Numerous complications following total knee replacement (TKR)
relate to the patellofemoral (PF) joint, including pain and patellar
maltracking, yet the options for A total of three knees with end-stage osteoarthritis and three
knees that had undergone TKR at more than one year’s follow-up were
investigated. In each knee, sequential biplane radiological images
were acquired from the sagittal direction (i.e. horizontal X-ray
source and 10° below horizontal) for a sequence of eight flexion
angles. Three-dimensional implant or bone models were matched to
the biplane images to compute the six degrees of freedom of PF tracking
and TF kinematics, and other clinical measures.Objectives
Methods
Endoprosthetic reconstruction with a distal femoral arthroplasty (DFA) can be used to treat distal femoral bone loss from oncological and non-oncological causes. This study reports the short-term implant survivorship, complications, and risk factors for patients who underwent DFA for non-neoplastic indications. We performed a retrospective review of 75 patients from a single institution who underwent DFA for non-neoplastic indications, including aseptic loosening or mechanical failure of a previous prosthesis (n = 25), periprosthetic joint infection (PJI) (n = 23), and native or periprosthetic distal femur fracture or nonunion (n = 27). Patients with less than 24 months’ follow-up were excluded. We collected patient demographic data, complications, and reoperations. Reoperation for implant failure was used to calculate implant survivorship.Aims
Methods
The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.Aims
Methods
An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry. A validation study was performed using five cadaver specimens. The actual mJSW was varied and images were acquired with variation in the cadaver positioning. For comparison purposes, the mJSW was also assessed from plain radiographs. To study the influence of SSM model accuracy, the 3D mJSW measurement was repeated with models from the actual bones, obtained from CT scans.Objectives
Materials and Methods
Static radiostereometric analysis (RSA) using implanted markers is considered the most accurate system for the evaluation of prosthesis migration. By using CT bone models instead of markers, combined with a dynamic RSA system, a non-invasive measurement of joint movement is enabled. This method is more accurate than current 3D skin marker-based tracking systems. The purpose of this study was to evaluate the accuracy of the CT model method for measuring knee joint kinematics in static and dynamic RSA using the marker method as the benchmark. Bone models were created from CT scans, and tantalum beads were implanted into the tibia and femur of eight human cadaver knees. Each specimen was secured in a fixture, static and dynamic stereoradiographs were recorded, and the bone models and marker models were fitted to the stereoradiographs.Objectives
Methods
In arthritis of the varus knee, a high tibial
osteotomy (HTO) redistributes load from the diseased medial compartment
to the unaffected lateral compartment. We report the outcome of 36 patients (33 men and three women)
with 42 varus, arthritic knees who underwent HTO and dynamic correction
using a Garches external fixator until they felt that normal alignment
had been restored. The mean age of the patients was 54.11 years
(34 to 68). Normal alignment was achieved at a mean 5.5 weeks (3
to 10) post-operatively. Radiographs, gait analysis and visual analogue
scores for pain were measured pre- and post-operatively, at one
year and at medium-term follow-up (mean six years; 2 to 10). Failure
was defined as conversion to knee arthroplasty. Pre-operative gait analysis divided the 42 knees into two equal
groups with high (17 patients) or low (19 patients) adductor moments.
After correction, a statistically significant (p <
0.001, At final follow-up, after a mean of 15.9 years (12 to 20), there
was a survivorship of 59% (95% CI 59.6 to 68.9) irrespective of
adductor moment group, with a mean time to conversion to knee arthroplasty
of 9.5 years (3 to 18; 95% confidence interval ± 2.5). HTO remains a useful option in the medium-term for the treatment
of medial compartment osteoarthritis of the knee but does not last
in the long-term. Cite this article:
