The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%).Aims
Methods
Paediatric triplane fractures and adult trimalleolar ankle fractures both arise from a supination external rotation injury. By relating the experience of adult to paediatric fractures, clarification has been sought on the sequence of injury, ligament involvement, and fracture pattern of triplane fractures. This study explores the similarities between triplane and trimalleolar fractures for each stage of the Lauge-Hansen classification, with the aim of aiding reduction and fixation techniques. Imaging data of 83 paediatric patients with triplane fractures and 100 adult patients with trimalleolar fractures were collected, and their fracture morphology was compared using fracture maps. Visual fracture maps were assessed, classified, and compared with each other, to establish the progression of injury according to the Lauge-Hansen classification.Aims
Methods
Proper preoperative planning benefits fracture reduction, fixation, and stability in tibial plateau fracture surgery. We developed and clinically implemented a novel workflow for 3D surgical planning including patient-specific drilling guides in tibial plateau fracture surgery. A prospective feasibility study was performed in which consecutive tibial plateau fracture patients were treated with 3D surgical planning, including patient-specific drilling guides applied to standard off-the-shelf plates. A postoperative CT scan was obtained to assess whether the screw directions, screw lengths, and plate position were performed according the preoperative planning. Quality of the fracture reduction was assessed by measuring residual intra-articular incongruence (maximum gap and step-off) and compared to a historical matched control group.Aims
Methods
Triplane ankle fractures are complex injuries typically occurring in children aged between 12 and 15 years. Classic teaching that closure of the physis dictates the overall fracture pattern, based on studies in the 1960s, has not been challenged. The aim of this paper is to analyze whether these injuries correlate with the advancing closure of the physis with age. A fracture mapping study was performed in 83 paediatric patients with a triplane ankle fracture treated in three trauma centres between January 2010 and June 2020. Patients aged younger than 18 years who had CT scans available were included. An independent Paediatric Orthopaedic Trauma Surgeon assessed all CT scans and classified the injuries as n-part triplane fractures. Qualitative analysis of the fracture pattern was performed using the modified Cole fracture mapping technique. The maps were assessed for both patterns and correlation with the closing of the physis until consensus was reached by a panel of six surgeons.Aims
Methods
The aim of this study was to investigate the association between fracture displacement and survivorship of the native hip joint without conversion to a total hip arthroplasty (THA), and to determine predictors for conversion to THA in patients treated nonoperatively for acetabular fractures. A multicentre cross-sectional study was performed in 170 patients who were treated nonoperatively for an acetabular fracture in three level 1 trauma centres. Using the post-injury diagnostic CT scan, the maximum gap and step-off values in the weightbearing dome were digitally measured by two trauma surgeons. Native hip survival was reported using Kaplan-Meier curves. Predictors for conversion to THA were determined using Cox regression analysis.Aims
Methods
To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration).Aims
Methods
This study aimed to answer the following questions: do 3D-printed models lead to a more accurate recognition of the pattern of complex fractures of the elbow?; do 3D-printed models lead to a more reliable recognition of the pattern of these injuries?; and do junior surgeons benefit more from 3D-printed models than senior surgeons? A total of 15 orthopaedic trauma surgeons (seven juniors, eight seniors) evaluated 20 complex elbow fractures for their overall pattern (i.e. varus posterior medial rotational injury, terrible triad injury, radial head fracture with posterolateral dislocation, anterior (trans-)olecranon fracture-dislocation, posterior (trans-)olecranon fracture-dislocation) and their specific characteristics. First, fractures were assessed based on radiographs and 2D and 3D CT scans; and in a subsequent round, one month later, with additional 3D-printed models. Diagnostic accuracy (acc) and inter-surgeon reliability (κ) were determined for each assessment.Aims
Methods
Artificial intelligence (AI) is, in essence, the concept of ‘computer thinking’, encompassing methods that train computers to perform and learn from executing certain tasks, called machine learning, and methods to build intricate computer models that both learn and adapt, called complex neural networks. Computer vision is a function of AI by which machine learning and complex neural networks can be applied to enable computers to capture, analyze, and interpret information from clinical images and visual inputs. This annotation summarizes key considerations and future perspectives concerning computer vision, questioning the need for this technology (the ‘why’), the current applications (the ‘what’), and the approach to unlocking its full potential (the ‘how’). Cite this article:
The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs? The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS).Aims
Methods
A comprehensive study of osteology remains a cornerstone of current orthopaedic and traumatological education. Osteology was already established as an important part of surgical education by the 16th century. In order to teach anatomy and osteology, the corpses of executed criminals were dissected by the
