Comparative evaluation of scapular and humeral coordinate systems based on biomedical images of the glenohumeral joint

Correspondence between scapular anatomical coordinate systems and the 3D axis of motion: A new perspective on an old challenge

Several scapular anatomical coordinate systems have been reported in the literature to describe shoulder kinematics. Unfortunately, the use of different conventions hinders comparison across studies. Further, inconsistencies between a coordinate system and the scapula's 3D axis of motion means that scapular motion will be incorrectly attributed to axes about which it did not rotate. The objectives of this study were to: 1) determine the extent to which the axes of four common scapular coordinate system conventions correspond to the 3D axis of scapular motion (i.e., instantaneous helical axis, IHA), and 2) report the prevalence of scapulothoracic gimbal lock for each convention. Shoulder kinematics were tracked during scapular plane abduction in 45 participants using biplane videoradiography. Scapulothoracic kinematics were described using the original convention proposed by van der Helm, the convention recommended by the International Society of Biomechanics (ISB), a glenoid-based coordinate system, and a glenoid-oriented coordinate system. The 3D angle was calculated between the IHA and each axis of the four conventions (IHA-axis angular deviations). A repeated measures ANOVA was used to compare IHA-axis angular deviations between conventions. The glenoid-oriented and ISB conventions resulted in the smallest and largest IHA-axis angular deviations, respectively (21.7°±3.6° vs. 30.5°±5.2°, p < 0.01). Gimbal lock was approached in 17.8% of participants when using the original convention, 2.2% when using the ISB convention, and 0% when using the glenoid-based or -oriented conventions. These findings suggest the glenoid-oriented coordinate system may be worthy of further consideration when investigating shoulder kinematics during scapular plane abduction.

Proximal humeral coordinate systems can predict humerothoracic and glenohumeral kinematics of a full bone system

BACKGROUND

Clinical imaging often excludes the distal humerus, confounding definition of common whole-bone coordinate systems. While proximal anatomy coordinate systems exist, no simple method transforms them to whole-bone systems. Their influence on humeral kinematics is unknown.

RESEARCH QUESTION

How do humeral kinematics vary based on proximal and whole-bone coordinate systems, and can average rotation matrices accurately convert kinematics between them?

METHODS

Three proximal coordinate systems were defined by the lesser and greater tuberosities (LT, GT), Crest of the greater tuberosity, and humeral shaft. Average rotation matrices derived from anatomic landmarks on cadaver humeri were generated between the proximal and whole-bone coordinate systems. Absolute angle of rotation was used to determine if anatomical variability within the cadaver population influenced the matrices. The matrices were applied to humerothoracic and glenohumeral motion (collected previously) and analyzed using the proximal coordinate systems, then expressed in the whole-bone system. RMSE was used to compare kinematics from the proximal and whole-bone systems.

RESULTS

A single average rotation matrix between a given proximal and whole-bone coordinate system achieved consistent error, regardless of landmarks. Elevation and plane of elevation had <2° mean error when proximal coordinate systems were transformed to whole-bone kinematics. Axial rotation had a mean 7° error, primarily due to variable humeral head retroversion. Absolute angles of rotation did not statistically differ between subgroups. The average rotation matrices were independent of sex, side, and motion.

SIGNIFICANCE

Proximal humerus coordinate systems can accurately predict whole-bone kinematics, with most error concentrated in axial rotation due to anatomic twist along the bone. These results enhance interpretability and reproducibility in expressing humerothoracic and glenohumeral motion data between laboratories by providing a simple means to convert data between common coordinate systems. This is necessitated by the lack of distal humerus anatomy present in most clinical imaging.

