Glenohumeral joint reconstruction using statistical shape modeling

A Novel Radiological Classification System of the Proximal Humerus

Different anatomical variants have been reported for the proximal and distal femur. Given this context, the goal of our study was to answer the following question: Can we also identify different anatomical variants of the proximal humerus?Two hundred anteroposterior (AP) radiographs of the proximal humerus with an equal gender distribution and equal laterality per gender were reviewed. The metaphyseal diameter of the proximal humerus at the level of the anatomical neck (X) and the intramedullary diameter at 10 cm from the apex of the greater tuberosity (Y) were measured. A new ratio was established, based on both measurements (Y/X). Radiographs showed different anatomical variants: type A: Y/X < 0.3, type B: Y/X = 0.3-0.4, type C: Y/X > 0.4. Two observers reviewed the AP radiographs independently and blindly in 2 different sessions.Three different anatomical groups (A, B and C) were identified based on the 25th and 75th percentiles. A higher percentage of type C was observed among females and a higher percentage of type A among males. A high inter-observer reliability was noted, with a Cronbach's alpha of 0.97 (ICC 0.96-0.98). The intra-observer reliability for observer 1 had a Cronbach's alpha of 0.98.A novel radiological classification of the proximal humerus has been established based on 3 different anatomical types (A, B and C). Further studies are needed to establish whether the novel classification system can be used as an indicator for aseptic loosening of cemented or cementless total shoulder arthroplasty.

OpenSim Moco tracking simulations efficiently replicate predictive simulation results across morphologically diverse shoulder models

OpenSim Moco enables solving for an optimal motion using Predictive and Tracking simulations. However, Predictive simulations are computationally prohibitive, and the efficacy of Tracking in deviating from its reference is unclear. This study compares Tracking and Predictive approaches applied to the generation of morphology-specific motion in statistically-derived musculoskeletal shoulder models. The signal analysis software, CORA, determined mean correlation ratings between Tracking and Predictive solutions of 0.91 ± 0.06 and 0.91 ± 0.07 for lateral and forward-reaching tasks. Additionally, Tracking provided computational speed-up of 6-8 times. Therefore, Tracking is an efficient approach that yields results equivalent to Predictive, facilitating future large-scale modelling studies.

Automatic bicipital groove identification in arthritic humeri for preoperative planning: A Random Forest Classifier approach

The bicipital groove is an important anatomical feature of the proximal humerus that needs to be identified during surgical planning for procedures such as shoulder arthroplasty and proximal humeral fracture reconstruction. Current algorithms for automatic identification prove ineffective in arthritic humeri due to the presence of osteophytes, reducing their usefulness for total shoulder arthroplasty. Our methodology involves the use of a Random Forest Classifier (RFC) to automatically detect the bicipital groove on segmented computed tomography scans of humeri. We evaluated our model on two distinct test datasets: one comprising non-arthritic humeri and another with arthritic humeri characterized by significant osteophytes. Our model detected the bicipital groove with a mean absolute error of less than 1mm on arthritic humeri, demonstrating a significant improvement over the previous gold standard approach. Successful identification of the bicipital groove with a high degree of accuracy even in arthritic humeri was accomplished. This model is open source and included in the python package shoulder.

Three-dimensional spine reconstruction from biplane radiographs using convolutional neural networks

PURPOSE

The purpose of this study was to develop and evaluate a deep learning network for three-dimensional reconstruction of the spine from biplanar radiographs.

METHODS

The proposed approach focused on extracting similar features and multiscale features of bone tissue in biplanar radiographs. Bone tissue features were reconstructed for feature representation across dimensions to generate three-dimensional volumes. The number of feature mappings was gradually reduced in the reconstruction to transform the high-dimensional features into the three-dimensional image domain. We produced and made eight public datasets to train and test the proposed network. Two evaluation metrics were proposed and combined with four classical evaluation metrics to measure the performance of the method.

RESULTS

In comparative experiments, the reconstruction results of this method achieved a Hausdorff distance of 1.85 mm, a surface overlap of 0.2 mm, a volume overlap of 0.9664, and an offset distance of only 0.21 mm from the vertebral body centroid. The results of this study indicate that the proposed method is reliable.

Prediction of the Proximal Humerus Morphology Based on a Statistical Shape Model with Two Parameters: Comparison to Contralateral Registration Method

(1) Background: Complex proximal humerus fractures often result in complications following surgical treatment. A better understanding of the full 3D displacement would provide insight into the fracture morphology. Repositioning of fracture elements is often conducted by using the contralateral side as a reconstruction template. However, this requires healthy contralateral anatomy. The purpose of this study was to create a Statistical Shape Model (SSM) and compare its effectiveness to the contralateral registration method for the prediction of the humeral proximal segment; (2) Methods: An SSM was created from 137 healthy humeri. A prediction for the proximal segment of the left humeri from eight healthy patients was made by combining the SSM with parameters. The predicted proximal segment was compared to the left proximal segment of the patients. Their left humerus was also compared to the contralateral (right) humerus; (3) Results: Eight modes explained 95% of the variation. Most deviations of the SSM prediction and the contralateral registration method were below the clinically relevant 2 mm distance threshold.; (4) Conclusions: An SSM combined with parameters is a suitable method to predict the proximal humeral segment when the contralateral CT scan is unavailable or the contralateral humerus is unhealthy, provided that the fracture pattern allows measurements of these parameters.

