Dorsal Subluxation of the First Metacarpal During Thumb Flexion is an Indicator of Carpometacarpal Osteoarthritis Progression.

BACKGROUND: Measurable changes in patients with progression of thumb carpometacarpal (CMC) osteoarthritis (OA) include joint space narrowing, osteophyte formation, subluxation, and adjacent-tissue changes. Subluxation, an indication of mechanical instability, is postulated as an early biomechanical indicator of progressing CMC OA. Various radiographic views and hand postures have been proposed to best assess CMC subluxation, but 3D measurements derived from CT images serve as the optimal metric. However, we do not know which thumb pose yields subluxation that most indicates OA progression. QUESTIONS/PURPOSES: Using osteophyte volume as a quantitative measure of OA progression, we asked: (1) Does dorsal subluxation vary by thumb pose, time, and disease severity in patients with thumb CMC OA? (2) In which thumb pose(s) does dorsal subluxation most differentiate patients with stable CMC OA from those with progressing CMC OA? (3) In those poses, what values of dorsal subluxation indicate a high likelihood of CMC OA progression? METHODS: Between 2011 and 2014, 743 patients were seen at our institutions for trapeziometacarpal pain. We considered individuals who were between the ages of 45 and 75 years, had tenderness to palpation or a positive grind test result, and had modified Eaton Stage 0 or 1 radiographic thumb CMC OA as potentially eligible for enrollment. Based on these criteria, 109 patients were eligible. Of the eligible patients, 19 were excluded because of a lack of interest in study participation, and another four were lost before the minimum study follow-up or had incomplete datasets, leaving 86 (43 female patients with a mean age of 53 ± 6 years and 43 male patients with a mean age of 60 ± 7 years) patients for analysis. Twenty-five asymptomatic participants (controls) aged 45 to 75 years were also prospectively recruited to participate in this study. Inclusion criteria for controls included an absence of thumb pain and no evidence of CMC OA during clinical examination. Of the 25 recruited controls, three were lost to follow-up, leaving 22 for analysis (13 female patients with a mean age of 55 ± 7 years and nine male patients with a mean age of 58 ± 9 years). Over the 6-year study period, CT images were acquired of patients and controls in 11 thumb poses: neutral, adduction, abduction, flexion, extension, grasp, jar, pinch, grasp loaded, jar loaded, and pinch loaded. CT images were acquired at enrollment (Year 0) and Years 1.5, 3, 4.5, and 6 for patients and at Years 0 and 6 for controls. From the CT images, bone models of the first metacarpal (MC1) and trapezium were segmented, and coordinate systems were calculated from their CMC articular surfaces. The volar-dorsal location of the MC1 relative to the trapezium was computed and normalized for bone size. Patients were categorized into stable OA and progressing OA subgroups based on trapezial osteophyte volume. MC1 volar-dorsal location was analyzed by thumb pose, time, and disease severity using linear mixed-effects models. Data are reported as the mean and 95% confidence interval. Differences in volar-dorsal location at enrollment and rate of migration during the study were analyzed for each thumb pose by group (control, stable OA, and progressing OA). A receiver operating characteristic curve analysis of MC1 location was used to identify thumb poses that differentiated patients whose OA was stable from those whose OA was progressing. The Youden J statistic was used to determine optimized cutoff values of subluxation from those poses to be tested as indicators of OA progression. Sensitivity, specificity, negative predictive values, and positive predictive values were calculated to assess the performance of pose-specific cutoff values of MC1 locations as indicators of progressing OA. RESULTS: In flexion, the MC1 locations were volar to the joint center in patients with stable OA (mean -6.2% [95% CI -8.8% to -3.6%]) and controls (mean -6.1% [95% CI -8.9% to -3.2%]), while patients with progressing OA exhibited dorsal subluxation (mean 5.0% [95% CI 1.3% to 8.6%]; p < 0.001). The pose associated with the most rapid MC1 dorsal subluxation in the progressing OA group was thumb flexion (mean 3.2% [95% CI 2.5% to 3.9%] increase per year). In contrast, the MC1 migrated dorsally much slower in the stable OA group (p < 0.001), at only a mean of 0.1% (95% CI -0.4% to 0.6%) per year. A cutoff value of 1.5% for the volar MC1 position during flexion at enrollment (C-statistic: 0.70) was a moderate indicator of OA progression, with a high positive predictive value (0.80) but low negative predictive value (0.54). Positive and negative predictive values of subluxation rate in flexion (2.1% per year) were high (0.81 and 0.81, respectively). The metric that most indicated a high likelihood of OA progression (sensitivity 0.96, negative predictive value 0.89) was a dual cutoff that combined the subluxation rate in flexion (2.1% per year) with that of loaded pinch (1.2% per year). CONCLUSION: In the thumb flexion pose, only the progressing OA group exhibited MC1 dorsal subluxation. The MC1 location cutoff value for progression in flexion was 1.5% volar to the trapezium , which suggests that dorsal subluxation of any amount in this pose indicates a high likelihood of thumb CMC OA progression. However, volar MC1 location in flexion alone was not sufficient to rule out progression. The availability of longitudinal data improved our ability to identify patients whose disease will likely remain stable. In patients whose MC1 location during flexion changed < 2.1% per year and whose MC1 location during pinch loading changed < 1.2% per year, the confidence that their disease would remain stable throughout the 6-year study period was very high. These cutoff rates were a lower limit, and any patients whose dorsal subluxation advanced faster than 2% to 1% per year in their respective hand poses, were highly likely to experience progressive disease. CLINICAL RELEVANCE: Our findings suggest that in patients with early signs of CMC OA, nonoperative interventions aimed to reduce further dorsal subluxation or operative treatments that spare the trapezium and limit subluxation may be effective. It remains to be determined whether our subluxation metrics can be rigorously computed from more widely available technologies, such as plain radiography or ultrasound.

