Accuracy of tibial cuts with patient-specific instrumentation is not influenced by the surgeon's level of experience

Predictive Accuracy Analysis of a Novel Robotic-Assisted System for Total Knee Arthroplasty:A Prospective Observational Study

Background

Robotic-assisted total knee arthroplasty (RATKA) has been reported to enhance operative decision-making. The purpose of this study was intended to assess the predictive accuracy of bone cuts, lower limb alignment, and component size of a novel system for RATKA preoperatively and intraoperatively.

Methods

Preoperatively planned bone cuts, limb alignment, and component size were projected using a reconstructed 3D model. Intraoperative bone cuts and postoperative limb alignment were measured. Errors between planned and real bone cuts, limb alignment, and component size were compared.

Results

The mean absolute errors for bone cuts and alignment were within 1.40mm/1.30° with a standard deviation (SD) of 0.96mm/1.12°. For all errors of bone cuts and alignment compared with the plan, there were no statistically significant differences except for the lateral distal of femoral cuts (P=0.004). The accuracy for predicting the femoral, tibial, and polyethylene component sizes was 100% (48/48), 90% (43/48), and 88% (42/48), respectively. Regarding all mean absolute errors of bone cuts and alignments, no significant differences were observed among surgeons.

Conclusion

The novel robotically-assisted system for RATKA donated reliable operative decision-making based on the predictive accuracy regardless of the surgeon's level of experience.

Total knee replacement with an accelerometer-based, hand-held navigation system improves knee alignment: reliable in all patients

BACKGROUND

Achieving adequate alignment has traditionally been an important goal in total knee arthroplasty to achieve long-term implant survival. While accelerometer-based hand-held navigation systems (ABN) has been introduced as a way to achieve alignment, there is a limited body of evidence on its accuracy, especially in patients under 65 years with differing etiologies for knee arthritis. This study aimed to assess the precision of a specific ABN system in restoring the mechanical axis and report surgical variables and complications, with particular attention to younger patients.

METHODS

We conducted a retrospective review of 310 primary TKA performed with ABN from May 2016 to February 2021. The mean patient age was 67.4 (SD 8.9) years, with 43% under 65 years and mean body mass index of 33.2 (SD 6.8). The average surgical time was 96.8 min (57-171) and the average follow-up was 3.3 years (1.9-6.7). Data regarding length of stay, pain, range of motion (ROM), complications, and reinterventions were collected from the institutional joint arthroplasty registry and the medical records. Preoperative mechanical axis measurements and postoperative radiological data, including mechanical axis, component alignment and mechanical alignment outliers were analyzed.

RESULTS

The mean preoperative mechanical axis was 175.4° (SD 7.6), with 248 knees (80%) in preoperative varus. The mean postoperative mechanical axis was 179.5° (SD 1.96) with 98% of knees falling within ± 3° of the neutral mechanical axis. Only 6 knees (2 varus, 4 valgus) fell outside the ± 3° range. And 3 knees (1 varus, 2 valgus) fell outside the ± 5° range. In the sagittal plane, 296 knees (95.5%) knees were within ± 3° of goal of 3 degrees of femoral flexion and 302 (97.4%) knees were within ± 2° of goal 1° of slope for tibial component. Far outliers (alignment outside ± 5° of targeted position) were found in 3 knees. Factors such as posttraumatic arthrosis, previous surgery, presence of retained hardware, and age below 65 years were not associated with increase in alignment outliers and far outliers. No complications related to the navigation system were observed. There were 22 complications and 20 reoperations, including 2 revisions for periprosthetic joint infection and 1 revision for flexion instability. Patients that required knee manipulation achieved an ultimate flexion of 110° (SD 14.1).

CONCLUSIONS

The ABN system proved to be user-friendly and accurate in reducing alignment outliers in both coronal and sagittal planes in all patient populations. It offers a straightforward navigation solution while preserving surgeon autonomy and the use of traditional surgical tools. These findings advocate for the integration of this navigation system as a valuable tool to enhance the precision of TKA surgery in all patient groups.

Using a patient-specific cutting guide enables identical knee osteotomies: An evaluation of accuracy on sawbones

PURPOSE

It was hypothesized that using a Patient-Specific Cutting Guide (PSCG) would allow the creation of sawbones model osteotomies, identical in the 3 planes and the hinge parameters, that can be used for biomechanical studies. The aim of the study was to evaluate the accuracy of the PSCG system and to introduce and assess the new hinge parameter; the hinge area.

