Efficacy of the Pre-operative Three-Dimensional (3D) CT Scan Templating in Predicting Accurate Implant Size and Alignment in Robot Assisted Total Knee Arthroplasty.

Abstract

Nearly 20% of Total knee Arthroplasty patients remain dissatisfied. This is a major concern in twenty-first century arthroplasty practice. Accurate implant sizing is shown to improve the implant survival, knee balance and patient reported outcome. Aim of the current study is to assess the efficacy of pre-operative three-dimensional (3D) CT scan templating in a robot-assisted TKA in predicting the correct implant sizes and alignment. Prospectively collected data in a single center from 30 RA-TKAswas assessed. Inclusion criterion was patients with end stage arthritis (both osteoarthritis and rheumatoid arthritis) undergoing primary TKA. Patients undergoing revision TKA and patients not willing to participate in the study were excluded. Preliminary study of ten patients had indicated almost 100% accuracy in determining the implant size and position. Sample size was estimated to be 28 for 90% reduction in implant size and position error with α error of 0.05 and beta error of 0.20 with power of study being 80. Post-operative radiographs were assessed by an independent observer with respect to implant size and position. The accuracy of femoral and tibial component sizing in the study was compared with the historic control with Chi-squared test. The p value < 0.05 was considered significant. The pre-operative CT scan 3D templating accuracy was 100% (30 out of 30 knees) for femoral component and 96.67% (29 out of 30 knees) for tibial component. The implant position and limb alignment was accurate in 100% of patients. The accuracy of femoral component and tibial component sizing is statistically significant (Chi-squared test, p value 0.0105 and 0.0461, respectively). The study results show the effectiveness of pre-operative 3 D CT scan planning in predicting the implant sizes and implant positioning. This may have a potential to improve the implant longevity, clinical outcomes and patient satisfaction.