When Can I Trust The Robot? An Algorithm for CT-Based Robotic-Assisted Total Hip Arthroplasty

Robotic-assisted total hip arthroplasty (THA) has been shown to demonstrate a variety of clinical benefits for patients, including reductions in dislocation rates, decreased impingement, and improved implant longevity. However, variability in surgeon experience with robotic systems can lead to inconsistent results. Mastery of the initial acetabular registration step is critical to performing a predictable and accurate robotic-assisted total hip replacement.

We retrospectively reviewed 100 consecutive patients who underwent unilateral THA with MAKOplasty®. From this data, we reviewed where errors in planning or registration occurred. These cases either required a repeat registration if the error was caught early, or the errors were realized on postoperative imaging when the x-ray did not match the preoperative plan. Subsequently, we developed an algorithm to ensure accurate registration and implemented its use on the next 100 cases, again reviewing the intraoperative case data and postoperative x-rays for any errors.

Initial analysis revealed that 87 of the first 100 cases were correctly registered, where postoperative acetabular cup position matched the plan on first attempt. Of the remaining 13 cases that had a registration error, eight cases were identified intra-operatively and re-registered. There were five cases where the postoperative x-ray did not match the plan despite a "good" registration. For incorrectly registered cases (N = 13), seven of 13 were found to exhibit a type I error (initial registration), while six of 13 demonstrated a type II error (fine point registration). Following the implementation of our registration algorithm, we were able to decrease the discrepancy between the preoperative plan (planning) and the postoperative x-rays (execution) from 13% to 0% of cases.

In this study, we present a detailed method to examine registration errors during robotic-navigated THA with MAKOplasty®. From this analysis, we were able to develop a successful algorithm that allows the surgeon to ensure correct registration and ultimately a postoperative x-ray that matches the preoperative plan. Our algorithm presents a principled approach that provides the surgeon and patient confidence in the safety and efficacy a roboticassisted total hip replacement.