Kinematic Accuracy in Tracking Total Wrist Arthroplasty With Biplane Videoradiography Using a Computed Tomography-Generated Model.

Total wrist arthroplasty (TWA) for improving the functionality of severe wrist joint pathology has not had the same success, in parameters such as motion restoration and implant survival, as hip, knee, and shoulder arthroplasty. These other arthroplasties have been studied extensively, including the use of biplane videoradiography (BVR) that has allowed investigators to study the in vivo motion of the total joint replacement during dynamic activities. The wrist has not been a previous focus, and utilization of BVR for wrist arthroplasty presents unique challenges due to the design characteristics of TWAs. Accordingly, the aims of this study were (1) to develop a methodology for generating TWA component models for use in BVR and (2) to evaluate the accuracy of model-image registration in a single cadaveric model. A model of the carpal component was constructed from a computed tomography (CT) scan, and a model of the radial component was generated from a surface scanner. BVR was acquired for three anatomical tasks from a cadaver specimen. Optical motion capture (OMC) was used as the gold standard. BVR's bias in flexion/extension, radial/ulnar deviation, and pronosupination was less than 0.3 deg, 0.5 deg, and 0.6 deg. Translation bias was less than 0.2 mm with a standard deviation of less than 0.4 mm. This BVR technique achieved a kinematic accuracy comparable to the previous studies on other total joint replacements. BVR's application to the study of TWA function in patients could advance the understanding of TWA, and thus, the implant's success.

Operator Bias Errors Are Reduced Using Standing Marker Alignment Device for Repeated Visit Studies.

When optical motion capture is used for motion analysis, reflective markers or a digitizer are typically used to record the location of anatomical landmarks identified through palpation. The landmarks are then used to construct anatomical coordinate systems. Failure to consistently identify landmarks through palpation over repeat tests creates artifacts in the kinematic waveforms. The purpose of this work was to improve intra- and inter-rater reliability in determining lower limb anatomical landmarks and the associated anatomical coordinate systems using a marker alignment device (MAD). The device aids the subject in recreating the same standing posture over multiple tests, and recreates the anatomical landmarks from previous static calibration trials. We tested three different raters who identified landmarks on eleven subjects. The subjects performed walking trials and their gait kinematics were analyzed with and without the device. Ankle kinematics were not improved by the device suggesting manual palpation over repeat visits is just as effective as the MAD. Intra-class correlation coefficients between gait kinematics registered to the reference static trial and registered to follow-up static trials with and without the device were improved between 1% and 33% when the device was used. Importantly, out-of-plane hip and knee kinematics showed the greatest improvements in repeatability. These results suggest that the device is well suited to reducing palpation artifact during repeat visits to the gait lab.

