Patellofemoral joint geometry and osteoarthritis features 3-10 years after knee injury compared with uninjured knees.

In this cross-sectional study, we compared patellofemoral geometry in individuals with a youth-sport-related intra-articular knee injury to uninjured individuals, and the association between patellofemoral geometry and magnetic resonance imaging (MRI)-defined osteoarthritis (OA) features. In the Youth Prevention of Early OA (PrE-OA) cohort, we assessed 10 patellofemoral geometry measures in individuals 3-10 years following injury compared with uninjured individuals of similar age, sex, and sport, using mixed effects linear regression. We also dichotomized geometry to identify extreme (>1.96 standard deviations) features and assessed likelihood of having extreme values using Poisson regression. Finally, we evaluated the associations between patellofemoral geometry with MRI-defined OA features using restricted cubic spline regression. Mean patellofemoral geometry did not differ substantially between groups. However, compared with uninjured individuals, injured individuals were more likely to have extremely large sulcus angle (prevalence ratio [PR] 3.9 [95% confidence interval, CI: 2.3, 6.6]), and shallow lateral trochlear inclination (PR 4.3 (1.1, 17.9)) and trochlear depth (PR 5.3 (1.6, 17.4)). In both groups, high bisect offset (PR 1.7 [1.3, 2.1]) and sulcus angle (PR 4.0 [2.3, 7.0]) were associated with cartilage lesion, and most geometry measures were associated with at least one structural feature, especially cartilage lesions and osteophytes. We observed no interaction between geometry and injury. Certain patellofemoral geometry features are correlated with higher prevalence of structural lesions compared with injury alone, 3-10 years following knee injury. Hypotheses generated in this study, once further evaluated, could contribute to identifying higher-risk individuals who may benefit from targeted treatment aimed at preventing posttraumatic OA.

Self-supervised-RCNN for medical image segmentation with limited data annotation.

Many successful methods developed for medical image analysis based on machine learning use supervised learning approaches, which often require large datasets annotated by experts to achieve high accuracy. However, medical data annotation is time-consuming and expensive, especially for segmentation tasks. To overcome the problem of learning with limited labeled medical image data, an alternative deep learning training strategy based on self-supervised pretraining on unlabeled imaging data is proposed in this work. For the pretraining, different distortions are arbitrarily applied to random areas of unlabeled images. Next, a Mask-RCNN architecture is trained to localize the distortion location and recover the original image pixels. This pretrained model is assumed to gain knowledge of the relevant texture in the images from the self-supervised pretraining on unlabeled imaging data. This provides a good basis for fine-tuning the model to segment the structure of interest using a limited amount of labeled training data. The effectiveness of the proposed method in different pretraining and fine-tuning scenarios was evaluated based on the Osteoarthritis Initiative dataset with the aim of segmenting effusions in MRI datasets of the knee. Applying the proposed self-supervised pretraining method improved the Dice score by up to 18% compared to training the models using only the limited annotated data. The proposed self-supervised learning approach can be applied to many other medical image analysis tasks including anomaly detection, segmentation, and classification.

Comparison of Dynamic Knee Contact Mechanics with T2 Imaging in Different Ages of Healthy Participants.

Aging is a known risk factor for Osteoarthritis (OA), however, relations between cartilage composition and aging remain largely unknown in understanding human OA. T2 imaging provides an approach to assess cartilage composition. Whether these T2 relaxation times in the joint contact region change with time during gait remain unexplored. The study purpose was to demonstrate a methodology for linking dynamic joint contact mechanics to cartilage composition as measured by T2 relaxometry. T2 relaxation times for unloaded cartilage were measured in a 3T General Electric magnetic resonance (MR) scanner in this preliminary study. High-speed biplanar video-radiography (HSBV) was captured for five 20-30-year-old and five 50-60-year-old participants with asymptomatic knees. By mapping the T2 cartilages to the dynamic contact regions, T2 values were averaged over the contact area at each measurement within the gait cycle. T2 values demonstrated a functional relationship across the gait cycle. There were no statistically significant differences between 20- and 30-year-old and 50-60-year-old participant T2 values at first force peak of the gait cycle in the medial femur (p = 1.00, U = 12) or in the medial tibia (p = 0.31, U = 7). In the medial and lateral femur in swing phase, the joint moved from a region of high T2 values at 75% of gait to a minimum at 85-95% of swing. The lateral femur and tibia demonstrated similar patterns to the medial compartments but were less pronounced. This research advances understanding of the linkage between cartilage contact and cartilage composition. The change from a high T2 value at ~ 75% of gait to a lower value near the initiation of terminal swing (90% gait) indicates that there are changes to T2 averages corresponding to changes in the contact region across the gait cycle. No differences were found between age groups for healthy participants. These preliminary findings provide interesting insights into the cartilage composition corresponding to dynamic cyclic motion and inform mechanisms of osteoarthritis.

