Aims. Classifying trochlear dysplasia (TD) is useful to determine the treatment options for patients suffering from patellofemoral instability (PFI). There is no consensus on which classification system is more reliable and reproducible for the purpose of guiding clinicians’ management of PFI. There are also concerns about the validity of the Dejour Classification (DJC), which is the most widely used classification for TD, having only a fair reliability score. The Oswestry-Bristol Classification (OBC) is a recently proposed system of classification of TD, and the authors report a fair-to-good interobserver agreement and good-to-excellent intraobserver agreement in the assessment of TD. The aim of this study was to compare the reliability and reproducibility of these two classifications. Methods. In all, six assessors (four consultants and two registrars) independently evaluated 100 axial MRIs of the patellofemoral joint (PFJ) for TD and classified them according to OBC and DJC. These assessments were again repeated by all raters after four weeks. The inter- and intraobserver reliability scores were calculated using Cohen’s kappa and Cronbach’s α. Results. Both classifications showed good to excellent
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. 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.Aims
Methods
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. 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.Aims
Methods
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). 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.Aims
Methods
Joint registries classify all further arthroplasty procedures to a knee with an existing partial arthroplasty as revision surgery, regardless of the actual procedure performed. Relatively minor procedures, including bearing exchanges, are classified in the same way as major operations requiring augments and stems. A new classification system is proposed to acknowledge and describe the detail of these procedures, which has implications for risk, recovery, and health economics. Classification categories were proposed by a surgical consensus group, then ranked by patients, according to perceived invasiveness and implications for recovery. In round one, 26 revision cases were classified by the consensus group. Results were tested for inter-rater reliability. In round two, four additional cases were added for clarity. Round three repeated the survey one month later, subject to inter- and intrarater reliability testing. In round four, five additional expert partial knee arthroplasty surgeons were asked to classify the 30 cases according to the proposed revision partial knee classification (RPKC) system.Aims
Methods
The Oswestry-Bristol Classification (OBC) was recently described as an MRI-based classification tool for the femoral trochlear. The authors demonstrated better inter- and intraobserver agreement compared to the Dejour classification. As the OBC could potentially provide a very useful MRI-based grading system for trochlear dysplasia, it was the aim to determine the inter- and intraobserver reliability of the classification system from the perspective of the non-founder. Two orthopaedic surgeons independently assessed 50 MRI scans for trochlear dysplasia and classified each according to the OBC. Both observers repeated the assessments after six weeks. The inter- and intraobserver agreement was determined using Cohen’s kappa statistic and S-statistic nominal and linear weights.Aims
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