The passive biomechanics of the thumb carpometacarpal joint: An in vitro study.

The thumb carpometacarpal (CMC) joint facilitates multidirectional motion of the thumb and affords prehensile power and precision. Traditional methods of quantifying thumb CMC kinematics have been largely limited to range-of-motion (ROM) measurements in 4 orthogonal primary directions (flexion, extension, abduction, adduction) due to difficulties in capturing multidirectional thumb motion. However, important functional motions (e.g., opposition) consist of combinations of these primary directions, as well as coupled rotations (internal and external rotation) and translations. Our goal was to present a method of quantifying the multidirectional in vitro biomechanics of the thumb CMC joint in 6 degrees-of-freedom. A robotic musculoskeletal simulation system was used to manipulate CMC joints of 10 healthy specimens according to specimen-specific joint coordinate systems calculated from computed tomography bone models. To determine ROM and stiffness (K), the first metacarpal (MC1) was rotated with respect to the trapezium (TPM) to a terminal torque of 1 Nm in the four primary directions and in 20 combinations of these primary directions. ROM and K were also determined in internal and external rotation. We found multidirectional ROM was greatest and K least in directions oblique to the primary directions. We also found external rotation coupling with adduction-flexion and abduction-extension and internal rotation coupling with abduction-flexion and adduction-extension. Additionally, the translation of the proximal MC1 was predominantly radial during adduction and predominantly ulnar during abduction. The findings of this study aid in understanding thumb CMC joint mechanics and contextualize pathological changes for future treatment improvement.

Development of an implantable trapezium carpal bone replacement for measuring in vivo loads at the base of the thumb.

Understanding the loads that occur across musculoskeletal joints is critical to advancing our understanding of joint function and pathology, implant design and testing, as well as model verification. Substantial work in these areas has occurred in the hip and knee but has not yet been undertaken in smaller joints, such as those in the wrist. The thumb carpometacarpal (CMC) joint is a uniquely human articulation that is also a common site of osteoarthritis with unknown etiology. We present two potential designs for an instrumented trapezium implant and compare approaches to load calibration. Two instrumented trapezia designs were prototyped using strain gauge technology: Tube and Diaphragm. The Tube design is a well-established structure for sensing loads while the Diaphragm is novel. Each design was affixed to a 6-DOF load cell that was used as the reference. Loads were applied manually, and two calibration methods, supervised neural network (DEEP) and matrix algebra (MAT), were implemented. Bland-Altman 95% confidence interval for the limits of agreement (95% CI LOA) was used to assess accuracy. Overall, the DEEP calibration decreased 95% CI LOA compared with the MAT approach for both designs. The Diaphragm design outperformed the Tube design in measuring the primary load vector (joint compression). Importantly, the Diaphragm design permits the hermetic encapsulation of all electronics, which is not possible with the Tube design, given the small size of the trapezium. Substantial work remains before this device can be approved for implantation, but this work lays the foundation for further device development that will be required.

The multidirectional roles of the anterior oblique ligament and dorsoradial ligament of the thumb carpometacarpal joint.