METHODS

Six identical sawbones tibia models were identically set up for identical osteotomy cuts by the same surgeon in the same session and with identical instruments. A medical scanner was used to evaluate the 3D configuration of all the specimens. The analyzed parameters included the cutting angles in both the coronal and sagittal planes (degrees) and the hinge and the slicing areas (cm2), and the hinge thickness (mm). The values were statistically evaluated for average, standard deviation, 95% confidence index, and delta to the expected values were calculated.

RESULTS

The mean values for the coronal and sagittal angles were 110.5̊±1̊ and 89.8̊±0.8̊, respectively. The 95% confidence index level ranged between 0.1̊, and 0.8̊ in both the coronal & the sagittal planes. The mean values for the hinge thickness, the hinge area, and the slicing area were 12.7±1.5mm, 4.2±0.9 cm2, and 18.3±1.2 cm2, respectively.

CONCLUSION

In the presented study, it can be demonstrated that mechanically identical osteotomy specimens, with regard to the cutting planes and hinge parameters, can be reliably created using the PSCG. The identical specimens can be used for biomechanical research purposes to further expand our knowledge of the factors affecting osteotomy outcomes.

LEVEL OF EVIDENCE

IV.

Bone Cuts Accuracy of a System for Total Knee Arthroplasty including an Active Robotic Arm

Introduction: This study aimed to assess the bone cuts accuracy of a system for total knee arthroplasty including an active robotic arm. A second objective was to compare the accuracy among orthopaedic surgeons of different levels of experience. Methods: Three orthopaedic surgeons cut 10 sawbone knees each. Planned and actual bone cuts were compared using computed tomography. Difference with respect to the planning was expressed as three position and three orientation errors following the anatomical planes. Statistical tests were performed to detect bias and compare surgeons. Results: None of the 30 knees presented an outlier error, meaning an error ≥3 mm or ≥3°. The root-mean-square values of the 12 error types were below 0.8 mm or 0.8°, except for the femoral proximal–distal errors (1.7 mm) and the tibial anterior-posterior errors (1.4 mm). Biases were observed, particularly in femoral proximal–distal and tibial anterior–posterior positions. Median differences between surgeons were all lower than 0.8 mm and 0.5°, with statistically significant differences among surgeons in the femoral proximal–distal errors and the tibial anterior–posterior errors. Conclusions: The system tested in this study achieved accurate bone cuts independently of the surgeon’s level of experience. Biases were observed, suggesting that there might be options to improve the accuracy, particularly in proximal–distal position for the femur and in anterior–posterior position for the tibia.

Influence of patient selection, component positioning and surgeon's caseload on the outcome of unicompartmental knee arthroplasty

BACKGROUND

Implant malpositioning, low surgical caseload, and improper patient selection have been identified as essential factors, which could negatively affect the longevity of unicompartmental knee arthroplasty (UKA). The aim of the current study was to evaluate the impact of the surgeon's caseload on patient selection, component positioning, as well as component survivorship and functional outcomes following a PSI-UKA.

METHODS

A total of 125 patient-specific instrumented (PSI) UKA were included. One hundred and two cases were treated by a high-volume surgeon (usage 40%) and 23 cases by a low-volume surgeon (< 10 cases/year, usage 34%). Preoperative UIS, as well as the postoperative clinical and radiologic outcome, were assessed retrospectively.

RESULTS

Irrespective of the surgeon's UKA caseload, PSI allowed good accuracy in component positioning (p > 0.05). The high-volume surgeon had a more strict indication for UKA with 89% showing a UIS > 25 (considered a good indication) compared to 70% for the low-volume surgeon (p = 0.016). The low-volume surgeon achieved worse results regarding functional outcome (p < 0.05) and a tendency toward an increased risk for UKA failure (p = 0.11) compared to the high-volume surgeon.

CONCLUSION

Due to potential selection errors, mostly connected to a low UKA-caseload, low-volume UKA surgeons might achieve worse outcomes. Very strict indications for UKA might be recommended in low-volume surgeons to achieve excellent clinical outcomes following a UKA.

Update on unicompartmental knee arthroplasty: Current indications and failure modes

Despite the excellent success rates of modern implants, unicompartmental knee arthroplasty (UKA) continues to show relatively high failure and revision rates, especially when compared with total knee arthroplasty (TKA).

These higher rates of failure and revision are mainly observed during the early (< 5 years) post-operative period and are often due to incorrect indications and/or surgical errors.

The correct clinical and radiological indications for UKA have therefore been analysed and correlated as far as possible with the principal mechanisms and timing of failures of UKA.

Cite this article: EFORT Open Rev 2018;3:442-448. DOI: 10.1302/2058-5241.3.170060