The Influence of Glenoid Bone Loss and Graft Positioning on Graft and Cartilage Contact Pressures After the Latarjet Procedure

BACKGROUND

Glenohumeral joint contact loading before and after glenoid bone grafting for recurrent anterior instability remains poorly understood.

PURPOSE

To develop a computational model to evaluate the influence of glenoid bone loss and graft positioning on graft and cartilage contact pressures after the Latarjet procedure.

STUDY DESIGN

Controlled laboratory study.

METHODS

A finite element model of the shoulder was developed using kinematics, muscle and glenohumeral joint loading of 6 male participants. Muscle and joint forces at 90° of abduction and external rotation were calculated and employed in simulations of the native shoulder, as well as the shoulder with a Bankart lesion, 10% and 25% glenoid bone loss, and after the Latarjet procedure.

RESULTS

A Bankart lesion as well as glenoid bone loss of 10% and 25% significantly increased glenoid and humeral cartilage contact pressures compared with the native shoulder (P < .05). The Latarjet procedure did not significantly increase glenoid cartilage contact pressure. With 25% glenoid bone loss, the Latarjet procedure with a graft flush with the glenoid and the humerus positioned at the glenoid half-width resulted in significantly increased humeral cartilage contact pressure compared with that preoperatively (P = .023). Under the same condition, medializing the graft by 1 mm resulted in humeral cartilage contact pressure comparable with that preoperatively (P = .097). Graft lateralization by 1 mm resulted in significantly increased humeral cartilage contact pressure in both glenoid bone loss conditions (P < .05).

CONCLUSION

This modeling study showed that labral damage and greater glenoid bone loss significantly increased glenoid and humeral cartilage contact pressures in the shoulder. The Latarjet procedure may mitigate this to an extent, although glenoid and humeral contact loading was sensitive to graft placement.

CLINICAL RELEVANCE

The Latarjet procedure with a correctly positioned graft should not lead to increased glenohumeral joint contact loading. The present study suggests that lateral graft overhang should be avoided, and in the situation of large glenoid bone defects, slight medialization (ie, 1 mm) of the graft may help to mitigate glenohumeral joint contact overloading.

Distal Humerus Morphological Analysis of Chinese Individuals: A Statistical Shape Modeling Approach

Objective

A detailed analysis of the morphology of distal humeral articulation can help in the creation of anatomic prostheses of hemiarthroplasty. This study used statistical shape modeling to evaluate the 3D morphology of the distal humerus in healthy Chinese individuals and to investigate the proper articular morphology differences.

Methods

A statistical shape model (SSM) of the distal humerus was created using CT scans of 106 survey‐confirmed nonpathologic elbows. In addition, the articular components of each principal component (PC) were selected and fitted on the mean mode. The Euclidean point‐to‐mesh distance of articular modes was calculated as a measurement the proper change in the morphology of the articulation.

Results

The first seven PCs jointly accounted for 80.9% of the total variation (44.4%, 12.2%, 7.9%, 5.9%, 4.1%, 3.4% and 3%, respectively). In the mean model, the distance between the medial and lateral epicondyles was 57.4 mm, the width of the articulation was 42.1 mm, and the angle of the transepicondylar line (TEL) and C line was 4.8°. The articular surface differences of the first PC were significant (RMS: 1.43 mm in the −3 SD model and 2.38 mm in the +3 SD model), whereas under other conditions, the differences were not remarkable despite the maximum deformation not exceeding 1 mm.

Conclusion

A novel method (SSM) was used to evaluate the 3D morphology of the distal humerus in healthy Chinese individuals and investigate the proper articular shape differences. We found the proper shape of articular surface basically transformed into one variation pattern which was relevant to the bone size, even though the morphology of distal humerus possessed complicated variation modes. The findings of this study can be helpful to design the next generation of elbow hemiarthroplasty in the future.

Complications of Reverse Total Shoulder Arthroplasty: A Computational Modelling Perspective

Reverse total shoulder arthroplasty (RTSA) is an established treatment for elderly patients with irreparable rotator cuff tears, complex proximal humerus fractures, and revision arthroplasty; however, with the increasing indications for RTSA over the last decade and younger implant recipients, post-operative complications have become more frequent, which has driven advances in computational modeling and simulation of reverse shoulder biomechanics. The objective of this study was to provide a review of previously published studies that employed computational modeling to investigate complications associated with RTSA. Models and applications were reviewed and categorized into four possible complications that included scapular notching, component loosening, glenohumeral joint instability, and acromial and scapular spine fracture, all of which remain a common cause of significant functional impairment and revision surgery. The computational shoulder modeling studies reviewed were primarily used to investigate the effects of implant design, intraoperative component placement, and surgical technique on postoperative shoulder biomechanics after RTSA, with the findings ultimately used to elucidate and mitigate complications. The most significant challenge associated with the development of computational models is in the encapsulation of patient-specific anatomy and surgical planning. The findings of this review provide a basis for future direction in computational modeling of the reverse shoulder.