The multidirectional biomechanics of the thumb carpometacarpal (CMC) joint underlie the remarkable power and precision of the thumb. Because of the unconfined nature of thumb CMC articulation, these biomechanics are largely dictated by ligaments, notably the anterior oblique ligament (AOL) and the dorsoradial ligament (DRL). However, the rotational and translational stabilizing roles of these ligaments remain unclear, as evidenced by the variety of interventions employed to treat altered pathological CMC biomechanics. The purpose of this study was to determine the effects of sectioning the AOL (n = 8) or DRL (n = 8) on thumb CMC joint biomechanics (rotational range-of-motion [ROM] and stiffness, translational ROM) in 26 rotational directions, including internal and external rotation, and in eight translational directions. Using a robotic musculoskeletal simulation system, the first metacarpal of each specimen (n = 16) was rotated and translated with respect to the trapezium to determine biomechanics before and after ligament sectioning. We observed the greatest increase in rotational ROM and decrease in rotational stiffness in flexion directions and internal rotation following DRL transection and in extension directions following AOL transection. The greatest increase in translational ROM was in dorsal and radial directions following DRL transection and in volar directions following AOL transection. These data suggest the AOL and DRL play complementary stabilizing roles, primarily restraining translations in the direction of and rotations away from the ligament insertion sites. These findings may inform future interventions or implant designs for pathological CMC joints.

Bone morphological changes of the trapezium and first metacarpal with early thumb osteoarthritis progression.

BACKGROUND: Thumb carpometacarpal osteoarthritis is characterized by osteophyte growth and changes in the curvature of the articular surfaces of the trapezium and first metacarpal. The aim of this longitudinal study was to quantify in-vivo bone morphology changes with osteoarthritis progression. METHODS: The study analyzed an observational dataset of 86 subjects with early thumb osteoarthritis and 22 age-matched asymptomatic controls. CT scans of subjects' affected hands were acquired at enrollment (year 0), and at 1.5, 3, 4.5, and 6-year follow-up visits. Osteoarthritic subjects were classified into stable and progressive groups, as defined by osteophyte volume and the rate of osteophyte growth. Trapezium height, width, and volar facet recession, along with first metacarpal volar beak recession and recession angle, were quantified. FINDINGS: Mean trapezium width increased 12% over six years in the progressive osteoarthritis group. Trapezium volar recession of the progressive osteoarthritis group was significantly greater than stable at enrollment (P < 0.0001) and year 6 (P < 0.0001). The first metacarpal volar beak of the progressive osteoarthritis group recessed significantly faster than stable (P = 0.0004) and control (P = 0.0003). In year 6, volar beak surfaces in subjects with progressive osteoarthritis were flatter with reduced curvature, measuring -8.7 ± 4.0 degrees, compared to the stable osteoarthritis (P < 0.0001) and control groups (P = 0.0003), which maintained nominal curvatures, measuring 0.7 ± 2.5 and 0.2 ± 3.2 degrees, respectively. INTERPRETATION: Our results demonstrate significant recession and reduction in the angle of the first metacarpal volar beak in progressive osteoarthritis. Flattening of the first metacarpal volar beak may have important associations with carpometacarpal joint contact and loading migrations, further propagating osteophyte formation and bony remodeling. This work highlights the volar beak of the first metacarpal as a region of morphology change with disease.

Biplanar Videoradiography to Study the Wrist and Distal Radioulnar Joints.

Accurate measurement of skeletal kinematics in vivo is essential for understanding normal joint function, the influence of pathology, disease progression, and the effects of treatments. Measurement systems that use skin surface markers to infer skeletal motion have provided important insight into normal and pathological kinematics, however, accurate arthrokinematics cannot be attained using these systems, especially during dynamic activities. In the past two decades, biplanar videoradiography (BVR) systems have enabled many researchers to directly study the skeletal kinematics of the joints during activities of daily living. To implement BVR systems for the distal upper extremity, videoradiographs of the distal radius and the hand are acquired from two calibrated X-ray sources while a subject performs a designated task. Three-dimensional (3D) rigid-body positions are computed from the videoradiographs via a best-fit registrations of 3D model projections onto to each BVR view. The 3D models are density-based image volumes of the specific bone derived from independently acquired computed-tomography data. Utilizing graphics processor units and high-performance computing systems, this model-based tracking approach is shown to be fast and accurate in evaluating the wrist and distal radioulnar joint biomechanics. In this study, we first summarized the previous studies that have established the submillimeter and subdegree agreement of BVR with an in vitro optical motion capture system in evaluating the wrist and distal radioulnar joint kinematics. Furthermore, we used BVR to compute the center of rotation behavior of the wrist joint, to evaluate the articulation pattern of the components of the implant upon one another, and to assess the dynamic change of ulnar variance during pronosupination of the forearm. In the future, carpal bones may be captured in greater detail with the addition of flat panel X-ray detectors, more X-ray sources (i.e., multiplanar videoradiography), or advanced computer vision algorithms.

