Background-Most individuals with spinal cord injury who use manual wheelchairs experience shoulder pain related to wheelchair use, potentially in part from mechanical impingement of soft tissue structures within the subacromial space. There is evidence suggesting that scapula and humerus motion during certain wheelchair tasks occurs in directions that may reduce the subacromial space, but it hasn't been thoroughly characterized in this context. Methods-Shoulder motion was imaged and quantified during scapular plane elevation with/ without handheld load, propulsion with/without added resistance, sideways lean, and weight-relief raise in ten manual wheelchair users with spinal cord injury using biplane fluoroscopy and computed tomography. For each position, minimum distance between rotator cuff tendon insertions (infraspinatus, subscapularis, supraspinatus) and the coracoacromial arch was determined. Tendon thickness was measured with ultrasound, and impingement risk scores were defined for each task based on frequency and amount of tendon compression.Findings-Periods of impingement were identified during scapular plane elevation and propulsion but not during pressure reliefs in most participants. There was a significant effect of activity on impingement risk scores (P< 0.0001), with greatest impingement risk during scapular plane elevation followed by propulsion. Impingement risk scores were not significantly different between scapular plane elevation loading conditions (P= 0.202) or propulsion resistances (P= 0.223). The infraspinatus and supraspinatus tendons were both susceptible to impingement during *

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Biplane 2D-3D registration approaches have been used for measuring 3D, in vivo glenohumeral (GH) joint kinematics. Computed tomography (CT) has become the gold standard for reconstructing 3D bone models, as it provides high geometric accuracy and similar tissue contrast to fluoroscopy. Alternatively, magnetic resonance imaging (MRI) would not expose subjects to radiation and provides the ability to add cartilage and other soft tissues to the models. However, the accuracy of MRI-based 2D-3D registration for quantifying glenohumeral kinematics is unknown. We developed an automatic 2D-3D registration program that works with both CT- and MRI-based image volumes for quantifying joint motions. The purpose of this study was to use the proposed 2D-3D auto-registration algorithm to describe the humerus and scapula tracking accuracy of CT- and MRI-based registration relative to radiostereometric analysis (RSA) during dynamic biplanar fluoroscopy. The GH kinematic accuracy (RMS error) was 0.6–1.0 mm and 0.6–2.2° for the CT-based registration and 1.4–2.2 mm and 1.2–2.6° for MRI-based registration. Higher kinematic accuracy of CT-based registration was expected as MRI provides lower spatial resolution and bone contrast as compared to CT and suffers from spatial distortions. However, the MRI-based registration is within an acceptable accuracy for many clinical research questions.

Biplane radiography and associated shape-matching provides non-invasive, dynamic, 3D osteo-and arthrokinematic analysis. Due to the complexity of data acquisition, each system should be validated for the anatomy of interest. The purpose of this study was to assess our system's acquisition methods and validate a custom, automated 2D/3D shape-matching algorithm relative to radiostereometric analysis (RSA) for the cervical and lumbar spine. Additionally, two sources of RSA error were examined via a Monte Carlo simulation: 1) static bead centroid identification and 2) dynamic bead tracking error. Tantalum beads were implanted into a cadaver for RSA and cervical and lumbar spine flexion and lateral bending were passively simulated. A bead centroid identification reliability analysis was performed and a vertebral validation block was used to determine bead tracking accuracy. Our system's overall root mean square error (RMSE) for the cervical spine ranged between 0.21-0.49mm and 0.42-1.80˚and the lumbar spine ranged between 0.35-1.17mm and 0.49-1.06˚. The RMSE associated with RSA ranged between 0.14-0.69mm and 0.96-2.33˚for bead centroid identification and 0.25-1.19mm and 1.69-4.06˚for dynamic bead tracking. The results of this study demonstrate our system's ability to accurately quantify segmental spine motion. Additionally, RSA errors should be considered when interpreting biplane validation results.