Clinical validation of fully automated cartilage transverse relaxation time (T2) and thickness analysis using quantitative DESS magnetic resonance imaging.

ABSTRACT:

Objective

To clinically validate a fully automated cartilage segmentation technique from quantitative double-echo steady-state (qDESS) MRI supporting simultaneous estimation of cartilage T2 and morphology. Here, we test whether laminar (superficial and deep layer) T2 results from convolutional neural network (CNN) segmentations are consistent with those from manual expert segmentations.

Materials and methods

The 3D qDESS sequence was acquired using 3 T MRI (resolution: 0.3125 × 0.3125x1.5 mm) in both knees of 37 subjects with unilateral anterior cruciate ligament (ACL) injury and 48 uninjured controls. Automated femorotibial cartilage (FTJ) segmentation was based on a 2D U-Net. Laminar T2 and cartilage thickness across the FTJ) were compared between ACL-injured and contralat

SUBMITTER: Wirth W 

PROVIDER: S-EPMC11914229 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature