Disease severity versus pain severity: Range of motion differences during single- and multiplanar tasks in women with carpometacarpal osteoarthritis.

In carpometacarpal osteoarthritis (CMC OA) of the thumb, to what extent treatments should be directed by radiographic disease severity versus pain-based indicators remains an open question. To address this gap, this study investigated the relative impact of disease severity and pain severity on the range of motion in participants with CMC OA. We hypothesized larger differences would exist between extremes in the pain severity cohort than the disease severity cohort, suggesting pain modulates movement to a greater extent than joint degradation. Thirty-one female participants (64.6 ± 10.9 years) were grouped as symptomatic or asymptomatic (pain severity cohort) and early stage OA or end-stage OA (disease severity cohort) using radiographs and questionnaires. Kinematics were measured during single-planar and multiplanar range of motion tasks. Joint angle differences between groups were statistically compared. Differences in self-reported pain, function, and disability were evident in both participant cohorts. Notably, substantial distinctions emerged exclusively during multiplanar tasks, with a greater prevalence in the disease severity cohort compared to the pain severity cohort. Participants with end-stage OA also exhibited similar overall area covered during circumduction in comparison to those with early-stage OA, despite having a decreased range of motion at the CMC joint. The study underscores the importance of assessing multiplanar tasks, potentially leading to earlier identification of CMC OA. While movement compensations such as employing the distal thumb joints over the CMC joint were observed, delving deeper into the interplay between pain and movement could yield greater insight into the underlying factors steering these compensatory mechanisms.

Association of Muscle Quality and Pain in Adults With Symptomatic Knee Osteoarthritis, Independent of Muscle Strength: Findings From a Cross-Sectional Study.

OBJECTIVE: Knee osteoarthritis (OA) is a leading cause of chronic pain in adults and shows wide interindividual variability, with peripheral and central factors contributing to the pain experience. Periarticular factors, such as muscle quality (eg, echo intensity [EI] and shear wave velocity [SWV]), may contribute to knee OA pain; however, the role of muscle quality in OA symptoms has yet to be fully established. METHODS: Twenty-six adults (age >50 years) meeting clinical criteria for knee OA were included in this cross-sectional study. Quantitative ultrasound imaging was used to quantify EI and SWV in the rectus femoris of the index leg. Pearson correlations followed by multiple linear regression was used to determine associations between muscle quality and pain, controlling for strength, age, sex, and body mass index. RESULTS: EI and SWV were significantly associated with movement-evoked pain (b = 0.452-0.839, P = 0.024-0.029). Clinical pain intensity was significantly associated with SWV (b = 0.45, P = 0.034), as were pressure pain thresholds at the medial (b = -0.41, P = 0.025) and lateral (b = -0.54, P = 0.009) index knee joint line, adjusting for all covariates. Pain interference was significantly associated with knee extension strength (b = -0.51, P = 0.041). CONCLUSION: These preliminary findings suggest that EI and SWV may impact knee OA pain and could serve as malleable treatment targets. Findings also demonstrate that muscle quality is a unique construct, distinct from muscle strength, which may impact pain and treatment outcomes. More research is needed to fully understand the role of muscle quality in knee OA.

Image Rotation Alters Apparent Fibula Length: An Evaluation of Talocrural Angle, Shenton Line, and Dime Sign.

BACKGROUND: Fibula shortening can compromise ankle stability and force transmission, thereby impacting clinical outcomes. Because radiographs depict 3-dimensional anatomy in 2 dimensions, accurate radiographic assessment of fibula length is a commonly encountered clinical challenge. The talocrural angle (TCA), Shenton line, and dime sign are useful parameters of fibula length. Yet, the impact of 3-dimensional limb positioning on these radiographic parameters is not established. METHODS: Bone models were constructed from CT scans of 30 lower limbs. Fibula length was computationally manipulated, and digitally reconstructed radiographs were generated reflecting 1-degree increments of sagittal and axial plane rotation of each limb for each fibula length condition. The TCA was computationally measured on each image. The presence of an aligned mortise view, intact Shenton line, and intact dime sign was assessed by 2 observers. RESULTS: The mean TCA, which was 78.0 (95% CI ± 1.6) degrees for a true mortise projection with anatomic fibula length, changed by approximately 1 degree per millimeter of fibula length change. On average, 14.7 degrees of caudal rotation obscured 2 mm of fibular shortening by virtue of producing the same TCA as a true mortise view with anatomic fibula length, designated a false positive view. Axial rotation had a comparatively small effect. Observers 1 and 2 were, respectively, 91% and 88% less likely to accurately judge the image alignment of the false positive images compared to true mortise images. Moreover, intraobserver agreement was poor to moderate (mean 0.47, range 0.13-0.59) and interobserver agreement was uniformly poor (mean 0.08, range 0.01-0.20). CONCLUSION: In our study using digitally reconstructed radiographs from CT scans of 30 limbs, we found that sagittal plane rotation impacts the radiographic appearance of fibula length as measured by the TCA. Limb axial rotation had a comparatively small effect. Further study of human perception of Shenton line and dime sign is needed before the effect of rotation on these parameters can be fully understood. LEVEL OF EVIDENCE: Level IV, case series.