Optical motion capture accuracy is task-dependent in assessing wrist motion.

Optical motion capture (OMC) systems are commonly used to capture in-vivo three-dimensional joint kinematics. However, the skin-based markers may not reflect the underlying bone movement, a source of error known as soft tissue artifact (STA). This study examined STA during wrist motion by evaluating the agreement between OMC and biplanar videoradiography (BVR). Nine subjects completed 7 different wrist motion tasks: doorknob rotation to capture supination and pronation, radial-ulnar deviation, flexion-extension, circumduction, hammering, and pitcher pouring. BVR and OMC captured the motion simultaneously. Wrist kinematics were quantified using helical motion parameters of rotation and translation, and Bland-Altman analysis quantified the mean difference (bias) and 95% limit of agreement (LOA). The rotational bias of doorknob pronation, a median bias of -4.9°, was significantly larger than the flexion-extension (0.7°, p < 0.05) and radial-ulnar deviation (1.8°, p < 0.01) tasks. The rotational LOA range was significantly smaller in the flexion-extension task (5.9°) compared to pitcher (11.6°, p < 0.05) and doorknob pronation (17.9°, p < 0.05) tasks. The translation bias did not differ between tasks. The translation LOA range was significantly larger in circumduction (9.8°) compared to the radial-ulnar deviation (6.3°, p < 0.05) and pitcher (3.4°, p < 0.05) tasks. While OMC technology has a wide-range of successful applications, we demonstrated it has relatively poor agreement with BVR in tracking wrist motion, and that the agreement depends on the nature and direction of wrist motion.

Biomechanics of the Distal Radioulnar Joint During In Vivo Forearm Pronosupination.

Background Ulnar variance (UV) and center of rotation (COR) location at the level of the distal radioulnar joint (DRUJ) change with forearm rotation. Nevertheless, these parameters have not been assessed dynamically during active in vivo pronosupination. This assessment could help us to improve our diagnosis and treatment strategies. Questions/purposes We sought to (1) mathematically model the UV change, and (2) determine the dynamic COR's location during active pronosupination. Methods We used biplanar videoradiography to study DRUJ during in vivo pronation and supination in nine healthy subjects. UV was defined as the proximal-distal distance of ulnar fovea with respect to the radial sigmoid notch, and COR was calculated using helical axis of motion parameters. The continuous change of UV was evaluated using a generalized linear regression model. Results A second-degree polynomial with R 2 of 0.85 was able to model the UV changes. Maximum negative UV occurred at 38.0 degrees supination and maximum positive UV occurred at maximum pronation. At maximum pronation, the COR was located 0.5 ± 1.8 mm ulnarly and 0.6 ± 0.8 mm volarly from the center of the ulnar fovea, while at maximum supination, the COR was located 0.2 ± 0.6 mm radially and 2.0 ± 0.5 mm volarly. Conclusion Changes in UV and volar translation of the COR are nonlinear at the DRUJ during pronosupination. Clinical Relevance Understanding the dynamic nature of UV as a function of pronosupination can help guide accurate evaluation and treatment of wrist pathology where the UV is an important consideration. The dynamic behavior of COR might be useful in designing DRUJ replacement implants to match the anatomical motion.

Total Wrist Arthroplasty Alignment and Its Potential Association with Clinical Outcomes.