Functional estimation of bony segment lengths using magneto-inertial sensing: Application to the humerus

Inertial sensor technology has assumed an increasingly important role in the field of human motion analysis. However, the reliability of the kinematic estimates could still be critical for specific applications in the field of functional evaluation and motor rehabilitation. Within this context, the definition of subject-specific multi-body kinematic models is crucial since it affects the accuracy and repeatability of movement reconstruction. A key step for kinematic model calibration is the determination of bony segment lengths. This study proposes a functional approach for the in vivo estimation of the humerus length using a single magneto-inertial measurement unit (MIMU) positioned on the right distal posterior forearm. The humerus length was estimated as the distance between the shoulder elevation axis and the elbow flexion-extension axis. The calibration exercise involved five shoulder elevations in the sagittal plane with the elbow completely extended and five elbow flexion-extensions with the upper arm rigidly aligned to the trunk. Validation of the method was conducted on five healthy subjects using the humerus length computed from magnetic resonance imaging as the gold standard. The method showed mean absolute errors of 12 ± 9 mm, which were in the estimate of the humerus length. When using magneto-inertial technology, the proposed functional method represents a promising alternative to the regressive methods or manual measurements for performing kinematic model calibrations. Although the proposed methodology was validated for the estimation of the humerus length, the same approach can be potentially extended to other body segments.

In vivo estimation of the shoulder joint center of rotation using magneto-inertial sensors: MRI-based accuracy and repeatability assessment

Background

The human gleno-humeral joint is normally represented as a spherical hinge and its center of rotation is used to construct humerus anatomical axes and as reduction point for the computation of the internal joint moments. The position of the gleno-humeral joint center (GHJC) can be estimated by recording ad hoc shoulder joint movement following a functional approach. In the last years, extensive research has been conducted to improve GHJC estimate as obtained from positioning systems such as stereo-photogrammetry or electromagnetic tracking. Conversely, despite the growing interest for wearable technologies in the field of human movement analysis, no studies investigated the problem of GHJC estimation using miniaturized magneto-inertial measurement units (MIMUs). The aim of this study was to evaluate both accuracy and precision of the GHJC estimation as obtained using a MIMU-based methodology and a functional approach.

Methods

Five different functional methods were implemented and comparatively assessed under different experimental conditions (two types of shoulder motions: cross and star type motion; two joint velocities: ω_max = 90°/s, 180°/s; two ranges of motion: Ɵ = 45°, 90°). Validation was conducted on five healthy subjects and true GHJC locations were obtained using magnetic resonance imaging.

Results

The best performing methods (NAP and SAC) showed an accuracy in the estimate of the GHJC between 20.6 and 21.9 mm and repeatability values between 9.4 and 10.4 mm. Methods performance did not show significant differences for the type of arm motion analyzed or a reduction of the arm angular velocity (180°/s and 90°/s). In addition, a reduction of the joint range of motion (90° and 45°) did not seem to influence significantly the GHJC position estimate except in a few subject-method combinations.

Conclusions

MIMU-based functional methods can be used to estimate the GHJC position in vivo with errors of the same order of magnitude than those obtained using traditionally stereo-photogrammetric techniques. The methodology proposed seemed to be robust under different experimental conditions. The present paper was awarded as “SIAMOC Best Methodological Paper 2016”.

Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images

We present a statistical shape model approach for automated segmentation of the proximal humerus and scapula with subsequent bone-cartilage interface (BCI) extraction from 3D magnetic resonance (MR) images of the shoulder region. Manual and automated bone segmentations from shoulder MR examinations from 25 healthy subjects acquired using steady-state free precession sequences were compared with the Dice similarity coefficient (DSC). The mean DSC scores between the manual and automated segmentations of the humerus and scapula bone volumes surrounding the BCI region were 0.926  ±  0.050 and 0.837  ±  0.059, respectively. The mean DSC values obtained for BCI extraction were 0.806  ±  0.133 for the humerus and 0.795  ±  0.117 for the scapula. The current model-based approach successfully provided automated bone segmentation and BCI extraction from MR images of the shoulder. In future work, this framework appears to provide a promising avenue for automated segmentation and quantitative analysis of cartilage in the glenohumeral joint.