Explainable AI Elucidates Musculoskeletal Biomechanics: A Case Study Using Wrist Surgeries.

As datasets increase in size and complexity, biomechanists have turned to artificial intelligence (AI) to aid their analyses. This paper explores how explainable AI (XAI) can enhance the interpretability of biomechanics data derived from musculoskeletal simulations. We use machine learning to classify the simulated lateral pinch data as belonging to models with healthy or one of two types of surgically altered wrists. This simulation-based classification task is analogous to using biomechanical movement and force data to clinically diagnose a pathological state. The XAI describes which musculoskeletal features best explain the classifications and, in turn, the pathological states, at both the local (individual decision) level and global (entire algorithm) level. We demonstrate that these descriptions agree with assessments in the literature and additionally identify the blind spots that can be missed with traditional statistical techniques.

Sensitivity Analysis of Upper Limb Musculoskeletal Models During Isometric and Isokinetic Tasks.

Sensitivity coefficients are used to understand how errors in subject-specific musculoskeletal model parameters influence model predictions. Previous sensitivity studies in the lower limb calculated sensitivity using perturbations that do not fully represent the diversity of the population. Hence, the present study performs sensitivity analysis in the upper limb using a large synthetic dataset to capture greater physiological diversity. The large dataset (n = 401 synthetic subjects) was created by adjusting maximum isometric force, optimal fiber length, pennation angle, and bone mass to induce atrophy, hypertrophy, osteoporosis, and osteopetrosis in two upper limb musculoskeletal models. Simulations of three isometric and two isokinetic upper limb tasks were performed using each synthetic subject to predict muscle activations. Sensitivity coefficients were calculated using three different methods (two point, linear regression, and sensitivity functions) to understand how changes in Hill-type parameters influenced predicted muscle activations. The sensitivity coefficient methods were then compared by evaluating how well the coefficients accounted for measurement uncertainty. This was done by using the sensitivity coefficients to predict the range of muscle activations given known errors in measuring musculoskeletal parameters from medical imaging. Sensitivity functions were found to best account for measurement uncertainty. Simulated muscle activations were most sensitive to optimal fiber length and maximum isometric force during upper limb tasks. Importantly, the level of sensitivity was muscle and task dependent. These findings provide a foundation for how large synthetic datasets can be applied to capture physiologically diverse populations and understand how model parameters influence predictions.

A Secondary Analysis: Comparison of Experimental Pain and Psychological Impact in Individuals with Carpometacarpal and Knee Osteoarthritis.

Purpose: Evaluate sensory and psychological differences in individuals with thumb carpometacarpal (CMC) and/or knee osteoarthritis (OA) pain. This secondary analysis focuses on comparing the effects of OA at large and small joints in community-dwelling adults. Patients and Methods: A total of 434 individuals were recruited from communities in Gainesville, FL and Birmingham, AL. Each participant completed health and clinical history questionnaires, quantitative sensory testing, and physical functional tests. Participants were divided into four groups based on their pain ("CMC pain" (n = 33), "knee pain" (n = 71), "CMC + knee pain" (n = 81), and "pain-free" controls (n = 60)). ANCOVAs were performed to identify significant differences in experimental pain and psychological variables across groups. Results: The "CMC + knee pain" group had lower pressure pain thresholds (lateral knee site, p < 0.01) and higher temporal summation of mechanical pain (knee, p < 0.01) when compared to "CMC pain" and "pain-free" groups. The "knee pain" group had lower heat pain tolerance at the forearm site (p = 0.02) and higher mechanical pain (p < 0.01) at both tested sites in comparison to the "CMC pain" group. Lastly, the "CMC + knee pain" group had the highest self-reported pain (p < 0.01) and disability (p < 0.01) compared to all other groups. Conclusion: Results suggest knee OA compounded with CMC OA increases disease impact and decreases emotional health compared to OA at either the CMC or knee joint alone. Results also support a relationship between the number of painful joints and enhanced widespread pain sensitivity. Measuring pain at sites other than the primary OA location is important and could contribute to more holistic treatment and prevention of OA progression.