Tricompartment offloader knee brace reduces sagittal plane knee moments, quadriceps muscle activity, and pain during chair rise and lower in individuals with knee osteoarthritis.

The Levitation tricompartment offloader (TCO) knee brace provides an assistive knee extension moment with the goal of unloading all three compartments of the knee and reducing pain for individuals with multicompartment knee osteoarthritis (OA). This study aimed to determine the effect of the TCO brace on sagittal plane knee moments, quadriceps muscle activity, and pain in individuals with multicompartment knee OA. Lower limb kinematics, kinetics, and electromyography data were collected during a chair rise and lower to determine differences between bracing conditions. TCO brace use significantly decreased the peak net knee external flexion moment in high power mode, providing extension assistance during chair rise [p<0.001; mean difference (MD) (98.75% CI) -0.8 (-1.0, -0.6)%BWxH] and bodyweight support during chair lower [p<0.001; -1.1 (-1.6, -0.7)%BWxH]. Quadriceps activation intensity was significantly reduced with brace use by up to 67% for the vastus medialis [Z = -2.55, p = 0.008] and up to 39% for the vastus lateralis [Z = -2.67, p = 0.004]. Participants reported significantly reduced knee pain with the TCO brace worn in high power mode compared to the no brace condition [p = 0.014; MD (97.5% CI) -18.8 (-32.22, -2.34) mm]. These results support the intended mechanism of joint unloading via extension assistance with the TCO brace. The observed biomechanical changes were accompanied by immediate reductions in user reported pain levels, and support the use of the TCO for conservative management to reduce knee pain in patients with multicompartment knee OA.

Tricompartment offloader knee brace reduces contact forces in adults with multicompartment knee osteoarthritis.

The levitation tricompartment offloader (TCO) brace is designed to unload all three knee compartments by reducing compressive forces caused by muscle contraction. This study aimed to determine the effect of the TCO on knee contact forces and quadriceps muscle activity in individuals with knee osteoarthritis. Lower limb kinematics, kinetics, and electromyography data were collected during a chair rise-and-lower task. A three-dimensional inverse dynamics model of the lower leg and foot was used with a sagittal plane knee model to compute knee joint forces. TCO brace use significantly decreased forces in the tibiofemoral [p = 0.001; mean difference, MD (97.5% confidence interval, CI) -0.62 (-0.91, -0.33) body weight (BW)] and patellofemoral [p = 0.001; MD (97.5% CI) -0.88 (-1.36, -0.39) BW] compartments in high-power mode. Significant reductions in quadriceps tendon force [p = 0.002; MD (97.5% CI) -0.53 (-0.83, -0.23) BW] and electromyography intensity of the vastus medialis [p = 0.018, MD (97.5% CI) -30.7 (-59.1, -2.3)] and vastus lateralis [p = 0.012, MD (97.5% CI) -26.2 (-48.5, -3.9)] were also observed. The TCO significantly reduced tibiofemoral and patellofemoral contact forces throughout chair lower, and when knee flexion was greater than 50° during chair rise in high power. These results demonstrate that the TCO reduces contact forces in the tibiofemoral and patellofemoral joint compartments and confirms that the TCO unloads the joint by reducing compressive forces caused by the quadriceps. Clinical significance: The magnitude of knee joint unloading provided by the TCO is similar to that achieved by clinically recommended levels of bodyweight loss and is therefore expected to result in clinical benefits for knee osteoarthritis patients.

The influence of smoothing techniques on the accuracy of the reference finite helical axis when applied to 2D-3D registrations.

