Optimised pre-operative planning for elbow arthrolysis

  • Didier Alonso Salvador

    Student thesis: Master of Philosophy


    The University of Manchester, Didier Alonso Salvador, Master of Philosophy (Mphil), Optimised pre-operative planning for elbow arthrolysis, 29th of September, 2016. Elbow Arthrolysis is a surgical operation intended to restore the range of motion in the elbow by removing the mechanical blocks present, such as osteophytes. While the operation is considered safe, the elbow stability depends critically on the geometry of the bones, and the amount of bone removed currently depends solely on the experience of the surgeon. For this reason, the amount of range of motion restored to the joint is only known until after recovery. The aim of the research is to create a model that provides the basis for a system that allows the surgeons to optimize the amount of bone removed to restore the range of motion in the elbow, with minimal removal of bone to maintain the stability of the elbow. The model is created using CT Scans of the elbow and analysed in Finite Element Analysis software (FEA). CT Scans from an elbow without bone impingement and one with bone impingement were used to obtain the geometries of the bones using segmentation software, including the differentiation of the cortical shell, the trabecular bone and the cartilage layer. A FE model was created using the obtained geometries, simulating the effects of the surrounding tissue to guide the motion of the joint, and identify the areas of contact between the bones; the ligaments were used as the main stabilizers of the joint while the while the muscles were used to apply force. This model can identify the regions where impingement occurs, by comparing the differences in contact between the model of a healthy elbow to the model of an elbow presenting bone impingement, those areas can then be virtually resected to restore the motion of the joint. The FE models were validated by comparing the RoM predicted by the model without bone impingement to RoM data obtained from clinical tests. The accuracy of the model was validated on a case study of a patient treated for bone impingement of the elbow; CT scans were obtained from before and after the surgery, and used to create models to simulate the range of motion of the patient, which was then compared to the RoM data measured by the surgeon. The same methodology used to resect the model with bone impingement was applied to the preoperative virtual model of the case study, comparing the results from traditional surgery, to the surgery assisted by the model. The predicted results using the technique showed than a larger restoration of the RoM can be achieved with significantly less removal of bone; in the case study, the RoM measured after the virtual resection was 12% larger than the postoperative model while the volume of bone resected was only around half of the original resection. The technique presented can then be used to significantly improve the preoperative stage of elbow arthrolysis, allowing the surgeons to more accurately remove the osteophytes causing impingement, which in turn leads to a larger restoration of the RoM, less recovery time for the patient, and a reduced chance of further surgeries being required to restore mobility to the joint.
    Date of Award1 Aug 2018
    Original languageEnglish
    Awarding Institution
    • The University of Manchester
    SupervisorM.T. Alonso-Rasgado (Supervisor) & Colin Bailey (Supervisor)


    • Preoperative planning
    • Virtual resection
    • Finite element
    • Range of motion
    • Elbow arthrolysis
    • Bone impingement

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