The Center-Center Image Closely Approximates Other Methods for Syndesmosis Reduction Clamp Placement.

BACKGROUND: The optimal placement for a syndesmosis reduction clamp remains an open question. This study compared the center-center axis, which localizes clamp placement using only an internally rotated lateral ankle X-ray, with other common approaches, whose accuracy can only be confirmed using computed tomography (CT). METHODS: Bone models of anatomically aligned (n = 6) and malreduced (n = 48) limbs were generated from CT scans of cadaveric specimens. Four axes for guiding clamp placement (center-center, centroid, B2, and trans-syndesmotic) were then analyzed, using digitally reconstructed radiographs derived from the bone models. Each axis' location was defined using angle-height pairs that describe axis orientation along the full anatomical region where syndesmosis fixation occurs. RESULTS: In anatomically aligned limbs, the center-center axis was located on average (±95% CI [confidence interval]), 0.64° (±0.50°) internal rotation, 1.03° (±0.73°) internal rotation, and 2.09° (±7.29°) external rotation from the centroid, B2, and trans-syndesmotic axes, respectively. Fibular displacement altered the magnitude of limb rotation needed to identify the center-center axis. CONCLUSION: The center-center technique is a valid method that closely approximates previously described methods for syndesmosis clamp placement without using CT, and the magnitude of C-arm rotation needed to transition from a talar dome lateral to a center-center view may be a potential method for assessing syndesmosis reduction. LEVELS OF EVIDENCE: Level III: Retrospective comparative study.

Predictions of thumb, hand, and arm muscle parameters derived using force measurements of varying complexity and neural networks.

Subject-specific musculoskeletal models are a promising avenue for personalized healthcare. However, current methods for producing personalized models require dense, biomechanical datasets that include expensive and time-consuming physiological measurements. For personalized models to be clinically useful, we must be able to rapidly generate models from simple, easy to collect data. In this context, the objective of this paper is to evaluate if and how simple data, namely height/weight and pinch force data, can be used to achieve model personalization via machine learning. Using simulated lateral pinch force measurements from a synthetic population of 40,000 randomly generated subjects, we train neural networks to estimate four Hill-type muscle model parameters and bone density. We compare parameter estimates to the true parameters of 10,000 additional synthetic subjects. We also generate new personalized models using the parameter estimates and perform new lateral pinch simulations to compare predicted forces using these personalized models to those generated using a baseline model. We demonstrate that increasing force measurement complexity reduces the root-mean-square error in the majority of parameter estimates. Additionally, musculoskeletal models using neural network-based parameter estimates provide up to an 80% reduction in absolute error in simulated forces when compared to a generic model. Thus, easily obtained force measurements may be suitable for personalizing models of the thumb, although extending the method to more tasks and models involving other joints likely requires additional measurements.

Inverse distance weighting to rapidly generate large simulation datasets.

