scholarly journals Robotic arm-assisted total knee arthroplasty improves preoperative planning and intraoperative decision-making

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Xufeng Wan ◽  
Qiang Su ◽  
Duan Wang ◽  
Mingcheng Yuan ◽  
Yahao Lai ◽  
...  

Abstract Background The reliability of robotic arm-assisted total knee arthroplasty (RA-TKA) has been previously reported. In this study, we evaluated the predictive accuracy of the RA-TKA system in determining the required bone resection and implant size preoperatively and its effect on intraoperative decision-making. Methods Data on the outcomes of RA-TKA procedures performed in our department were prospectively collected. A three-dimensional model of the femur, tibia, and fibula was reconstructed using standard computed tomography (CT) images. The model was used preoperatively to predict bone required resection for the femur and tibia and implant size. Intraoperatively, the images were registered to the local anatomy to create a patient-specific model for decision-making, including real-time measurement of the medial-to-lateral difference in the extension/flexion gap and TKA component alignment. Differences between predicted and real bone resections and implant size were evaluated, and the post-TKA mechanical axis of the lower limb and difference in medial-to-lateral flexion/extension gap were measured. Results The analysis was based on the data of 28 patients who underwent TKA to treat severe osteoarthritis. The RA-TKA system successfully predicted the femoral and tibial component within one implant size in 28/28 cases (100%). For the 168 bone resections performed, including both femoral and tibial cuts, the resection was within 1 mm of the predicted value in 120/168 (71%) of the cuts. The actual versus predicted bone resection was statistically different only for the lateral tibial plateau (p = 0.018). The medial-to-lateral gap difference was between − 1 and 1 mm, except in one case. The achieved lower limb alignment was accurate overall, with the alignment being within < 1.0° of the neutral mechanical axis in 13/28 cases (46%) and within < 3.0° in 28/28 cases (100%). Conclusions The RA-TKA system provided considerable pre- and intraoperative surgical assistance to achieve accurate bone resection, appropriate component sizing, and postoperative alignment after RA-TKA.

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Sharma Cook-Richardson ◽  
Rasesh Desai

In this case, we will describe a 68-year-old man with combined femoral and tibial bone deformities who underwent robotic arm-assisted total knee arthroplasty (RATKA) to treat his severe osteoarthritis in the setting of extra-articular deformities that altered the native anatomical axis and the kinematics of the deformed extra-articular bony structures which chronically generated a neomechanical axis. The combination of severe osteoarthritis with extra-articular deformities made the RATKA method the best surgical treatment option taking into account altered kinematics of the native joint which conventional jig-based total knee arthroplasty would not have prioritized during bony cuts and implant positioning. The patient underwent successful knee arthroplasty with robotic arm-assisted technology with restoration of the mechanical axis.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Liang Yuan ◽  
Bin Yang ◽  
Xiaohua Wang ◽  
Bin Sun ◽  
Ke Zhang ◽  
...  

Purpose. Bony resection is the primary step during total knee arthroplasty. The accuracy of bony resection was highly addressed because it was deemed to have a good relationship with mechanical line. Patient-specific instruments (PSI) were invented to copy the bony resection references from the preoperative surgical plan during a total knee arthroplasty (TKA); however, the accuracy still remains controversial. This study was aimed at finding out the accuracy of the bony resection during PSI-assisted TKA. Methods. Forty-two PSI-assisted TKAs (based on full-length leg CT images) were analyzed retrospectively. Resected bones of every patient were given a CT scan, and three-dimensional radiographs were reconstructed. The thickness of each bony resection was measured with the three-dimensional radiographs and recorded. The saw blade thickness (1.27 mm) was added to the measurements, and the results represented intraoperative bone resection thickness. A comparison between intraoperative bone resection thickness and preoperatively planned thickness was conducted. The differences were calculated, and the outliers were defined as >3 mm. Results. The distal femoral condyle had the most accurate bone cuts with the smallest difference (median, 1.0 mm at the distal medial femoral condyle and 0.8 mm at the distal lateral femoral condyle) and the least outliers (none at the distal medial femoral condyle and 1 (2.4%) at the distal lateral femoral condyle). The tibial plateau came in second (median difference, 0.8 mm at the medial tibial plateau and 1.4 mm at the lateral tibial plateau; outliers, none at the medial tibial plateau and 1 (2.6%) at the lateral tibial plateau). Regardless of whether the threshold was set to >2 mm (14 (17.9%) at the tibial plateau vs. 12 (14.6%) at the distal femoral condyle, p > 0.05 ) or >3 mm (1 (1.3%) at the tibial plateau vs. 1 (1.2%) at the distal femoral condyle, p > 0.05 ), the accuracy of tibial plateau osteotomy was similar to that of the distal femoral condyle. Osteotomy accuracy at the posterior femoral condyle and the anterior femoral condyle were the worst. Outliers were up to 6 (15.0%) at the posterior medial femoral condyle, 5 (12.2%) at the posterior lateral femoral condyle, and 6 (15.8%) at the anterior femoral condyle. The percentages of overcut and undercut tended to 50% in most parts except the lateral tibial plateau. At the lateral tibial plateau, the undercut percentage was twice that of the overcut. Conclusion. The tibial plateau and the distal femoral condyle share a similar accuracy of osteotomy with PSI. PSI have a generally good accuracy during the femur and tibia bone resection in TKA. PSI could be a kind of user-friendly tool which can simplify TKA with good accuracy. Level of Evidence. This is a Level IV case series with no comparison group.


