Artificial intelligence-based detection of paediatric appendicular skeletal fractures: performance and limitations for common fracture types and locations.

Background: Research into artificial intelligence (AI)-based fracture detection in children is scarce and has disregarded the detection of indirect fracture signs and dislocations.

Objective: To assess the diagnostic accuracy of an existing AI-tool for the detection of fractures, indirect fracture signs, and dislocations.

Materials And Methods: An AI software, BoneView (Gleamer, Paris, France), was assessed for diagnostic accuracy of fracture detection using paediatric radiology consensus diagnoses as reference.

Lesions with unclear malignant potential (B3) after minimally invasive breast biopsy: evaluation of vacuum biopsies performed in Switzerland and recommended further management.

Background: Histopathological B3 lesions after minimal invasive breast biopsy (VABB) are a particular challenge for the clinician, as there are currently no binding recommendations regarding the subsequent procedure.

Purpose: To analyze all B3 lesions, diagnosed at VABB and captured in the national central Swiss MIBB database and to provide a data basis for further management in this subgroup of patients.

Material And Methods: All 9,153 stereotactically, sonographically, or magnetic resonance imaging (MRI)-guided vacuum-assisted breast biopsies, performed in Switzerland between 2009 and 2011, captured in a central database, were evaluated.