Aims. While mechanical alignment (MA) is the traditional technique in total knee arthroplasty (TKA), its potential for altering constitutional alignment remains poorly understood. This study aimed to quantify unintentional changes to constitutional coronal alignment and joint line obliquity (JLO) resulting from MA. Methods. A retrospective cohort study was undertaken of 700 primary MA TKAs (643 patients) performed between 2014 and 2017. Lateral distal femoral and medial proximal tibial angles were measured pre- and postoperatively to calculate the arithmetic hip-knee-ankle angle (aHKA), JLO, and Coronal Plane Alignment of the Knee (CPAK) phenotypes. The primary outcome was the magnitude and direction of aHKA, JLO, and CPAK alterations. Results. The mean aHKA and JLO increased by 0.1° (SD 3.4°) and 5.8° (SD 3.5°), respectively, from pre- to postoperatively. The most common phenotypes shifted from 76.3% CPAK Types I, II, or III (apex distal JLO) preoperatively to 85.0% IV, V, or VI (apex horizontal JLO) postoperatively. The proportion of knees with apex proximal JLO increased from 0.7% preoperatively to 11.1% postoperatively. Among all MA TKAs, 60.0% (420 knees) were changed from their constitutional alignments into CPAK Type V, while 40.0% (280 knees) either remained in constitutional Type V (5.0%, 35 knees) or were unintentionally aligned into other CPAK types (35.0%; 245 knees). Conclusion. Fixed MA targets in TKA lead to substantial changes from constitutional alignment, primarily a significant increase in JLO. These findings enhance our understanding of alignment alterations resulting from both unintended changes to knee phenotypes and surgical resection imprecision. Cite this article: Bone Jt Open 2024;5(2):109–116

Aims. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680

Aims. The Coronal Plane Alignment of the Knee (CPAK) classification is a simple and comprehensive system for predicting pre-arthritic knee alignment. However, when the CPAK classification is applied in the Asian population, which is characterized by more varus and wider distribution in lower limb alignment, modifications in the boundaries of arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) should be considered. The purposes of this study were as follows: first, to propose a modified CPAK classification based on the actual joint line obliquity (aJLO) and wider range of aHKA in the Asian population; second, to test this classification in a cohort of Asians with healthy knees; third, to propose individualized alignment targets for different CPAK types in kinematically aligned (KA) total knee arthroplasty (TKA). Methods. The CPAK classification was modified by changing the neutral boundaries of aHKA to 0° ± 3° and using aJLO as a new variable. Radiological analysis of 214 healthy knees in 214 Asian individuals was used to assess the distribution and mean value of alignment angles of each phenotype among different classifications based on the coronal plane. Individualized alignment targets were set according to the mean lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) of different knee types. Results. A very high concentration, 191 from 214 individuals (89.3%), were found in knee types with apex distal JLO when the CPAK classification was applied in the Asian population. By using aJLO as a new variable, the high distribution percentage in knee types with apex distal JLO decreased to 125 from 214 individuals (58.4%). The most common types in order were Type II (n = 70; 32.7%), Type V (n = 55; 25.7%), and Type I (n = 46; 21.5%) in the modified CPAK classification. Conclusion. The modified CPAK classification corrected the uneven distribution when applying the CPAK classification in the Asian population. Setting individualized TKA alignment targets according to CPAK type may be a practical method to recreate optimal LDFA and MPTA in KA-TKA. Cite this article: Bone Jt Open 2022;3(3):211–217

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The aims of this study were: 1) to describe extended restricted kinematic alignment (E-rKA), a novel alignment strategy during robotic-assisted total knee arthroplasty (RA-TKA); 2) to compare residual medial compartment tightness following virtual surgical planning during RA-TKA using mechanical alignment (MA) and E-rKA, in the same set of osteoarthritic varus knees; 3) to assess the requirement of soft-tissue releases during RA-TKA using E-rKA; and 4) to compare the accuracy of surgical plan execution between knees managed with adjustments in component positioning alone, and those which require additional soft-tissue releases.

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This study examined windswept deformity (WSD) of the knee, comparing prevalence and contributing factors in healthy and osteoarthritic (OA) cohorts.

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The impact of a diaphyseal femoral deformity on knee alignment varies according to its severity and localization. The aims of this study were to determine a method of assessing the impact of diaphyseal femoral deformities on knee alignment for the varus knee, and to evaluate the reliability and the reproducibility of this method in a large cohort of osteoarthritic patients.

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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.

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The aim of this study was to screen the entire genome for genetic markers associated with risk for anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) injury.

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The processes linking long-term bisphosphonate treatment to atypical fracture remain elusive. To establish a means of exploring this link, we have examined how long-term bisphosphonate treatment with prior ovariectomy modifies femur fracture behaviour and tibia mass and shape in murine bones.