How Does Robotic-Arm Assisted Technology Influence Total Knee Arthroplasty Implant Placement for Surgeons in Fellowship Training?

Implant malalignment during total knee arthroplasty (TKA) may lead to suboptimal postoperative outcomes. Accuracy studies are typically performed with experienced surgeons; however, it is important to study less experienced surgeons when considering teaching hospitals where younger surgeons operate. Therefore, this study assessed whether robotic-arm assisted TKA (RATKA) allowed for more accurate and precise implant position to plan when compared with manual techniques when the surgery is performed by in-training orthopaedic surgical fellows. Two surgeons, currently in their fellowship training and having minimal RATKA experience, performed a total of six manual TKA (MTKA) and six RATKAs on paired cadaver knees. Computed tomography scans were obtained for each knee pre- and postoperatively. These scans were analyzed using a custom autosegmentation and autoregistration process to compare postoperative implant position with the preoperative planned position. Mean system errors and standard deviations were compared between RATKA and MTKA for the femoral component for sagittal, coronal, and axial planes and for the tibial component in the sagittal and coronal planes. A 2-Variance testing was performed using an α = 0.05. Although not statistically significant, RATKA was found to have greater accuracy and precision to plan than MTKA for: femoral axial plane (1.1° ± 1.1° vs. 1.6° ± 1.3°), coronal plane (0.9° ± 0.7° vs. 2.2° ± 1.0°), femoral sagittal plane (1.5° ± 1.3° vs. 3.1° ± 2.1°), tibial coronal plane (0.9° ± 0.5° vs. 1.9° ± 1.3°), and tibial sagittal plane (1.7° ± 2.6° vs. 4.7° ± 4.1°). There were no statistical differences between surgical groups or between the two surgeons performing the cases. With limited RATKA experience, fellows showed increased accuracy and precision to plan for femoral and tibial implant positions. Furthermore, these results were comparable to what has been reported for an experienced surgeon performing RATKA.

Magnetic resonance imaging-based three-dimensional bone shape of the knee predicts onset of knee osteoarthritis: data from the osteoarthritis initiative.

OBJECTIVE: To examine whether magnetic resonance imaging (MRI)-based 3-dimensional (3-D) bone shape predicts the onset of radiographic knee osteoarthritis (OA). METHODS: We conducted a case-control study using data from the Osteoarthritis Initiative by identifying knees that developed incident tibiofemoral radiographic knee OA (case knees) during followup, and matching them each to 2 random control knees. Using knee MRIs, we performed active appearance modeling of the femur, tibia, and patella and linear discriminant analysis to identify vectors that best classified knees with OA versus those without OA. Vectors were scaled such that -1 and +1 represented the mean non-OA and mean OA shapes, respectively. We examined the relation of 3-D bone shape to incident OA (new-onset Kellgren and Lawrence [K/L] grade ≥2) occurring 12 months later using conditional logistic regression. RESULTS: A total of 178 case knees (incident OA) were matched to 353 control knees. The whole joint (i.e., tibia, femur, and patella) 3-D bone shape vector had the strongest magnitude of effect, with knees in the highest tertile having a 3.0 times higher likelihood of developing incident radiographic knee OA 12 months later compared with those in the lowest tertile (95% confidence interval [95% CI] 1.8-5.0, P < 0.0001). The associations were even stronger among knees that had completely normal radiographs before incidence (K/L grade of 0) (odds ratio 12.5 [95% CI 4.0-39.3]). Bone shape at baseline, often several years before incidence, predicted later OA. CONCLUSION: MRI-based 3-D bone shape predicted the later onset of radiographic OA. Further study is warranted to determine whether such methods can detect treatment effects in trials and provide insight into the pathophysiology of OA development.