Purpose There is a lack of quantitative research that describes the alignment and, more importantly, the effects of malalignment on total wrist arthroplasty (TWA). The main goal of this pilot study was to assess the alignment of TWA components in radiographic images and compare them with measures computed by three-dimensional analysis. Using these measures, we then determined if malalignment is associated with range of motion (ROM) or clinical outcomes (PRWHE, PROMIS, QuickDash, and grip strength). Methods Six osteoarthritic patients with a single type of TWA were recruited. Radiographic images, computed tomography images, and clinical outcomes of the wrists were recorded. Using posteroanterior and lateral radiographs, alignment measurements were defined for the radial and carpal components. Radiographic measurements were validated with models reconstructed from computed tomography images using Bland-Altman analysis. Biplanar videoradiography (<1mm and <1 degree accuracy) was used to capture and compute ROM of the TWA components. Linear regression assessed the associations between alignment and outcomes. Results Radiographic measures had a 95% limit-of-agreement (mean difference ± 1.96 × SD) of 3 degrees and 3mm with three-dimensional values, except for the measures of the carpal component in the lateral view. In our small cohort, wrist flexion-extension and radial-ulnar deviation were correlated with volar-dorsal tilt and volar-dorsal offset of the radial component and demonstrated a ROM increase of 3.7 and 1.6 degrees per degree increase in volar tilt, and 10.8 and 4.2 degrees per every millimeter increase in volar offset. The carpal component's higher volar tilt was also associated with improvements in patient-reported pain. Conclusions We determined metrics describing the alignment of TWA, and found the volar tilt and volar offset of the radial component could potentially influence the replaced wrist's ROM. Clinical Relevance TWA component alignment can be measured reliably in radiographs, and may be associated with clinical outcomes. Future studies must evaluate its role in a larger cohort.

In vivo articular contact pattern of a total wrist arthroplasty design.

Total wrist arthroplasty (TWA) designs suffer from relatively high complication rates when compared to other arthroplasties. Understanding the contact pattern of hip and knee replacement has improved their design and function; however, the in vivo contact pattern of TWA has not yet been examined and is thus the aim of this study. We hypothesized that the center of contact (CoC) is located at the geometric centers of the carpal component and radial component in the neutral posture and that the CoC moves along the principal arcs of curvature throughout primary anatomical motions. Wrist motion and implant kinematics of six patients with the Freedom® total wrist implant were studied during various tasks using biplanar videoradiography. The location of the CoC of the components was investigated by calculating distance fields between the articular surfaces. We found the CoC at the neutral posture was not at the geometric centers but was located 3.5 mm radially on the carpal component and 1.2 mm ulnarly on the radial component. From extension to flexion, the CoC moved 10.8 mm from dorsal to volar side on the carpal component (p < 0.0001) and 7.2 mm from volar to dorsal on the radial component (p = 0.0009). From radial to ulnar deviation, the CoC moved 12.4 mm from radial to ulnar on the carpal component (p < 0.0001), and 5.6 mm from ulnar to radial on the radial component (p = 0.009). The findings of this study may eventually improve TWA success by advancing future designs through a more accurate understating of their kinematic performance in vivo.

Accuracy of an electrogoniometer relative to optical motion tracking for quantifying wrist range of motion.

Methods for capturing wrist range of motion (RoM) vary in complexity, cost, and sensitivity. Measures by manual goniometer, though an inexpensive modality, provide neither dynamic nor objective motion data. Conversely, optical motion capture systems are widely used in three-dimensional scientific motion capture studies but are complex and expensive. The electrogoniometer bridges the gap between portability and objective measurement. Our study aims to evaluate the accuracy of a 2 degree of freedom electrogoniometer using optical motion capture as the reference for in vivo wrist motion. First, a mechanical system constructed from two plastic pipes and a universal joint mimicked a human wrist to assess the inherent accuracy of the electrogoniometer. Simulations of radial/ulnar deviation (R/U), flexion/extension (F/E) and circumduction were evaluated. Second, six subjects performed three RoM tasks of R/U deviation, F/E, and circumduction for evaluation of the in vivo accuracy. Bland-Altman analysis quantified the accuracy. The mechanical experiment reported greater accuracy than the in vivo study with mean difference values less than ±1°. The in vivo accuracy varied across RoM tasks, with mean differences greatest in the F/E task (7.2°). Smaller mean differences values were reported in the R/U deviation task (-0.8°) and the circumduction task (1.2°).