Highspeed Biplanar Videoradiography (HSBV) permits recording of 3D bone movements with sub-millimeter precision. 2D-3D registrations are performed to quantify bone movements, providing a series of affine transformation matrices (ATMs). These registrations may result in alignment errors that produce inaccurate kinematics. Smoothing techniques can be applied to the ATMs to reduce these inaccuracies. Which techniques are best for this application remain unknown. The purpose of this study was to investigate the performance of six smoothing techniques on ATMs obtained from HSBV. Performance was assessed by measuring the accuracy of three reference finite helical axis (rFHA) measures during a turntable rotation: orientation, dispersion, and rotation speed difference (RSD = rFHA RS-turntable RS). A 3D printed femur and tibia were mounted to the turntable and rotations recorded with HSBV. The rFHA was calculated for the bones using each smoothing technique and ranked using a Friedman test. The relative percent change to the unsmoothed data was reported. A spline filter with outlier removal (SPOUT) was ranked the best technique, producing the most accurate RSDs for the femur (-79.64%) and tibia (-70.59%). SPOUT was the top performing smoothing technique. Further investigations using SPOUT are required for in-vivo human movements.

The effect of axillary crutch length on upper limb kinematics during swing-through gait.

BACKGROUND: Axillary crutches are commonly used in rehabilitation. Inappropriately fit crutches may result in upper limb pain or injury. OBJECTIVE: To investigate the effects of axillary crutch length on upper limb kinematics to better understand potential injury mechanisms. It was hypothesized that crutches that were longer or shorter than standard-fit crutches would alter upper limb kinematics. DESIGN: Cross-sectional. SETTING: Gait laboratory. PARTICIPANTS: Fifteen healthy males with no prior crutch experience. INTERVENTIONS: Participants were fit with axillary crutches using standardized methods, as well as with crutches that were 5 cm longer and 5 cm shorter. Participants performed swing-through gait (1.20 ± 0.07 ms-1 ) with all crutch lengths in randomized order. Kinematics were recorded using an optical motion-tracking system and joint angles for the scapula, shoulder, elbow, and wrist were computed. MAIN OUTCOME MEASURES: The effects of crutch length on joint range of motion (ROM) and joint angles at initial crutch contact were analyzed using multivariate analysis (Hotelling's T2 ; α = .025) and simultaneous confidence intervals (CI). RESULTS: The long-standard crutch fit comparison showed effects across all joints (ROM p = .009; initial contact p < .001). Longer crutches resulted in greater scapular upward rotation (mean difference [95% CI] ROM: 1.0 [-0.2 to 2.2]; initial contact: -2.7 [-4.4, -1.1]) and shoulder abduction (ROM: 0.8 [-0.1 to 1.8]; initial contact: -1.9 [-4.1 to 0.3]). Crutch length also had effects across all joints for the short-standard fit comparison (ROM p = .004; initial contact p = .016). Shorter crutches resulted in greater scapula downward rotation (2.2 [-0.4 to 4.8]) and greater shoulder adduction (2.5 [-0.6 to 5.6]) at initial contact. Shorter crutches also reduced shoulder flexion/extension ROM (-2.5 [-4.4 to -0.6]). CONCLUSIONS: Altered crutch length results in scapular and shoulder kinematic deviations that may present risk factors for upper limb injury with crutch-walking. This may underline the importance of appropriate device fitting to reduce injury risk in crutch users.

Empirical joint contact mechanics: A comprehensive review.

Empirical joint contact mechanics measurement (EJCM; e.g. contact area or force, surface velocities) enables critical investigations of the relationship between changing joint mechanics and the impact on surface-to-surface interactions. In orthopedic biomechanics, understanding the changes to cartilage contact mechanics following joint pathology or aging is critical due to its suggested role in the increased risk of osteoarthritis (OA), which might be due to changed kinematics and kinetics that alter the contact patterns within a joint. This article reviews and discusses EJCM approaches that have been applied to articulating joints such that readers across different disciplines will be informed of the various measurement and analysis techniques used in this field. The approaches reviewed include classical measurement approaches (radiographic and sectioning, dye staining, casting, surface proximity, and pressure measurement), stereophotogrammetry/motion analysis, computed tomography (CT), magnetic resonance imaging (MRI), and high-speed videoradiography. Perspectives on approaches to advance this field of EJCM are provided, including the value of considering relative velocity in joints, tractional stress, quantification of joint contact area shape, consideration of normalization techniques, net response (superposition) of multiple input variables, and establishing linkages to regional cartilage health status. EJCM measures continue to provide insights to advance our understanding of cartilage health and degeneration and provide avenues to assess the efficacy and guide future directions of developing interventions (e.g. surgical, biological, rehabilitative) to optimize joint's health and function long term.

