In this study we randomised 140 patients who
were due to undergo primary total knee arthroplasty (TKA) to have the
procedure performed using either
Objectives. Unicompartmental knee arthroplasty (UKA) is an alternative to total knee arthroplasty for patients who require treatment of single-compartment osteoarthritis, especially for young patients. To satisfy this requirement, new
Objectives.
Aims.
Improvements in the surgical technique of total
knee replacement (TKR) are continually being sought. There has recently
been interest in three-dimensional (3D) pre-operative planning using
magnetic resonance imaging (MRI) and CT. The 3D images are increasingly
used for the production of
Aims. The purpose of the present study was to compare
We conducted a meta-analysis, including randomised
controlled trials (RCTs) and cohort studies, to examine the effect
of
Patient specific instrumentation (PSI) uses advanced
imaging of the knee (CT or MRI) to generate individualised cutting
blocks aimed to make the procedure of total knee arthroplasty (TKA)
more accurate and efficient. However, in this era of healthcare
cost consciousness, the value of new technologies needs to be critically
evaluated. There have been several comparative studies looking at
PSI Cite this article:
This prospective randomised controlled trial was designed to
evaluate the outcome of both the MRI- and CT-based patient-specific
matched guides (PSG) from the same manufacturer. A total of 137 knees in 137 patients (50 men, 87 women) were
included, 67 in the MRI- and 70 in the CT-based PSG group. Their
mean age was 68.4 years (47.0 to 88.9). Outcome was expressed as
the biomechanical limb alignment (centre hip-knee-ankle: HKA-axis)
achieved post-operatively, the position of the individual components
within 3° of the pre-operatively planned alignment, correct planned
implant size and operative data (e.g. operating time and blood loss).Aims
Patients and Methods
Aims. The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. Methods. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct
Aims. Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort. Methods. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A DL workflow was created to measure the FMAA and validated against human measurements. To reflect potential intramedullary guide placement during manual TKA, two different FMAAs were calculated either using a line approximating the entire diaphyseal shaft, and a line connecting the apex of the femoral intercondylar sulcus to the centre of the diaphysis. The proportion of FMAAs outside a range of 5.0° (SD 2.0°) was calculated for both definitions, and FMAA was compared using univariate analyses across sex, BMI, knee alignment, and femur length. Results. The algorithm measured 1,078 radiographs at a rate of 12.6 s/image (2,156 unique measurements in 3.8 hours). There was no significant difference or bias between reader and algorithm measurements for the FMAA (p = 0.130 to 0.563). The FMAA was 6.3° (SD 1.0°; 25% outside range of 5.0° (SD 2.0°)) using definition one and 4.6° (SD 1.3°; 13% outside range of 5.0° (SD 2.0°)) using definition two. Differences between males and females were observed using definition two (males more valgus; p < 0.001). Conclusion. We developed a rapid and accurate DL tool to quantify the FMAA. Considerable variation with different measurement approaches for the FMAA supports that
Aims. No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model. Methods. A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data. Results. The key factors for predicting operating time were the surgeon and patient weight, followed by 12 anatomical parameters derived from CT scans. The predictive model based only on demographic data showed that 90% of predictions were within 15 minutes of actual operating time, with 73% within ten minutes. The predictive model including demographic data and CT scans showed that 94% of predictions were within 15 minutes of actual operating time and 88% within ten minutes. Conclusion. The primary factors for predicting robotic-assisted TKA operating time were surgeon, patient weight, and osteophyte volume. This study demonstrates that incorporating 3D
Aims. Accurate identification of the ankle joint centre is critical for estimating tibial coronal alignment in total knee arthroplasty (TKA). The purpose of the current study was to leverage artificial intelligence (AI) to determine the accuracy and effect of using different radiological anatomical landmarks to quantify mechanical alignment in relation to a traditionally defined radiological ankle centre. Methods. Patients with full-limb radiographs from the Osteoarthritis Initiative were included. A sub-cohort of 250 radiographs were annotated for landmarks relevant to knee alignment and used to train a deep learning (U-Net) workflow for angle calculation on the entire database. The radiological ankle centre was defined as the midpoint of the superior talus edge/tibial plafond. Knee alignment (hip-knee-ankle angle) was compared against 1) midpoint of the most prominent malleoli points, 2) midpoint of the soft-tissue overlying malleoli, and 3) midpoint of the soft-tissue sulcus above the malleoli. Results. A total of 932 bilateral full-limb radiographs (1,864 knees) were measured at a rate of 20.63 seconds/image. The knee alignment using the radiological ankle centre was accurate against ground truth radiologist measurements (inter-class correlation coefficient (ICC) = 0.99 (0.98 to 0.99)). Compared to the radiological ankle centre, the mean midpoint of the malleoli was 2.3 mm (SD 1.3) lateral and 5.2 mm (SD 2.4) distal, shifting alignment by 0.34. o. (SD 2.4. o. ) valgus, whereas the midpoint of the soft-tissue sulcus was 4.69 mm (SD 3.55) lateral and 32.4 mm (SD 12.4) proximal, shifting alignment by 0.65. o. (SD 0.55. o. ) valgus. On the intermalleolar line, measuring a point at 46% (SD 2%) of the intermalleolar width from the medial malleoli (2.38 mm medial adjustment from midpoint) resulted in knee alignment identical to using the radiological ankle centre. Conclusion. The current study leveraged AI to create a consistent and objective model that can estimate
