AGREEMENT AND SENSITIVITY TO BETWEEN-GROUP DIFFERENCES OF U-NET-BASED, AUTOMATED CARTILAGE T2 ANALYSES FROM MULTI-ECHO SPIN ECHO MRI - DATA FROM THE OA-BIO PROJECT

Abstract

Purpose: Previous studies reported a high agreement for cartilage segmentations from high resolution 3D gradient echo MRIs using deep learning techniques when compared to manual cartilage segmentations with Dice similarity coefficients (DSC) of up to ∼0.90 (scale: 0.0 to 1.0). Only few studies applied deep learning techniques to multi-echo spin echo (MESE) MRIs for analysis of cartilage T2 relaxation time, an imaging biomarker sensitive to alterations in cartilage composition. These reported a somewhat lower agreement compared to manual segmentations with DSCs of up to 0.75.