The objective of this study was to compare macroscopic bone and soft tissue injury between robotic-arm assisted total knee arthroplasty (RA-TKA) and conventional jig-based total knee arthroplasty (CJ-TKA), and create a validated classification system for reporting iatrogenic bone and periarticular soft tissue injury following TKA.
This study included 30 consecutive CJ-TKAs followed by 30 consecutive RA-TKAs performed by a single-surgeon. Intraoperative photographs of the femur, tibia, and periarticular soft tissues were taken prior to implantation of prostheses. Using these outcomes, a macroscopic soft tissue injury (MASTI) classification system was developed to grade iatrogenic soft tissue injuries. Inter- and intra-observer validity of the proposed classification system was assessed.
Patients undergoing RA-TKA had reduced medial soft tissue injury in both passively correctible (p<0.05) and non-correctible varus deformities (p<0.05); more pristine femoral (p<0.05) and tibial (p<0.05) bone resection cuts; and improved MASTI scores compared to CJ-TKA (p<0.05). There was high inter-observer (ICC 0.92 [95% CI: 0.88-0.96], p<0.05) and intra-observer agreement (ICC 0.94 [95% CI: 0.92- 0.97], p<0.05) of the proposed MASTI classification system.
There is reduced bone and periarticular soft tissue injury in patients undergoing RA-TKA compared to CJ-TKA. The proposed MASTI classification system is a reproducible grading scheme for describing iatrogenic bone and soft tissue injury in TKA.
Robotic-assisted knee arthroplasty has been clinically available for the past 2 decades, but is still in the early stages of adoption for use in total knee arthroplasty (TKA). The purpose of this technology is to improve the precision, accuracy, and reproducibility of TKA. Robotic-assisted systems may be passive, semiactive, or active. Although robotic-assisted systems have been used extensively in unicondylar knee arthroplasty, there are relatively few studies of using this technology in TKA. These early studies have shown that robot-assisted technology may lead to improvements in both mechanical axis and component alignment. No studies have demonstrated that these radiographic improvements have translated into any clinical benefit, however. The purpose of this review is to introduce robotic-assisted systems for use in knee arthroplasty, describe the potential advantages and limitations associated with this technology, and review several of the systems that are currently available.
A method for x-ray image-guided robotic instrument positioning is reported and evaluated in preclinical studies of spinal pedicle screw placement with the aim of improving delivery of transpedicle K-wires and screws. The known-component (KC) registration algorithm was used to register the three-dimensional patient CT and drill guide surface model to intraoperative two-dimensional radiographs. Resulting transformations, combined with offline hand–eye calibration, drive the robotically held drill guide to target trajectories defined in the preoperative CT. The method was assessed in comparison with a more conventional tracker-based approach, and robustness to clinically realistic errors was tested in phantom and cadaver. Deviations from planned trajectories were analyzed in terms of target registration error (TRE) at the tooltip (mm) and approach angle (deg). In phantom studies, the KC approach resulted in TRE = 1.51 ± 0.51 mm and 1.01 deg ± 0.92 deg, comparable with accuracy in tracker-based approach. In cadaver studies with realistic anatomical deformation, the KC approach yielded TRE = 2.31 ± 1.05 mm and 0.66 deg ± 0.62 deg, with statistically significant improvement versus tracker (TRE = 6.09 ± 1.22 mm and 1.06 deg ± 0.90 deg). Robustness to deformation is attributed to relatively local rigidity of anatomy in radiographic views. X-ray guidance offered accurate robotic positioning and could fit naturally within clinical workflow of fluoroscopically guided procedures.
Studies have showed improved accuracy of lower leg alignment, precise component position, and soft-tissue balance with robotic-assisted unicompartmental knee arthroplasty (UKA). No studies, however, have assessed the effect on mid-term survivorship. Therefore, the purpose of this prospective multicenter study was to determine mid-tem survivorship, modes of failure, and satisfaction of robotic-assisted medial UKA.
473 consecutive patients (528 knees) underwent robotic-arm assisted medial UKA surgery at four separate institutions between March 2009 and December 2011. All patients received a fixed-bearing metal-backed onlay tibial component. Each patient was contacted at minimum five-year follow-up and asked a series of questions to determine survival and satisfaction. Kaplan-Meier method was used to determine survivorship.
Data was collected for 384 patients (432 knees) with mean follow-up of 5.7 years (5.0 – 7.7). The follow-up rate was 81.2%. In total, 13 revisions were performed, of which 11 knees were converted to TKA and in two cases one UKA component was revised, resulting in 97% survivorship. The mean time to revision was 2.27 years. The most common failure mode was aseptic loosening (7/13). Fourteen reoperations were reported. Of all unrevised patients, 91% was either very satisfied or satisfied with their knee function.
Robotic-arm assisted medial UKA showed high survivorship and satisfaction at mid-term follow-up in this prospective multicenter study. However, in spite of the robotic technique, early fixation failure remains the primary cause for revision with cemented implants. Comparative studies are necessary to confirm these findings and compare to conventional implanted UKA and TKA.