Kinematics of the head and associated vertebral artery length changes during high-velocity, low-amplitude cervical spine manipulation.

BACKGROUND: Cervical spine manipulation (CSM) is a frequently used treatment for neck pain. Despite its demonstrated efficacy, concerns regarding the potential of stretch damage to vertebral arteries (VA) during CSM remain. The purpose of this study was to quantify the angular displacements of the head relative to the sternum and the associated VA length changes during the thrust phase of CSM. METHODS: Rotation and lateral flexion CSM procedures were delivered bilaterally from C1 to C7 to three male cadaveric donors (Jan 2016-Dec 2019). For each CSM the force-time profile was recorded using a thin, flexible pressure pad (100-200 Hz), to determine the timing of the thrust. Three dimensional displacements of the head relative to the sternum were recorded using an eight-camera motion analysis system (120-240 Hz) and angular displacements of the head relative to the sternum were computed in Matlab. Positive kinematic values indicate flexion, left lateral flexion, and left rotation. Ipsilateral refers to the same side as the clinician's contact and contralateral, the opposite. Length changes of the VA were recorded using eight piezoelectric ultrasound crystals (260-557 Hz), inserted along the entire vessel. VA length changes were calculated as D = (L1 - L0)/L0, where L0 = length of the whole VA (sum of segmental lengths) or the V3 segment at CSM thrust onset; L1 = whole VA or V3 length at peak force during the CSM thrust. RESULTS: Irrespective of the type of CSM, the side or level of CSM application, angular displacements of the head and associated VA length changes during the thrust phase of CSM were small. VA length changes during the thrust phase were largest with ipsilateral rotation CSM (producing contralateral head rotation): [mean ± SD (range)] whole artery [1.3 ± 1.0 (- 0.4 to 3.3%)]; and V3 segment [2.6 ± 3.6 (- 0.4 to 11.6%)]. CONCLUSIONS: Mean head angular displacements and VA length changes were small during CSM thrusts. Of the four different CSM measured, mean VA length changes were largest during rotation procedures. This suggests that if clinicians wish to limit VA length changes during the thrust phase of CSM, consideration should be given to the type of CSM used.

Concurrent validity and reliability of a semi-automated approach to measuring the magnetic resonance imaging morphology of the knee joint in active youth.

Post-traumatic knee osteoarthritis is attributed to alterations in joint morphology, alignment, and biomechanics triggered by injury. While magnetic resonance (MR) imaging-based measures of joint morphology and alignment are relevant to understanding osteoarthritis risk, time consuming manual data extraction and measurement limit the number of outcomes that can be considered and deter widespread use. This paper describes the development and evaluation of a semi-automated software for measuring tibiofemoral and patellofemoral joint architecture using MR images from youth with and without a previous sport-related knee injury. After prompting users to identify and select key anatomical landmarks, the software can calculate 37 (14 tibiofemoral, 23 patellofemoral) relevant geometric features (morphology and alignment) based on established methods. To assess validity and reliability, 11 common geometric features were calculated from the knee MR images (proton density and proton density fat saturation sequences; 1.5 T) of 76 individuals with a 3-10-year history of youth sport-related knee injury and 76 uninjured controls. Spearman's or Pearson's correlation coefficients (95% CI) and Bland-Altman plots were used to assess the concurrent validity of the semi-automated software (novice rater) versus expert manual measurements, while intra-class correlation coefficients (ICC2,1; 95%CI), standard error of measurement (95%CI), 95% minimal detectable change, and Bland-Altman plots were used to assess the inter-rater reliability of the semi-automated software (novice vs resident radiologist rater). Correlation coefficients ranged between 0.89 (0.84, 0.92; Lateral Trochlear Inclination) and 0.97 (0.96, 0.98; Patellar Tilt Angle). ICC estimates ranged between 0.79 (0.63, 0.88; Lateral Patellar Tilt Angle) and 0.98 (0.95, 0.99; Bisect Offset). Bland-Altman plots did not reveal systematic bias. These measurement properties estimates are equal, if not better than previously reported methods suggesting that this novel semi-automated software is an accurate, reliable, and efficient alternative method for measuring large numbers of geometric features of the tibiofemoral and patellofemoral joints from MR studies.

