Purpose: The use of computed tomography (CT) in fractures is time consuming, challenging and suffers from poor inter-surgeon reliability. Convolutional neural networks (CNNs), a subset of artificial intelligence (AI), may overcome shortcomings and reduce clinical burdens to detect and classify fractures. The aim of this review was to summarize literature on CNNs for the detection and classification of fractures on CT scans, focusing on its accuracy and to evaluate the beneficial role in daily practice. Methods: Literature search was performed according to the PRISMA statement, and Embase, Medline ALL, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar databases were searched. Studies were eligible when the use of AI for the detection of fractures on CT scans was described. Quality assessment was done with a modified version of the methodologic index for nonrandomized studies (MINORS), with a seven-item checklist. Performance of AI was defined as accuracy, F1-score and area under the curve (AUC). Results: Of the 1140 identified studies, 17 were included. Accuracy ranged from 69 to 99%, the F1-score ranged from 0.35 to 0.94 and the AUC, ranging from 0.77 to 0.95. Based on ten studies, CNN showed a similar or improved diagnostic accuracy in addition to clinical evaluation only. Conclusions: CNNs are applicable for the detection and classification fractures on CT scans. This can improve automated and clinician-aided diagnostics. Further research should focus on the additional value of CNN used for CT scans in daily clinics.

It is unclear whether it is safe to convert above-elbow cast (AEC) to below-elbow cast (BEC) in a child who has sustained a displaced diaphyseal both-bone forearm fracture that is stable after reduction. In this multicenter study, we wanted to answer the question: does early conversion to BEC cause similar forearm rotation to that after treatment with AEC alone? Children were randomly allocated to 6 weeks of AEC, or 3 weeks of AEC followed by 3 weeks of BEC. The primary outcome was limitation of pronation/supination after 6 months. The secondary outcomes were re-displacement of the fracture, limitation of flexion/extension of the wrist and elbow, complication rate, cast comfort, complaints in daily life, and cosmetics of the fractured arm. 62 children were treated with 6 weeks of AEC, and 65 children were treated with 3 weeks of AEC plus 3 weeks of BEC. The follow-up rate was 60/62 and 64/65, respectively with a mean time of 6.9 (4.7-13) months. The limitation of pronation/supination was similar in both groups (18 degrees for the AEC group and 11 degrees for the AEC/BEC group). The secondary outcomes were similar in both groups, with the exception of cast comfort, which was in favor of the AEC/BEC group. Early conversion to BEC cast is safe and results in greater cast comfort.