Aims. A functional anterior cruciate ligament (ACL) or posterior cruciate ligament (PCL) has been assumed to be required for patients undergoing unicompartmental knee arthroplasty (UKA). However, this assumption has not been thoroughly tested. Therefore, this study aimed to assess the biomechanical effects exerted by cruciate ligament-deficient knees with medial UKAs regarding different posterior tibial slopes. Methods. ACL- or PCL-deficient models with posterior tibial slopes of 1°, 3°, 5°, 7°, and 9° were developed and compared to intact models. The kinematics and contact stresses on the tibiofemoral joint were evaluated under gait cycle loading conditions. Results. Anterior translation increased in ACL-deficient UKA cases compared with intact models. In contrast, posterior translation increased in PCL-deficient UKA cases compared with intact models. As the posterior tibial slope increased, anterior translation of ACL-deficient UKA increased significantly in the stance phase, and posterior translation of PCL-deficient UKA increased significantly in the swing phase. Furthermore, as the posterior tibial slope increased, contact stress on the other compartment increased in cruciate ligament-deficient UKAs compared with intact UKAs. Conclusion. Fixed-bearing medial UKA is a viable treatment option for patients with cruciate ligament deficiency, providing a less invasive procedure and allowing
Aims. The primary objective of this registry-based study was to compare patient-reported outcomes of cementless and cemented medial unicompartmental knee arthroplasty (UKA) during the first postoperative year. The secondary objective was to assess one- and three-year implant survival of both fixation techniques. Methods. We analyzed 10,862 cementless and 7,917 cemented UKA cases enrolled in the Dutch Arthroplasty Registry, operated between 2017 and 2021. Pre- to postoperative change in outcomes at six and 12 months’ follow-up were compared using mixed model analyses. Kaplan-Meier and Cox regression models were applied to quantify differences in implant survival. Adjustments were made for
Aims. The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty. Methods. Using an US system, which is fitted with an electromagnetic (EM) tracker that is integrated into the US probe, allows 3D tracking of the probe, femur, and tibia. The raw US radiofrequency (RF) signals are acquired and, using real-time signal processing, bone boundaries are extracted. Bone boundaries and the tracking information are fused in a 3D point cloud for the femur and tibia. Using a statistical shaping model, the
Aims. Wear of the polyethylene (PE) tibial insert of total knee arthroplasty (TKA) increases the risk of revision surgery with a significant cost burden on the healthcare system. This study quantifies wear performance of tibial inserts in a large and diverse series of retrieved TKAs to evaluate the effect of factors related to the patient, knee design, and bearing material on tibial insert wear performance. Methods. An institutional review board-approved retrieval archive was surveyed for modular PE tibial inserts over a range of in vivo duration (mean 58 months (0 to 290)). Five knee designs, totalling 1,585 devices, were studied. Insert wear was estimated from measured thickness change using a previously published method. Linear regression statistical analyses were used to test association of 12 patient and implant design variables with calculated wear rate. Results. Five
Aims. A retrospective longitudinal study was conducted to compare directly volumetric wear of retrieved polyethylene inserts to predicted volumetric wear modelled from individual gait mechanics of total knee arthroplasty (TKA) patients. Methods. In total, 11 retrieved polyethylene tibial inserts were matched with gait analysis testing performed on those patients. Volumetric wear on the articular surfaces was measured using a laser coordinate measure machine and autonomous reconstruction. Knee kinematics and kinetics from individual gait trials drove computational models to calculate medial and lateral tibiofemoral contact paths and forces. Sliding distance along the contact path, normal forces and implantation time were used as inputs to Archard’s equation of wear to predict volumetric wear from gait mechanics. Measured and modelled wear were compared for each component. Results. Volumetric wear rates on eight non-delaminated components measured 15.9 mm. 3. /year (standard error (SE) ± 7.7) on the total part, 11.4 mm. 3. /year (SE ± 6.4) on the medial side and 4.4 (SE ± 2.6) mm. 3. /year on the lateral side. Volumetric wear rates modelled from patient gait mechanics predicted 16.4 mm. 3. /year (SE 2.4) on the total part, 11.7 mm. 3. /year (SE 2.1) on the medial side and 4.7 mm. 3. /year (SE 0.4) on the lateral side. Measured and modelled wear volumes correlated significantly on the total part (p = 0.017) and the medial side (p = 0.012) but not on the lateral side (p = 0.154). Conclusion. In the absence of delamination,
We have previously reported the short-term radiological
results of a randomised controlled trial comparing kinematically
aligned total knee replacement (TKR) and mechanically aligned TKR,
along with early pain and function scores. In this study we report
the two-year clinical results from this trial. A total of 88 patients
(88 knees) were randomly allocated to undergo either kinematically
aligned TKR using