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 patient-specific anatomy and surgeon-dependent technique must be accounted for when correcting for the FMAA using an intramedullary guide. The angle between the mechanical and anatomical axes of the femur fell outside the range of 5.0° (SD 2.0°) for nearly a quarter of patients. Cite this article: Bone Jt Open 2024;5(2):101–108

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 patient-specific adjustments necessary for optimal landmark usage in extramedullary and computer-guided navigation for tibial coronal alignment to match radiological planning. Cite this article: Bone Jt Open 2022;3(10):767–776

Aims. Recent studies have suggested that corticosteroid injections into the knee may harm the joint resulting in cartilage loss and possibly accelerating the progression of osteoarthritis (OA). The aim of this study was to assess whether patients with, or at risk of developing, symptomatic osteoarthritis of the knee who receive intra-articular corticosteroid injections have an increased risk of requiring arthroplasty. Methods. We used data from the Osteoarthritis Initiative (OAI), a multicentre observational cohort study that followed 4,796 patients with, or at risk of developing, osteoarthritis of the knee on an annual basis with follow-up available up to nine years. Increased risk for symptomatic OA was defined as frequent knee symptoms (pain, aching, or stiffness) without radiological evidence of OA and two or more risk factors, while OA was defined by the presence of both femoral osteophytes and frequent symptoms in one or both knees. Missing data were imputed with multiple imputations using chained equations. Time-dependent propensity score matching was performed to match patients at the time of receving their first injection with controls. The effect of corticosteroid injections on the rate of subsequent (total and partial) knee arthroplasty was estimated using Cox proportional-hazards survival analyses. Results. After removing patients lost to follow-up, 3,822 patients remained in the study. A total of 249 (31.3%) of the 796 patients who received corticosteroid injections, and 152 (5.0%) of the 3,026 who did not, had knee arthroplasty. In the matched cohort, Cox proportional-hazards regression resulted in a hazard ratio of 1.57 (95% confidence interval (CI) 1.37 to 1.81; p < 0.001) and each injection increased the absolute risk of arthroplasty by 9.4% at nine years’ follow-up compared with those who did not receive injections. Conclusion. Corticosteroid injections seem to be associated with an increased risk of knee arthroplasty in patients with, or at risk of developing, symptomatic OA of the knee. These findings suggest that a conservative approach regarding the treatment of these patients with corticosteroid injections should be recommended. Cite this article: Bone Joint J 2020;102-B(5):586–592

We studied whether the presence of lateral osteophytes on plain radiographs was a predictor for the quality of cartilage in the lateral compartment of patients with varus osteoarthritic of the knee (Kellgren and Lawrence grade 2 to 3).

The baseline MRIs of 344 patients from the Osteoarthritis Initiative (OAI) who had varus osteoarthritis (OA) of the knee on hip-knee-ankle radiographs were reviewed. Patients were categorised using the Osteoarthritis Research Society International (OARSI) osteophyte grading system into 174 patients with grade 0 (no osteophytes), 128 grade 1 (mild osteophytes), 28 grade 2 (moderate osteophytes) and 14 grade 3 (severe osteophytes) in the lateral compartment (tibia). All patients had Kellgren and Lawrence grade 2 or 3 arthritis of the medial compartment. The thickness and volume of the lateral cartilage and the percentage of full-thickness cartilage defects in the lateral compartment was analysed.

There was no difference in the cartilage thickness or cartilage volume between knees with osteophyte grades 0 to 3. The percentage of full-thickness cartilage defects on the tibial side increased from < 2% for grade 0 and 1 to 10% for grade 3.

The lateral compartment cartilage volume and thickness is not influenced by the presence of lateral compartment osteophytes in patients with varus OA of the knee. Large lateral compartment osteophytes (grade 3) increase the likelihood of full-thickness cartilage defects in the lateral compartment.

Cite this article: Bone Joint J 2015;97-B:1634–9.

Early and accurate prediction of hospital length-of-stay (LOS) in patients undergoing knee replacement is important for economic and operational reasons. Few studies have systematically developed a multivariable model to predict LOS. We performed a retrospective cohort study of 1609 patients aged ≥ 50 years who underwent elective, primary total or unicompartmental knee replacements. Pre-operative candidate predictors included patient demographics, knee function, self-reported measures, surgical factors and discharge plans. In order to develop the model, multivariable regression with bootstrap internal validation was used. The median LOS for the sample was four days (interquartile range 4 to 5). Statistically significant predictors of longer stay included older age, greater number of comorbidities, less knee flexion range of movement, frequent feelings of being down and depressed, greater walking aid support required, total (versus unicompartmental) knee replacement, bilateral surgery, low-volume surgeon, absence of carer at home, and expectation to receive step-down care. For ease of use, these ten variables were used to construct a nomogram-based prediction model which showed adequate predictive accuracy (optimism-corrected R² = 0.32) and calibration. If externally validated, a prediction model using easily and routinely obtained pre-operative measures may be used to predict absolute LOS in patients following knee replacement and help to better manage these patients.

Cite this article: Bone Joint J 2013;95-B:1490–6.