexor torque assessments via isokinetic dynamometer. Manual segmentation of mid-thigh CSA was completed for all MRI scans. A convolutional neural network (CNN) was created based on the manual segmentation to develop automated quantification of mid-thigh CSA. Relationships were established between the automated CNN values to the manual CSA segmentation, ALM via DXA, knee extensor, and flexor torque. Results: A total of 47 obese patients were enrolled in this study. Agreement between the CNN-automated measures and manual segmentation of mid-thigh CSA was high (>0.90). Automated measures of mid-thigh CSA were strongly related to the leg lean mass (r = 0.86, p < 0.001) and ALM (r = 0.87, p < 0.001). Additionally, mid-thigh CSA was strongly related to knee extensor strength (r = 0.76, p < 0.001) and moderately related to knee flexor strength (r = 0.48, p = 0.002). Conclusion: CNN-measured mid-thigh CSA was accurate compared to the manual segmented values from the mid-thigh. These values were strongly predictive of clinical measures of ALM and knee extensor torque. Mid-thigh MRI may be utilized to accurately estimate clinical measures of lean mass and function in obese adults.

Differences in Structural Brain Characteristics Between Individuals with Chronic Nonspecific Neck Pain and Asymptomatic Controls: A Case-Control Study.

BACKGROUND: Neck pain is a prevalent and costly problem, but its underlying mechanisms are poorly understood. Neuroimaging studies show alterations in brain morphometry in chronic musculoskeletal pain, but reports on neck pain are scarce. OBJECTIVE: This study investigates (1) differences in brain morphometry between individuals with chronic nonspecific neck pain and asymptomatic individuals and (2) associations between brain morphometry and patient-reported outcomes. METHODS: Sixty-three participants (33 pain, 11 female, mean [SD] age 35 [10] years; 30 control, 12 female, age 35 [11] years) underwent magnetic resonance imaging. Brain regions of interest (ROIs) were determined a priori, outcomes included cortical thickness and volume. Between-group differences were determined using cluster-wise correction for multiple comparisons and analyses of pain-related ROIs. RESULTS: Between-group differences in volume were identified in the precentral, frontal, occipital, parietal, temporal, and paracentral cortices. ROI analyses showed that parahippocampal cortical thickness was larger in the neck pain group (p=0.015, 95% CI: -0.27 to -0.03). Moderate to strong associations between volume and thickness of the cingulate cortex, prefrontal cortex, and temporal lobe and neck pain duration, pain intensity, and neck disability were identified (p-values 0.006 to 0.048). CONCLUSION: Alterations in brain morphology that are associated with clinical characteristics inform the mechanisms underlying chronic nonspecific neck pain and may guide the development of more effective treatment approaches.

Confounds in neuroimaging: A clear case of sex as a confound in brain-based prediction.

Muscle weakness is common in many neurological, neuromuscular, and musculoskeletal conditions. Muscle size only partially explains muscle strength as adaptions within the nervous system also contribute to strength. Brain-based biomarkers of neuromuscular function could provide diagnostic, prognostic, and predictive value in treating these disorders. Therefore, we sought to characterize and quantify the brain's contribution to strength by developing multimodal MRI pipelines to predict grip strength. However, the prediction of strength was not straightforward, and we present a case of sex being a clear confound in brain decoding analyses. While each MRI modality-structural MRI (i.e., gray matter morphometry), diffusion MRI (i.e., white matter fractional anisotropy), resting state functional MRI (i.e., functional connectivity), and task-evoked functional MRI (i.e., left or right hand motor task activation)-and a multimodal prediction pipeline demonstrated significant predictive power for strength (R 2 = 0.108-0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R 2 = -0.038-0.075). Next, we flipped the analysis and demonstrated that each MRI modality and a multimodal prediction pipeline could significantly predict sex (accuracy = 68.0%-93.3%, AUC = 0.780-0.982, p < 0.001). However, correcting the brain features for strength reduced the accuracy for predicting sex (accuracy = 57.3%-69.3%, AUC = 0.615-0.780). Here we demonstrate the effects of sex-correlated confounds in brain-based predictive models across multiple brain MRI modalities for both regression and classification models. We discuss implications of confounds in predictive modeling and the development of brain-based MRI biomarkers, as well as possible strategies to overcome these barriers.