Author(s):  
Jenny Zhang ◽  
Chelsea N. Matzko ◽  
Andrew Sawires ◽  
Joseph O. Ehiorobo ◽  
Michael A. Mont ◽  
...  

AbstractHaptic robotic-arm-assisted total knee arthroplasty (RATKA) seeks to leverage three-dimensional planning, intraoperative assessment of ligament laxity, and guided bone preparation to establish and achieve patient-specific targets for implant position. We sought to compare (1) operative details, (2) knee alignment, (3) recovery of knee function, and (4) complications during adoption of this technique to our experience with manual TKA. We compared 120 RATKAs performed between December 2016 and July 2018 to 120 consecutive manual TKAs performed between May 2015 and January 2017. Operative details, lengths of stay (LOS), and discharge dispositions were collected. Tibiofemoral angles, Knee Society Scores (KSS), and ranges of motion were assessed until 3 months postoperatively. Manipulations under anesthesia, complications, and reoperations were tabulated. Mean operative times were 22 minutes longer in RATKA (p < 0.001) for this early cohort, but decreased by 27 minutes (p < 0.001) from the first 25 RATKA cases to the last 25 RATKA cases. Less articular constraint was used to achieve stability in RATKA (93 vs. 55% cruciate-retaining, p < 0.001; 3 vs. 35% posterior stabilized (PS), p < 0.001; and 4 vs. 10% varus-valgus constrained, p_ = _0.127). RATKA had lower LOS (2.7 vs. 3.4 days, p < 0.001). Discharge dispositions, tibiofemoral angles, KSS, and knee flexion angles did not differ, but manipulations were less common in RATKAs (4 vs. 17%, p = 0.013). We observed less use of constraint, shorter LOS, and fewer manipulations under anesthesia in RATKA, with no increase in complications. Operative times were longer, particularly early in the learning curve, but improved with experience. All measured patient-centered outcomes were equivalent or favored the newer technique, suggesting that RATKA with patient-specific alignment targets does not compromise initial quality. Observed differences may relate to improved ligament balance or diminished need for ligament release.


2018 ◽  
Vol 6 (4_suppl2) ◽  
pp. 2325967118S0001
Author(s):  
Hagen Hommel

Mechanical axis of the lower limb assessed in standing long-leg radiographs was demonstrated to change within the first three postoperative months after total knee arthroplasty (TKA). The underlying mechanism including the influence of limb loading for the change in mechanical axis alignment after TKA has not been evaluated so far. Mechanical axis of the lower limb and limb loading were evaluated in 115 patients 10 days and 12 weeks after TKA. Mechanical axis was measured in standing long-leg radiographs while limb loading was simultaneously assessed using a scale. Absolute and relative limb loading with their correlation to the mechanical axis were calculated. Mechanical axis in patients with postoperative complete extension (n = 100) changed from an initial -0.82° ± 1.9° valgus alignment to a varus axis of +0.6° ± 1.5 (p < 0.01). This change in alignment was accompanied by an increased limb loading from 89.9% 10.7% to 93.0% 7.0% (p < 0.01). The mechanical axis highly/significantly correlated with relative limb loading in both measurements (r = 0.804, p < 0.001 respectively r = 0.562, p < 0.001). These alterations and distinctions were much more pronounced in patients with postoperative incomplete extension. Mechanical axis of the leg significantly changes while limb loading increases within the first three postoperative months after TKA. The postoperative alignment highly correlates with the loading of the lower limb. Therefore, the actual mechanical axis can only be assessed at physiological limb loading in long-leg radiographs at complete extension with full weight bearing.


Author(s):  
Leo Pauzenberger ◽  
Martin Munz ◽  
Georg Brandl ◽  
Julia K. Frank ◽  
Philipp R. Heuberer ◽  
...  

