The aim of this study was to create artificial intelligence (AI) software with the purpose of providing a second opinion to physicians to support distal radius fracture (DRF) detection, and to compare the accuracy of fracture detection of physicians with and without software support. The dataset consisted of 26,121 anonymized anterior-posterior (AP) and lateral standard view radiographs of the wrist, with and without DRF. The convolutional neural network (CNN) model was trained to detect the presence of a DRF by comparing the radiographs containing a fracture to the inconspicuous ones. A total of 11 physicians (six surgeons in training and five hand surgeons) assessed 200 pairs of randomly selected digital radiographs of the wrist (AP and lateral) for the presence of a DRF. The same images were first evaluated without, and then with, the support of the CNN model, and the diagnostic accuracy of the two methods was compared.Aims
Methods
Traumatic brachial plexus injury causes severe functional impairment
of the arm. Elbow flexion is often affected. Nerve surgery or tendon
transfers provide the only means to obtain improved elbow flexion.
Unfortunately, the functionality of the arm often remains insufficient.
Stem cell therapy could potentially improve muscle strength and
avoid muscle-tendon transfer. This pilot study assesses the safety
and regenerative potential of autologous bone marrow-derived mononuclear
cell injection in partially denervated biceps. Nine brachial plexus patients with insufficient elbow flexion
(i.e., partial denervation) received intramuscular escalating doses
of autologous bone marrow-derived mononuclear cells, combined with
tendon transfers. Effect parameters included biceps biopsies, motor
unit analysis on needle electromyography and computerised muscle tomography,
before and after cell therapy.Objectives
Methods
