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
The primary aim of this study was to address the hypothesis that fracture morphology might be more important than posterior malleolar fragment size in rotational type posterior malleolar ankle fractures (PMAFs). The secondary aim was to identify clinically important predictors of outcome for each respective PMAF-type, to challenge the current dogma that surgical decision-making should be based on fragment size. This observational prospective cohort study included 70 patients with operatively treated rotational type PMAFs, respectively: 23 Haraguchi Type I (large posterolateral-oblique), 22 Type II (two-part posterolateral and posteromedial), and 25 (avulsion-) Type III. There was no standardized protocol on how to address the PMAFs and CT-imaging was used to classify fracture morphology and quality of postoperative syndesmotic reduction. Quantitative 3D-CT (Q3DCT) was used to assess the quality of fracture reduction, respectively: the proportion of articular involvement; residual intra-articular: gap, step-off, and 3D-displacement; and residual gap and step-off at the fibular notch. These predictors were correlated with the Foot and Ankle Outcome Score (FAOS) at two-years follow-up.Aims
Methods