Obtaining large biomechanical datasets for machine learning is an ongoing challenge. Physics-based simulations offer one approach for generating large datasets, but many simulation methods, such as computed muscle control (CMC), are computationally costly. In contrast, interpolation methods, such as inverse distance weighting (IDW), are computationally fast. We examined whether IDW is a low-cost and accurate approach for interpolating muscle activations from CMC.IDW was evaluated using lateral pinch simulations in OpenSim. Simulated pinch data were organized into grids of varying sparsity (high, medium, and low density), where each grid point represented the muscle activations associated with a unique combination of mass and height of a young adult. For each grid, muscle activations were calculated via CMC and IDW for 108 random mass-height pairs that were not coincident with simulation grid vertices. We evaluated the interpolation errors from IDW for each grid, as well as the sensitivity of lateral pinch force to these errors. The root mean square error (RMSE) associated with interpolated muscle activations decreased with increasing grid density and never exceeded 4%. While CMC received a target thumb-tip force of 40 N, errors from the interpolated muscle activations never impacted the simulated force magnitude by more than 0.1 N. Furthermore, the computation time for CMC simulations averaged 4.22 core-minutes, while IDW averaged 0.95 core-seconds per mass-height pair.These results indicate IDW is a practical approach for rapidly estimating muscle activations from sparse CMC datasets. Future works could adapt our IDW approach to evaluate other tasks, biomechanical features, and/or populations.

Odorant Binding Causes Cytoskeletal Rearrangement, Leading to Detectable Changes in Endothelial and Epithelial Barrier Function and Micromotion.

Non-olfactory cells have excellent biosensor potential because they express functional olfactory receptors (ORs) and are non-neuronal cells that are easy to culture. ORs are G-protein coupled receptors (GPCRs), and there is a well-established link between different classes of G-proteins and cytoskeletal structure changes affecting cellular morphology that has been unexplored for odorant sensing. Thus, the present study was conducted to determine if odorant binding in non-olfactory cells causes cytoskeletal changes that will lead to cell changes detectable by electric cell-substrate impedance sensing (ECIS). To this end, we used the human umbilical vein endothelial cells (HUVECs), which express OR10J5, and the human keratinocyte (HaCaT) cells, which express OR2AT4. Using these two different cell barriers, we showed that odorant addition, lyral and Sandalore, respectively, caused an increase in cAMP, changes in the organization of the cytoskeleton, and a decrease in the integrity of the junctions between the cells, causing a decrease in cellular electrical resistance. In addition, the random cellular movement of the monolayers (micromotion) was significantly decreased after odorant exposure. Collectively, these data demonstrate a new physiological role of olfactory receptor signaling in endothelial and epithelial cell barriers and represent a new label-free method to detect odorant binding.

Biomechanical Sequelae of Syndesmosis Injury and Repair.

This review characterizes fibula mechanics in the context of syndesmosis injury and repair. Through detailed understanding of fibula kinematics (the study of motion) and kinetics (the study of forces that cause motion), the full complexity of fibula motion can be appreciated. Although the magnitudes of fibula rotation and translation are inherently small, even slight alterations of fibula position or movement can substantially impact force propagation through the ankle and hindfoot joints. Accordingly, implications for clinical care are discussed.

Measuring fascicle lengths of extrinsic and intrinsic thumb muscles using extended field-of-view ultrasound.

Complex motion of the human thumb is enabled by the balanced architectural design of the extrinsic and intrinsic thumb muscles. Given that recent imaging advances have not yet been applied to enhance our understanding of the in vivo properties of thumb muscles, the objective of this study was to test the reliability and validity of measuring thumb muscle fascicle lengths using extended field of view ultrasound (EFOV-US). Three muscles (FPL: flexor pollicis longus, APB: abductor pollicis brevis, and ECU: extensor carpi ulnaris) were imaged in eight healthy adults (4 female; age, 21.6 ± 1.3 years; height, 175.9 ± 8.3 cm)[mean ± SD]. Measured fascicle lengths were compared to cadaveric data (all muscles) and ultrasound data (ECU only). Additionally, to evaluate how fascicle lengths scale with anthropometric measurements, height, forearm length, hand length, and hand width were recorded. The EFOV-US method obtained precise fascicle length measurements [mean ± SD] for the FPL (6.2 ± 0.5 cm), APB (5.1 ± 0.3 cm), and ECU (4.0 ± 0.4 cm). However, our EFOV-US measurements were consistently different (p < 0.05) than prior cadaveric data, highlighting the need to better understand differences between in vivo and ex vivo fascicle length measurements. Fascicle length was significantly related to only hand length (r2 = 0.56, p = 0.03) for APB, highlighting that anthropometric scaling may not accurately estimate thumb muscle length. As the first study to apply EFOV-US to measure thumb muscle fascicle lengths, this study expands the utility of this imaging technology within the upper limb.

