Performance Analysis of a Deep Learning Algorithm to Detect MRI Positive Sacroiliac Joints in Patients with Axial Spondyloarthritis According to the Assessment of SpondyloArthritis international Society 2009 Definition
Résumé
Objectives: To assess the ability of a previously trained deep learning algorithm to identify magnetic resonance imaging positive (MRI+) scans of the sacroiliac joints (SIJ) in a large external validation set of patients with axial spondylarthritis (axSpA).
Methods: Baseline SIJ MRI scans were collected from two prospective randomised controlled trials in patients with non-radiographic (nr-) and radiographic (r-) axSpA (NCT01087762 and NCT02505542) and were centrally evaluated by two expert readers (and adjudicator in case of disagreement) for the presence of inflammation by the 2009 Assessment in SpondyloArthritis international Society (ASAS) definition. Scans were processed by the deep learning algorithm, blinded to clinical information and central expert readings.