Evaluation of a computational model to predict elbow range of motion

© 2014 The Author(s). Computer models capable of predicting elbow flexion and extension range of motion (ROM) limits would be useful for assisting surgeons in improving the outcomes of surgical treatment of patients with elbow contractures. A simple and robust computer-based model was developed that predicts elbow joint ROM using bone geometries calculated from computed tomography image data. The model assumes a hinge-like flexion-extension axis, and that elbow passive ROM limits can be based on terminal bony impingement. The model was validated against experimental results with a cadaveric specimen, and was able to predict the flexion and extension limits of the intact joint to 0° and 3°, respectively. The model was also able to predict the flexion and extension limits to 1° and 2°, respectively, when simulated osteophytes were inserted into the joint. Future studies based on this approach will be used for the prediction of elbow flexion-extension ROM in patients with primary osteoarthritis to help identify motion-limiting hypertrophic osteophytes, and will eventually permit real-time computer-assisted navigated excisions

A rigid body model for the assessment of glenohumeral joint mechanics: Influence of osseous defects on range of motion and dislocation

© 2016. The purpose of this study was to employ subject-specific computer models to evaluate the interaction of glenohumeral range-of-motion and Hill-Sachs humeral head bone defect size on engagement and shoulder dislocation. We hypothesized that the rate of engagement would increase as defect size increased, and that greater shoulder ROM would engage smaller defects. Three dimensional computer models of 12 shoulders were created. For each shoulder, additional models were created with simulated Hill-Sachs defects of varying severities (XS=15%, S=22.5%, M=30%, L=37.5%, XL=45% and XXL=52.5% of the humeral head diameter, respectively). Rotational motion simulations without translation were conducted. The simulations ended if the defect engaged the anterior glenoid rim with resultant dislocation. The results showed that the rate of engagement was significantly different between defect sizes (0.00

Accuracy assessment of 3D bone reconstructions using CT: An intro comparison

© 2015 IPEM. Computed tomography provides high contrast imaging of the joint anatomy and is used routinely to reconstruct 3D models of the osseous and cartilage geometry (CT arthrography) for use in the design of orthopedic implants, for computer assisted surgeries and computational dynamic and structural analysis. The objective of this study was to assess the accuracy of bone and cartilage surface model reconstructions by comparing reconstructed geometries with bone digitizations obtained using an optical tracking system. Bone surface digitizations obtained in this study determined the ground truth measure for the underlying geometry. We evaluated the use of a commercially available reconstruction technique using clinical CT scanning protocols using the elbow joint as an example of a surface with complex geometry. To assess the accuracies of the reconstructed models (8 fresh frozen cadaveric specimens) against the ground truth bony digitization-as defined by this study-proximity mapping was used to calculate residual error. The overall mean error was less than 0.4mm in the cortical region and 0.3mm in the subchondral region of the bone. Similarly creating 3D cartilage surface models from CT scans using air contrast had a mean error of less than 0.3mm. Results from this study indicate that clinical CT scanning protocols and commonly used and commercially available reconstruction algorithms can create models which accurately represent the true geometry