POS0341 PERFORMANCE ANALYSIS OF A DEEP LEARNING ALGORITHM TO DETECT POSITIVE SIJ MRI ACCORDING TO THE ASAS DEFINITION IN AXSPA PATIENTS
Résumé
Background: Magnetic resonance imaging (MRI) of the sacroiliac joints (SIJ) is an essential tool in the evaluation of patients with axial spondyloarthritis (axSpA). In-depth knowledge of characteristic MRI lesions and their definitions, as well as reliability of identification and scoring, varies amongst general radiologists and rheumatologists.[1] A deep learning algorithm was developed to detect the presence of inflammation in SIJ MRI (MRI+) scans with promising results.[2]
Objectives: The aim of this diagnostic performance study was to assess the ability of a deep learning algorithm to identify MRI+ scans in a study cohort of axSpA patients.