Osteophyte volume calculation using dissimilarity-excluding Procrustes registration of archived bone models from healthy volunteers.

Osteophytes are associated with later stage osteoarthritis and are most commonly described using semiquantitative radiographic grading systems. A detailed understanding of osteophyte formation is, in part, limited by the ability to quantify bone pathology. Osteophytes can be quantified relative to pre-osteoarthritic bone, or to the contralateral bone if it is healthy; however, in many cases, neither are available as references. We present a method for computing three-dimensional (3D) osteophyte models using a library of healthy control bones. An existing data set containing the computed tomography scans of 90 patients with first carpometacarpal osteoarthritis (OA) and 46 healthy subjects were utilized. A healthy bone that best fit each OA subject's bone was determined using a dissimilarity-excluding Procrustes registration technique (DEP) that minimized the influence of dissimilar features (ie, osteophytes). The osteophyte model was then computed through Boolean subtraction of the reference bone model from the OA bone model. DEP reference bones conformed significantly better to the OA bones (P < .0001) than by finite difference iterative closest point registration (root mean squared distances, 0.33 ± 0.05 and 0.41 ± 0.16 mm, respectively). The effect of library size on dissimilarity measure was investigated by leave-k-out cross-validation randomly reducing k from 46 to 1. A library of n ≥ 31 resulted in less than 10% difference from the theoretical minimum value. The proposed method enables quantification of osteophytes when the disease-free bone or the healthy contralateral bone is not available for any 3D data set. Quantifying osteophyte formation and growth may aid in understating the associated mechanisms in OA.

Proximal-distal shift of the center of rotation in a total wrist arthroplasty is more than twice of the healthy wrist.

Reproduction of healthy wrist biomechanics should minimize the abnormal joint forces that could potentially result in the failure of a total wrist arthroplasty (TWA). To date, the in vivo kinematics of TWA have not been measured and it is unknown if TWA preserves healthy wrist kinematics. Therefore, the purpose of this in vivo study was to determine the center of rotation (COR) for a current TWA design and to compare its location to the healthy wrist. The wrist COR for six patients with TWA and 10 healthy subjects were calculated using biplane videoradiography as the subjects performed various range-of-motion and functional tasks that included coupled wrist motions. An open-source registration software, Autoscoper, was used for model-based tracking and kinematics analysis. It was demonstrated that the COR was located near the centers of curvatures of the carpal component for the anatomical motions of flexion-extension and radial-ulnar deviation. When compared to healthy wrists, the COR of TWAs was located more distal in both pure radial deviation (P < .0001) and pure ulnar deviation (P = .07), while there was no difference in its location in pure flexion or extension (P = .99). Across all coupled motions, the TWA's COR shifted more than two times that of the healthy wrists in the proximal-distal direction (17.1 vs 7.2 mm). We postulate that the mismatch in the COR location and behavior may be associated with increased loading of the TWA components, leading to an increase in the risk of component and/or interface failure.

Accuracy of biplane videoradiography for quantifying dynamic wrist kinematics.