Improved-Mask R-CNN: Towards an accurate generic MSK MRI instance segmentation platform (data from the Osteoarthritis Initiative).

INTRODUCTION: Objective assessment of osteoarthritis (OA) Magnetic Resonance Imaging (MRI) scans can address the limitations of the current OA assessment approaches. Detecting and extracting bone, cartilage, and joint fluid is a necessary component for the objective assessment of OA, which helps to quantify tissue characteristics such as volume and thickness. Many algorithms, based on Artificial Intelligence (AI), have been proposed over recent years for segmenting bone and soft tissues. Most of these segmentation methods suffer from the class imbalance problem, can't differentiate between the same anatomic structure, or do not support segmenting different rang of tissue sizes. Mask R-CNN is an instance segmentation framework, meaning it segments and distinct each object of interest like different anatomical structures (e.g. bone and cartilage) using a single model. In this study, the Mask R-CNN architecture was deployed to address the need for a segmentation method that is applicable to use for different tissue scales, pathologies, and MRI sequences associated with OA, without having a problem with imbalanced classes. In addition, we modified the Mask R-CNN to improve segmentation accuracy around instance edges. METHODS: A total of 500 adult knee MRI scans from the publicly available Osteoarthritis Initiative (OAI), and 97 hip MRI scans from adults with symptomatic hip OA, evaluated by two readers, were used for training and validating the network. Three specific modifications to Mask R-CNN yielded the improved-Mask R-CNN (iMaskRCNN): an additional ROIAligned block, an extra decoder block in the segmentation header, and connecting them using a skip connection. The results were evaluated using Hausdorff distance, dice score for bone and cartilage segmentation, and differences in detected volume, dice score, and coefficients of variation (CoV) for effusion segmentation. RESULTS: The iMaskRCNN led to improved bone and cartilage segmentation compared to Mask RCNN as indicated with the increase in dice score from 95% to 98% for the femur, 95-97% for the tibia, 71-80% for the femoral cartilage, and 81-82% for the tibial cartilage. For the effusion detection, the dice score improved with iMaskRCNN 72% versus Mask R-CNN 71%. The CoV values for effusion detection between Reader1 and Mask R-CNN (0.33), Reader1 and iMaskRCNN (0.34), Reader2 and Mask R-CNN (0.22), Reader2 and iMaskRCNN (0.29) are close to CoV between two readers (0.21), indicating a high agreement between the human readers and both Mask R-CNN and iMaskRCNN. CONCLUSION: Mask R-CNN and iMaskRCNN can reliably and simultaneously extract different scale articular tissues involved in OA, forming the foundation for automated assessment of OA. The iMaskRCNN results show that the modification improved the network performance around the edges.

Validation of a magnetic resonance imaging based method to study passive knee laxity: An in-situ study.

Knee laxity can be described as an increased anterior tibial translation (ATT) or decreased stiffness of the tibiofemoral joint under an applied force. Küpper et al. (2013, 2016) and Westover et al. (2016) previously developed and reported on a magnetic resonance (MR)-based in vivo measure of knee laxity. In this study, the application of an in situ knee loading apparatus (ISKLA) is presented as a step toward validating the MR-based methodology for measuring ATT and stiffness. The ISKLA is designed to measure these outcome variables using MR imaging and is validated against a gold-standard ElectroForce mechanical test instrument (TA Instruments 3550). Accuracy was assessed through an in situ experimental setup by testing four cadaveric specimens with both the MR-based methodology and in the ElectroForce system. The outcome of the current study showed that the MR-based ATTs and stiffness measurements using the ISKLA were within 1.44-2.10 mm and 0.16-6.14 N/mm, respectively, of the corresponding values measured by the gold standard system. An excellent ICC was observed for ATT (0.97) and good ICC for stiffness (0.87) between the MR and ElectroForce-based systems across all target force levels. These findings suggest that the MR-based approach can be used with satisfactory accuracy and correlation to the gold standard measure.

Secondary consequences of juvenile idiopathic arthritis in children and adolescents with knee involvement: physical activity, adiposity, fitness, and functional performance.