Abstract Background The purpose of this study was to compare restoration of mechanical limb alignment and three-dimensional component-positioning between conventional and patient-specific instrumentation in total knee arthroplasty. Methods Radiographic data of patients undergoing mobile-bearing total knee arthroplasty (n = 1257), using either conventional (n = 442) or patient-specific instrumentation (n = 812), were analyzed. To evaluate accuracy of axis restoration and 3D-component-positioning between conventional and patient-specific instrumentation, absolute deviations from the targeted neutral mechanical limb alignment and planned implant positions were determined. Measurements were performed on standardized coronal long-leg and sagittal knee radiographs. CT-scans were evaluated for accuracy of axial femoral implant rotation. Outliers were defined as deviations from the targeted neutral mechanical axis of > ± 3° or from the intraoperative component-positioning goals of > ± 2°. Deviations greater than ± 5° from set targets were considered to be severe outliers. Results Deviations from a neutral mechanical axis (conventional instrumentation: 2.3°± 1.7° vs. patient-specific instrumentation: 1.7°± 1.2°; p < 0.001) and numbers of outliers (conventional instrumentation: 25.8% vs. patient-specific instrumentation: 10.1%; p < 0.001) were significantly lower in the patient-specific instrumentation group. Significantly lower mean deviations and less outliers were detected regarding 3D-component-positioning in the patient-specific instrumentation compared to the conventional instrumentation group (all p < 0.05). Conclusions Patient-specific instrumentation prevented from severe limb malalignment and component-positioning outliers (> ± 5° deviation). Use of patient-specific instrumentation proved to be superior to conventional instrumentation in achieving more accurate limb alignment and 3D-component positioning, particularly regarding femoral component rotation. Furthermore, the use of patient-specific instrumentation successfully prevented severe (> 5° deviation) outliers.


2018 ◽  
Vol 32 (08) ◽  
pp. 742-749 ◽  
Author(s):  
Robert C. Marchand ◽  
Nipun Sodhi ◽  
Manoshi Bhowmik-Stoker ◽  
Laura Scholl ◽  
Caitlin Condrey ◽  
...  

Although several studies highlight the advantages of robotic arm-assisted total knee arthroplasty (RA-TKA), few investigate its intraoperative outcome. Therefore, the purpose of this study was to analyze the RA-TKA's ability to assist with intraoperative correction of: (1) flexion and (2) extension gaps, as well as its ability to (3) accurately predict implant sizes. Additionally, in this RA-TKA cohort, length of stay, complications, and readmissions were assessed. A total of 335 patients who underwent RA-TKA were included. The robotic software virtually measured the intraoperative prebone cut extension and flexion gaps. Differences in medial versus lateral prebone cut extension and flexion gaps were calculated. A total of 155 patients (46%) had an extension gap difference of between –2 and 2 mm (mean, –0.3 mm), while 119 patients (36%) had a flexion gap difference of between –2 and 2 mm (mean, –0.6 mm). Postbone cut differences in medial versus lateral flexion and extension gaps were measured. Balanced knees were considered to have a medial and lateral flexion gap difference within 2 mm. The robot-predicted implant size was also compared with the final implant size. Additionally, lengths of stay, complications, and readmissions were assessed. All patients achieved a postbone cut extension gap difference between –1 and 1 mm (mean, –0.1 mm). A total of 332 patients (99%) achieved a postbone cut flexion gap difference of between –2 and 2 mm (mean, 0 mm). For 98% of prostheses, the robotic software predicted within 1 implant size the actual tibial or femoral implant size used.The mean length of stay was found to be 2 days. No patients suffered from superficial skin infection, pin site infections or fractures, soft tissue damage, and no robotic cases were converted to manual TKA due to intraoperative complications. A total of 8 patients (2.2%) were readmitted; however, none were directly related to robotic use. The robotic software and use of a preoperative computed tomography (CT) substantially helped with intraoperative planning and accurate prediction of implant sizes. Therefore, based on the results of this study, the RA-TKA device does, in fact, provide considerable intraoperative assistance.


SICOT-J ◽  
2018 ◽  
Vol 4 ◽  
pp. 29 ◽  
Author(s):  
Ikram Nizam ◽  
Ashish V. Batra

Introduction: We conducted this study to determine if the pre-surgical patient specific instrumented planning based on Computed Tomography (CT) scans can accurately predict each of the femoral and tibial resections performed through 3D printed cutting guides. The technique helps in optimization of component positioning determined by accurate bone resection and hence overall alignment thereby reducing errors. Methods: Prophecy evolution medial pivot patient specific instrumented knee replacement systems were used for end stage arthrosis in all consecutive cases over a period of 20 months by a single surgeon. All resections (4 femoral and 2 tibial) were measured using a vernier callipers intraoperatively. These respective measurements were then compared with the preoperative CT predicted bone resection surgical plan to determine margins of errors that were categorized into 7 groups (0 mm to ≥2.6 mm). Results: A total of 3618 measurements (averaged to 1206) were performed in 201 knees (105 right and 96 left) in 188 patients (112 females and 76 males) with an average age of 67.72 years (44 to 90 years) and average BMI of 32.3 (25.1 to 42.3). 94% of all collected resection readings were below the error margin of ≤1.5 mm of which 90% showed resection error of ≤1 mm. Mean error of different resections were ≤0.60 mm (P ≤ 0.0001). In 24% of measurements there were no errors or deviations from the templated resection (0.0 mm). Conclusion: The 3D printed cutting blocks with slots for jigs accurately predict bone resections in patient specific instrumentation total knee arthroplasty which would directly affect component positioning.


2016 ◽  
Vol 06 (08) ◽  
pp. 253-258 ◽  
Author(s):  
Mohamed Mosa Mohamed ◽  
Maher A. El Assal ◽  
Ahmed M. Abdel Aal ◽  
Yaser E. Khalifa ◽  
Mahmoud A. Hafez

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