Accurately assessing the dynamic kinematics of the skeletal wrist could advance our understanding of the normal and pathological wrist. Biplane videoradiography (BVR) has allowed investigators to study dynamic activities in the knee, hip, and shoulder joint; however, currently, BVR has not been utilized for the wrist joint because of the challenges associated with imaging multiple overlapping bones. Therefore, our aim was to develop a BVR procedure and to quantify its accuracy for evaluation of wrist kinematics. BVR was performed on six cadaveric forearms for one neutral static and six dynamic tasks, including flexion-extension, radial-ulnar deviation, circumduction, pronation, supination, and hammering. Optical motion capture (OMC) served as the gold standard for assessing accuracy. We propose a feedforward tracking methodology, which uses a combined model of metacarpals (second and third) for initialization of the third metacarpal (MC3). BVR-calculated kinematic parameters were found to be consistent with the OMC-calculated parameters, and the BVR/OMC agreement had submillimeter and sub-degree biases in tracking individual bones as well as the overall joint's rotation and translation. All dynamic tasks (except pronation task) showed a limit of agreement within 1.5° for overall rotation, and within 1.3 mm for overall translations. Pronation task had a 2.1° and 1.4 mm limit of agreement for rotation and translation measurement. The poorest precision was achieved in calculating the pronation-supination angle, and radial-ulnar and volar-dorsal translational components, although they were sub-degree and submillimeter. The methodology described herein may assist those interested in examining the complexities of skeletal wrist function during dynamic tasks.

Mild leg length discrepancy affects lower limbs, pelvis and trunk biomechanics of individuals with knee osteoarthritis during gait.

BACKGROUND: Leg length discrepancy greater than 1cm increases odds of progressive knee osteoarthritis in the shorter limb. METHODS: Biomechanical data of 15 knee osteoarthritis participants were collected while they walked under two conditions: (1) control - wearing thick sandals; (2) short limb - wearing a thin sandal on the osteoarthritic limb and a thick sandal on the contralateral limb. The thick and thin sandals had 1.45cm of thickness difference. The knee osteoarthritis limb was analyzed for both conditions. Ankle, knee, hip, pelvis and trunk kinematics and moments were measured with a motion and force capture system. Principal component analysis and mean hypothesis' tests were used to compare the conditions. FINDINGS: The short limb condition reduced rearfoot plantarflexion in loading response and increased plantarflexion in late stance (p<0.001), increased ankle dorsiflexion moment (p=0.003), increased knee flexion angle in loading response and delayed knee flexion in late stance (p=0.001), increased knee extension moment in loading response and increased knee flexion moment in terminal stance (p=0.023), reduced hip extension moment in early stance and reduced hip flexion moment in late stance (p<0.001), reduced knee adduction moment (p=0.015), reduced hip adduction angle (p=0.001) and moment (p=0.012) and increased pelvic (p=0.023) and trunk (p=0.001) external rotation. INTERPRETATION: Mild leg length discrepancy affects the entire kinetic chain of individuals with knee osteoarthritis during gait, increasing knee sagittal plane loading, which helps to explain why mild leg length discrepancy accelerates knee osteoarthritis progression. Mild leg length discrepancy should not be overlooked in knee osteoarthritis individuals.

Why don't most runners get knee osteoarthritis? A case for per-unit-distance loads.

UNLABELLED: Peak knee joint contact forces ("loads") in running are much higher than they are in walking, where the peak load has been associated with the initiation and progression of knee osteoarthritis. However, runners do not have an especially high risk of osteoarthritis compared with nonrunners. This paradox suggests that running somehow blunts the effect of very high peak joint contact forces, perhaps to provide a load per unit distance (PUD) traveled that is relatively low. PURPOSE: This study aimed to compare peak and PUD knee joint loads between human walking and running. METHODS: Fourteen healthy adults walked and ran at self-selected speeds. Ground reaction force and motion capture data were measured and combined with inverse dynamics and musculoskeletal modeling to estimate the peak knee joint loads, PUD knee joint loads, and the impulse of the knee joint contact force for each gait with a matched-pair (within-subject) design. RESULTS: The peak load was three times higher in running (8.02 vs 2.72 body weight, P < 0.001), but the PUD load did not differ between running and walking (0.80 vs 0.75 body weight per meter, P = 0.098). The impulse of the joint contact force was greater for running than for walking (1.30 vs 1.04 body weight per second, P < 0.001). The peak load increased with increasing running speed, whereas the PUD load decreased with increasing speed. CONCLUSIONS: Compared with walking, the relatively short duration of ground contact and relatively long length of strides in running seem to blunt the effect of high peak joint loads, such that the PUD loads are no higher than that in walking. Waveform features other than or in addition to the peak value should be considered when studying joint loading and injuries.