OBJECTIVE: Secondary consequences of juvenile idiopathic arthritis (JIA) may impact long-term health outcomes. This study examined differences in physical activity, cardiorespiratory fitness, adiposity, and functional performance in children and adolescents with JIA compared to their typically developing (TD) peers. METHODS: Participants with JIA (n = 32; 10-20 years old) and their TD peers (n = 35) volunteered for assessments of: daily moderate-to-vigorous physical activity (MVPA, body-worn accelerometer); peak oxygen consumption (VO2 Peak, incremental bike test); fat mass index (FMI, dual-energy X-ray absorptiometry); and triple-single-leg-hop (TSLH) distance. Statistical analyses were performed in R using four linear mixed-effect models with Bonferroni adjustment (⍺ = 0.0125). Fixed effects were group, sex, and age. Participant clusters based on sex and age (within 1.5 years) were considered as random effects. RESULTS: Participants with JIA displayed lower mean daily MVPA than their TD peers [p = 0.006; ß (98.75% CI); -21.2 (-40.4 to -2.9) min]. VO2 Peak [p = 0.019; -1.4 (-2.5 to -0.2) ml/kg/min] decreased with age. Females tended to have lower VO2 Peak [p = 0.045; -6.4 (-13.0 to 0.4) ml/kg/min] and greater adiposity [p = 0.071; 1.4 (-0.1 to 3.0) kg/m2] than males. CONCLUSION: The findings support the need for strategies to promote MVPA participation in children and adolescents with JIA. Sex and age should be considered in research on the consequences of JIA.

Vertical Drop Jump Biomechanics of Patients With a 3- to 10-Year History of Youth Sport-Related Anterior Cruciate Ligament Reconstruction.

BACKGROUND: A better understanding of movement biomechanics after anterior cruciate ligament reconstruction (ACLR) could inform injury prevention, knee injury rehabilitation, and osteoarthritis prevention strategies. PURPOSE: To investigate differences in vertical drop jump (VDJ) biomechanics between patients with a 3- to 10-year history of youth sport-related ACLR and uninjured peers of a similar age, sex, and sport. STUDY DESIGN: Cross-sectional study. Level of evidence III. METHODS: Lower limb kinematics and bilateral ground-reaction forces (GRFs) were recorded for participants performing 10 VDJs. Joint angles and GRF data were analyzed, and statistical analysis was performed using 2 multivariate models. Dependent variables included sagittal (ankle, knee, and hip) and coronal (knee and hip) angles at initial contact and maximum knee flexion, the rate of change of coronal knee angles (35%-90% of the support phase; ie, slopes of linear regression lines), and vertical and mediolateral GRFs (normalized to body weight [BW]). Fixed effects included group, sex, and time since injury. Participant clusters, defined by sex and sport, were considered as random effects. RESULTS: Participants included 48 patients with a history of ACLR and 48 uninjured age-, sex-, and sport-matched controls (median age, 22 years [range, 18-26 years]; 67% female). Patients with ACLR demonstrated steeper negative coronal knee angle slopes (ß = -0.04 deg/% [95% CI, -0.07 to -0.00 deg/%]; P = .025). A longer time since injury was associated with reduced knee flexion (ß = -0.2° [95% CI, -0.3° to -0.0°]; P = .014) and hip flexion (ß = -0.1° [95% CI, -0.2° to -0.0°]; P = .018). Regardless of ACLR history, women displayed greater knee valgus at initial contact (ß = 2.1° [95% CI, 0.4° to 3.8°]; P = .017), greater coronal knee angle slopes (ß = 0.05 deg/% [95% CI, 0.02 to 0.09 deg/%]; P = .004), and larger vertical GRFs (landing: ß = -0.34 BW [95% CI, -0.61 to -0.07 BW]; P = .014) (pushoff: ß = -0.20 BW [95% CI, -0.32 to -0.08 BW]; P = .001). CONCLUSION: Women and patients with a 3- to 10-year history of ACLR demonstrated VDJ biomechanics that may be associated with knee motion control challenges. CLINICAL RELEVANCE: It is important to consider knee motion control during activities such as VDJs when developing injury prevention and rehabilitation interventions aimed at improving joint health after youth sport-related ACLR.

Automatic Assessment Of Hip Effusion From MRI.