A Musculoskeletal Model of the Hand and Wrist Capable of Simulating Functional Tasks.

OBJECTIVE: The purpose of this work was to develop an open-source musculoskeletal model of the hand and wrist and to evaluate its performance during simulations of functional tasks. METHODS: The current model was developed by adapting and expanding upon existing models. An optimal control theory framework that combines forward-dynamics simulations with a simulated-annealing optimization was used to simulate maximum grip and pinch force. Active and passive hand opening were simulated to evaluate coordinated kinematic hand movements. RESULTS: The model's maximum grip force production matched experimental measures of grip force, force distribution amongst the digits, and displayed sensitivity to wrist flexion. Simulated lateral pinch strength replicated in vivo palmar pinch strength data. Additionally, predicted activations for 7 of 8 muscles fell within variability of EMG data during palmar pinch. The active and passive hand opening simulations predicted reasonable activations and demonstrated passive motion mimicking tenodesis, respectively. CONCLUSION: This work advances simulation capabilities of hand and wrist models and provides a foundation for future work to build upon. SIGNIFICANCE: This is the first open-source musculoskeletal model of the hand and wrist to be implemented during both functional kinetic and kinematic tasks. We provide a novel simulation framework to predict maximal grip and pinch force which can be used to evaluate how potential surgical and rehabilitation interventions influence these functional outcomes while requiring minimal experimental data.

Intraoperative Assessment of Reduction of the Ankle Syndesmosis.

PURPOSE OF REVIEW: Postoperative malreduction of the ankle syndesmosis is common, poorly defined, and its assessment is controversial. In the absence of a gold standard method to evaluate the ankle syndesmosis, a variety of techniques have been described. As the knowledgebase expands, data illustrating caveats for such techniques has become available. The purpose of this review is to highlight literature-sourced technical pearls and their related caveats for the intraoperative assessment of the ankle syndesmosis. RECENT FINDINGS: Although numerical criteria are commonly used to assess syndesmotic reduction, anatomical variation in the healthy population frequently exceeds proposed cutoffs. Patient-specific uninjured anatomy can be defined by comparing to the uninjured contralateral ankle; however, side-to-side variation is present for many anatomical relationships. Advanced imaging (e.g., lateral radiographs, 3-dimensional radiography) can influence intraoperative surgeon decision-making and improve syndesmosis reduction, but minute improvements in syndesmosis reduction may not outweigh increased operating time and costs. Intraoperative imaging is an adjunct, not a replacement for direct visualization or palpation when reducing the syndesmosis. Arthroscopy may benefit younger patients with high physical demands by improving identification of intra-articular pathology absent on MRI. Although anatomical reduction is important to restore pre-injury biomechanics, it is unclear whether differences in reduction quality influence patient-reported outcomes. In the absence of a gold standard, awareness of the options for intraoperative assessment of the syndesmosis and their respective accuracy and limitations reported herein could enhance surgeons' ability to intraoperatively reduce the syndesmosis with the tools currently available.

Linear relationship between electromyography and shear wave elastography measurements persists in deep muscles of the upper extremity.

Recent works have demonstrated a linear relationship between muscle activation and shear modulus in various superficial muscles. As such, it may be possible to overcome limitations of traditional electromyography (EMG) methods by assessing activation using shear wave elastography. However, the relationship has not been wholly validated in deep muscles. This study measured the association between squared shear wave velocity, which is related to shear modulus, and activation within superficial and deep muscles. This relationship was also compared between surface and intramuscular EMG electrodes. We simultaneously recorded EMG and shear wave velocity in one deep (brachialis) and one superficial (brachioradialis) muscle in ten healthy individuals during isometric elbow flexion across a wide range of contraction intensities. Muscle activation and squared shear wave velocity demonstrated good reliability (ICC > 0.75) and showed a linear relationship (P < 0.05) for all muscle/EMG electrode type combinations (study conditions) after down-sampling. Study condition was not a significant within-subject factor to the slope or intercept of the relationship (P > 0.05). This work demonstrates that activation of both superficial and deep muscles can be assessed noninvasively using ultrasound shear wave elastography and is a critical step toward demonstrating elastography's utility as an alternative to EMG.

Syndesmosis Injury Contributes a Large Negative Effect on Clinical Outcomes: A Systematic Review.

