Iliopsoas impingement occurs in 4% to 30% of patients after undergoing total hip arthroplasty (THA). Despite a relatively high incidence, there are few attempts at modelling impingement between the iliopsoas and acetabular component, and no attempts at modelling this in a representative cohort of subjects. The purpose of this study was to develop a novel computational model for quantifying the impingement between the iliopsoas and acetabular component and validate its utility in a case-controlled investigation. This was a retrospective cohort study of patients who underwent THA surgery that included 23 symptomatic patients diagnosed with iliopsoas tendonitis, and 23 patients not diagnosed with iliopsoas tendonitis. All patients received postoperative CT imaging, postoperative standing radiography, and had minimum six months’ follow-up. 3D models of each patient’s prosthetic and bony anatomy were generated, landmarked, and simulated in a novel iliopsoas impingement detection model in supine and standing pelvic positions. Logistic regression models were implemented to determine if the probability of pain could be significantly predicted. Receiver operating characteristic curves were generated to determine the model’s sensitivity, specificity, and area under the curve (AUC).Aims
Methods
Leg length discrepancy (LLD) is a common pre- and postoperative issue in total hip arthroplasty (THA) patients. The conventional technique for measuring LLD has historically been on a non-weightbearing anteroposterior pelvic radiograph; however, this does not capture many potential sources of LLD. The aim of this study was to determine if long-limb EOS radiology can provide a more reproducible and holistic measurement of LLD. In all, 93 patients who underwent a THA received a standardized preoperative EOS scan, anteroposterior (AP) radiograph, and clinical LLD assessment. Overall, 13 measurements were taken along both anatomical and functional axes and measured twice by an orthopaedic fellow and surgical planning engineer to calculate intraoperator reproducibility and correlations between measurements.Aims
Methods