Joint effusion is a hallmark of osteoarthritis (OA) associated with stiffness, and may relate to pain, disability, and long-term outcomes. However, it is difficult to quantify accurately. We propose a new Deep Learning (DL) approach for automatic effusion assessment from Magnetic Resonance Imaging (MRI) using volumetric quantification measures (VQM). We developed a new multiplane ensemble convolutional neural network (CNN) approach for 1) localizing bony anatomy and 2) detecting effusion regions. CNNs were trained on femoral head and effusion regions manually segmented from 3856 images (63 patients). Upon validation on a non-overlapping set of 2040 images (34 patients) DL showed high agreement with ground-truth in terms of Dice score (0.85), sensitivity (0.86) and precision (0.83). Agreement of VQM per-patient was high for DL vs experts in term of Intraclass correlation coefficient (ICC)= 0.88[0.80,0.93]. We expect this technique to reduce inter-observer variability in effusion assessment, reducing expert time and potentially improving the quality of OA care.Clinical Relevance- Our technique for automatic assessment of hip MRI can be used for volumetric measurement of effusion. We expect this to reduce variability in OA biomarker assessment and provide more reliable indicators for disease progression.

MRI Knee Domain Translation for Unsupervised Segmentation By CycleGAN (data from Osteoarthritis initiative (OAI)).

Accurate quantification of bone and cartilage features is the key to efficient management of knee osteoarthritis (OA). Bone and cartilage tissues can be accurately segmented from magnetic resonance imaging (MRI) data using supervised Deep Learning (DL) methods. DL training is commonly conducted using large datasets with expert-labeled annotations. DL models perform better if distributions of testing data (target domains) are close to those of training data (source domains). However, in practice, data distributions of images from different MRI scanners and sequences are different and DL models need to re-trained on each dataset separately. We propose a domain adaptation (DA) framework using the CycleGAN model for MRI translation that would aid in unsupervised MRI data segmentation. We have validated our pipeline on five scans from the Osteoarthritis Initiative (OAI) dataset. Using this pipeline, we translated TSE Fat Suppressed MRI sequences to pseudo-DESS images. An improved MaskRCNN (IMaskRCNN) instance segmentation network trained on DESS was used to segment cartilage and femoral head regions in TSE Fat Suppressed sequences. Segmentations of the I-MaskRCNN correlated well with approximated manual segmentation obtained from nearest DESS slices (DICE = 0.76) without the need for retraining. We anticipate this technique will aid in automatic unsupervised assessment of knee MRI using commonly acquired MRI sequences and save experts' time that would otherwise be required for manual segmentation.Clinical relevance- This technique paves the way to automatically convert one MRI sequence to its equivalent as if acquired by a different protocol or different magnet, facilitating robust, hardware-independent automated analysis. For example, routine clinically acquired knee MRI could be converted to high-resolution high-contrast images suitable for automated detection of cartilage defects.

fMRI-Informed EEG for brain mapping of imagined lower limb movement: Feasibility of a brain computer interface.

BACKGROUND: EEG and fMRI have contributed greatly to our understanding of brain activity and its link to behaviors by helping to identify both when and where the activity occurs. This is particularly important in the development of brain-computer interfaces (BCIs), where feed forward systems gather data from imagined brain activity and then send that information to an effector. The purpose of this study was to develop and evaluate a computational approach that enables an accurate mapping of spatial brain activity (fMRI) in relation to the temporal receptors (EEG electrodes) associated with imagined lower limb movement. NEW METHOD: EEG and fMRI data from 16 healthy, male participants while imagining lower limb movement were used for this purpose. A combined analysis of fMRI data and EEG electrode locations was developed to identify EEG electrodes with a high likelihood of capturing imagined lower limb movement originating from various clusters of brain activity. This novel feature selection tool was used to develop an artificial neural network model to classify right and left lower limb movement. RESULTS: Results showed that left versus right lower limb imagined movement could be classified with 66.5% accuracy using this approach. Comparison with existing methods: Adopting a purely data-driven approach for feature selection to use in the right/left classification task resulted in the same accuracy (66.6%) but with reduced interpretability. CONCLUSIONS: The developed fMRI-informed EEG approach could pave the way towards improved brain computer interfaces for lower limb movement while also being applicable to other systems where fMRI could be helpful to inform EEG acquisition and processing.

