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  • https://doi.org/10.18122/td/1464/boisestateCopy DOI Icon

A Computational Approach to Optimize Surgical Intervention for Patients with Recurrent Patellar Dislocation on a Subject-Specific Basis

  • Jan 15, 2019
  • Oliver Alvarez
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Abstract

Lateral patellar dislocation is one of the most common acute knee injuries in young active people and accounts for 3% of all knee injuries. Over 20,000 persons per year are affected by an initial incidence of patellar dislocation.Conservative treatment through physical therapy after initial dislocation is often recommended, but results are unsatisfactory. Approximately half of these first-time dislocation patients go on to experience a subsequent dislocation or multiple dislocation events.A targeted patient-specific approach that directly addresses risk factors for patellar dislocation has potential to improve surgical outcomes for patients with recurrent instability. This work includes two research studies. First, clinical intervention for patients who suffer from recurrent patellar dislocation were optimized using finite element analysis. The objective of this study was to compare preoperative patellofemoral (PF) joint stability with stability after restorative surgery to correct to pre-injury state, generic tibial tubercle osteotomy, patient specific reconstructive surgery to correct anatomic abnormality, less invasive patient specific surgery and equivalent healthy controls. Dynamic, three-dimensional (3D), subject-specific finite element models of the patellofemoral joint were developed for 28 patients with recurrent patellar dislocation and lateral stability of the PF joint was assessed. Medial patellofemoral ligament (MPFL) reconstruction, along with reconstructive procedures to correct anatomic abnormality were simulated. Of all the simulations performed, the healthy equivalent control models showed the least patellar internal-external (I-E) rotation, medial-lateral (M-L) translation, and MPFL restraining load during lateral loading tests. Patient specific reconstructions to correct anatomic abnormality were not significantly different from the healthy equivalent control models (p > 0.05). This study suggests patient specific reconstructive surgery that corrects underlying anatomic abnormalities best reproduces the joint stability of an equivalent healthy control when compared to pre-injury state, generic tibial tubercle osteotomy, and less invasive patient specific surgery. The second project focuses on rapid generation of patient specific models (PSM). The objective of this study was to efficiently and accurately generate PSM of the human knee for finite element analysis (FEA). Dual kriging mesh deformation was utilized to morph a source template mesh onto a target patient specific mesh. Meshes created from dual kriging were compared with manually reconstructed PSM based on three criteria: (i) time to generate a model, (ii) mesh accuracy and (iii) accuracy of finite element results. The time to create a PSM by kriging deformation was significantly less (p0.05). This combined approach of rapid PSM mesh generation and application of finite element analysis to investigate subject-specific

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