INTRODUCTION: The literature largely addresses questions of diagnostic accuracy and therapeutic accuracy. However, the magnitude of the clinical impact of syndesmosis injury is commonly described in intuitive yet qualitative terms. This systematic review aimed to quantify the impact of syndesmosis injury. METHODS: Published clinical outcomes data were used to compute an effect size reflecting the impact of syndesmosis injury. This was done within the clinical contexts of isolated syndesmosis injury and syndesmosis injury with concomitant ankle fracture. Clinical outcomes data included Olerud-Molander (OM) and American Orthopaedic Foot and Ankle Society (AOFAS) scores, visual analog scale for pain, and days missed from sport competition. Parametric data were compared with Student t tests. Effect size was computed using Cohen's d. RESULTS: In ankle fracture patients, syndesmosis injury demonstrated a large effect size for OM (d = 0.96) and AOFAS (d = 0.83) scores. In athletic populations without concomitant ankle fracture, syndesmosis injury demonstrated a large effect size on days missed from competition (d = 2.32). DISCUSSION: These findings confirm the magnitude of the negative impact of syndesmosis injury in athletic populations with isolated injury and in ankle fracture patients. In ankle fracture patients, this large negative effect remains despite surgery. Thus, syndesmosis repair may not fully mitigate the impact of the injury. LEVELS OF EVIDENCE: Level III: Systematic review.

Classifying muscle parameters with artificial neural networks and simulated lateral pinch data.

OBJECTIVE: Hill-type muscle models are widely employed in simulations of human movement. Yet, the parameters underlying these models are difficult or impossible to measure in vivo. Prior studies demonstrate that Hill-type muscle parameters are encoded within dynamometric data. But, a generalizable approach for estimating these parameters from dynamometric data has not been realized. We aimed to leverage musculoskeletal models and artificial neural networks to classify one Hill-type muscle parameter (maximum isometric force) from easily measurable dynamometric data (simulated lateral pinch force). We tested two neural networks (feedforward and long short-term memory) to identify if accounting for dynamic behavior improved accuracy. METHODS: We generated four datasets via forward dynamics, each with increasing complexity from adjustments to more muscles. Simulations were grouped and evaluated to show how varying the maximum isometric force of thumb muscles affects lateral pinch force. Both neural networks classified these groups from lateral pinch force alone. RESULTS: Both neural networks achieved accuracies above 80% for datasets which varied only the flexor pollicis longus and/or the abductor pollicis longus. The inclusion of muscles with redundant functions dropped model accuracies to below 30%. While both neural networks were consistently more accurate than random guess, the long short-term memory model was not consistently more accurate than the feedforward model. CONCLUSION: Our investigations demonstrate that artificial neural networks provide an inexpensive, data-driven approach for approximating Hill-type muscle-tendon parameters from easily measurable data. However, muscles of redundant function or of little impact to force production make parameter classification more challenging.

Anthropometric scaling of musculoskeletal models of the hand captures age-dependent differences in lateral pinch force.

Musculoskeletal models and computer simulations enable non-invasive study of muscle function and contact forces. Hand models are useful for understanding the complexities of hand strength, precision movement, and the dexterity required during daily activities. Yet, generic models fail to accurately represent the entire scope of the population, while subject-specific models are labor-intensive to create. The objective of this study was to assess the efficacy of scaled generic models to represent the broad spectrum of strength profiles across the lifespan. We examined one hundred lateral pinch simulations using a generic model of the wrist and thumb anthropometrically scaled to represent the full range of heights reported for four ages across childhood, puberty, older adolescence, and adulthood. We evaluated maximum lateral pinch force produced, muscle control strategies, and the effect of linearly scaling the maximum isometric force. Our simulations demonstrated three main concepts. First, anthropometric scaling could capture age-dependent differences in pinch strength. Second, a generic muscle control strategy is not representative of all populations. Lastly, simulations do not employ optimal fiber length to complete a lateral pinch task. These results demonstrate the potential of anthropometrically-scaled models to study hand strength across the lifespan, while also highlighting that muscle control strategies may adapt as we age. The results also provide insight to the force-length relationship of thumb muscles during lateral pinch. We conclude that anthropometric scaling can accurately represent age characteristics of the population, but subject-specific models are still necessary to represent individuals.