Volumetric quantitative measurement of hip effusions by manual versus automated artificial intelligence techniques: An OMERACT preliminary validation study.

OBJECTIVE: Preliminary assessment, via OMERACT filter, of manual and automated MRI hip effusion Volumetric Quantitative Measurement (VQM). METHODS: For 358 hips (93 osteoarthritis subjects, bilateral, 2 time points), 2 radiologists performed manual VQM using custom Matlab software. A Mask R-CNN artificial-intelligence (AI) tool was trained to automatically compute joint fluid volumes. RESULTS: Manual VQM had excellent inter-observer reliability (ICC 0.96). AI predicted hip fluid volumes with ICC 0.86 (status), 0.58 (change) vs. 2 human readers. CONCLUSION: Hip joint fluid volumes are reliably assessed by VQM. It is feasible to automate this approach using AI, with promising initial reliability.

EEG differentiates left and right imagined Lower Limb movement.

BACKGROUND: Identifying which EEG signals distinguish left from right leg movements in imagined lower limb movement is crucial to building an effective and efficient brain-computer interface (BCI). Past findings on this issue have been mixed, partly due to the difficulty in collecting and isolating the relevant information. The purpose of this study was to contribute to this new and important literature. RESEARCH QUESTION: Can left versus right imagined stepping be differentiated using the alpha, beta, and gamma frequencies of EEG data at four electrodes (C1, C2, PO3, and PO4)? METHODS: An experiment was conducted with a sample of 16 healthy male participants. They imagined left and right lower limb movements across 60 trials at two time periods separated by one week. Participants were fitted with a 64-electrode headcap, lay supine on a specially designed device and then completed the imagined task while observing a customized computer-generated image of a human walking to signify the left and right steps, respectively. RESULTS: Findings showed that eight of the twelve frequency bands from 4 EEG electrodes were significant in differentiating imagined left from right lower limb movement. Using these data points, a neural network analysis resulted in an overall participant average test classification accuracy of left versus right movements at 63 %. SIGNIFICANCE: Our study provides support for using the alpha, beta and gamma frequency bands at the sensorimotor areas (C1 and C2 electrodes) and incorporating information from the parietal/occipital lobes (PO3 and PO4 electrodes) for focused, real-time EEG signal processing to assist in creating a BCI for those with lower limb compromised mobility.

Consequences of Juvenile Idiopathic Arthritis on Single Leg Squat Performance in Youth.

OBJECTIVE: Juvenile idiopathic arthritis (JIA) affects body structure and function outcomes that may increase the risk of acute joint injury. The purpose of this study was to examine single leg squat (SLS) biomechanics for youth with JIA and their healthy peers. The study design was a matched pair cohort study. METHODS: Sixty-five youth (JIA n = 30; control n = 35) participated in this ethics-approved study. Participants performed 3 sets of 5 consecutive SLS tasks. Disease activity and functional status were assessed using the Juvenile Arthritis Disease Activity Score and Child Health Assessment Questionnaire. Indexed (most-affected leg [JIA]; dominant leg [control]) and contralateral extremity biomechanics were obtained using a 12-camera system. Outcomes included hip flexion/extension (FE), adduction/abduction (AA), and internal/external (IE) rotation range of motion (ROM). Data were analyzed using a multivariate random coefficient model in R (α⍺ = 0.05). RESULTS: A total of 29 matched pairs were analyzed. Youth with JIA had low disease activity and performed the SLS with a more internally rotated hip (indexed leg P = 0.023, ß = -1.9°). Female participants displayed greater hip FE (indexed leg P = 0.015, ß = -4.3°; contralateral leg P = 0.005, ß = -4.8°) and IE ROM (indexed leg P = 0.021, ß = -2.1°) than male participants. Associations were observed for body mass index and hip IE ROM (contralateral leg P = 0.001, ß = -0.4°), knee flexion angle, and hip FE ROM (indexed leg P = 0.001, ß = 0.4°; contralateral leg P = 0.001, ß = 0.5°) and AA (indexed leg P = 0.010, ß = 0.1°; contralateral leg P = 0.002, ß = 0.2°). CONCLUSION: This study identified functional alterations for an SLS in youth with JIA. These findings support the use of physical therapy as part of a multidisciplinary management approach, to restore normal hip posture and movement.