Abstract
Introduction
The application of digital radiography in clinical settings has provided the opportunity to obtain high quality images while reducing the overall cost of imaging, thus this technology is gaining more popularity in clinical settings specifically in orthopaedic clinics 1. In addition, advanced computer software helps with quick and easy approach to perform preoperative measurements with high accuracy 2. Preoperative templating has become one of the standard of care procedures that prepares the surgical team to lower surgical time and more efficiently face intraoperative complications 3. Commonly, the acetabular cup size and femoral stem size are templated and used for estimation process 4. However, the goal of this study was to investigate whether patients' demographics would play a role in increasing the accuracy of templating. We hypothesized that preoperative implant templating (acetabular and femoral components), gender, weight, height, and body mass index (BMI) would contribute to higher accuracy of templating in total hip arthroplasty (THA).
Method
Digital radiographs of 468 patients treated with THA from August 2012 to December 2013 at a single institution were reviewed. They aged 59.96 ±12.50 years and 436 of them were diagnosed with osteoarthritis, 53 with avascular necrosis, 13 with failed THA, 2 with infection, 4 post trauma, and 13 with failed hemi arthroplasty. THA templating was conducted by assessing the anteroposterior view of the pelvis that was centered over the pubic symphysis, with the hips in 10° to 15° of internal rotation and we utilized a lateral frog-leg view of the affected hip. A backward stepwise multiple regression model was used to exclude the parameters that had no significant contribution to the accuracy of the measurement.
Results
The outcome of the backward stepwise analysis indicated that in estimation of actual acetabular size, gender and body weight did not have a significant role however preoperative femoral and acetabular component size, BMI, and height were significant factors to predict the model. This model had an adjusted R2=0.795.
The femoral component size was significantly predicted from preoperative femoral size and other parameters did not add significant accuracy to the model. The model reached an adjusted R2 = 0.723.
Discussion
We explored the possibility of using other factors to improve the accuracy of preoperative templating. We were successful to predict the acetabular size with accuracy of 98.5% within two sizes and 100% femoral size in the same range. The additional accuracy may be translated in lower treatment costs by reducing expensive inventory fees.
