Given the possible radiation damage and inaccuracy of radiological investigations, particularly in children, ultrasound and superb microvascular imaging (SMI) may offer alternative methods of evaluating new bone formation when limb lengthening is undertaken in paediatric patients. The aim of this study was to assess the use of ultrasound combined with SMI in monitoring new bone formation during limb lengthening in children. In this retrospective cohort study, ultrasound and radiograph examinations were performed every two weeks in 30 paediatric patients undergoing limb lengthening. Ultrasound was used to monitor new bone formation. The number of vertical vessels and the blood flow resistance index were compared with those from plain radiographs.Aims
Methods
The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application. In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Clinicians labelled each radiograph using a uniform standard method. Radiographs were grouped according to age and into ‘dislocation’ (dislocation and subluxation) and ‘non-dislocation’ (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis. The deep learning system was trained and optimized using 9,081 radiographs; 1,138 test radiographs were then used to compare the diagnoses made by deep learning system and clinicians. The accuracy of the deep learning system was determined using a receiver operating characteristic curve, and the consistency of acetabular index measurements was evaluated using Bland-Altman plots.Aims
Methods
