Feasibility of High-Resolution SSFSE MR imaging using Deep Learning Reconstruction in Assessment of Ovarian Volume and Follicle Count

Motivation: Transvaginal ultrasonography (TVUS) often underestimates follicle count (FC) compared to MRI. The repeatability of FC and ovarian volume (OV) assessment was still affected by motion artifact on conventional T2-weighted fast spin echo images. Goal(s): To propose a more reliable MRI technique in assessing the FC and OV. Approach: High-resolution single-shot fast spin echo (SSFSE) sequence was used to accelerate the acquisition speed, and AIRTM Recon DL was used to compensate for noise in this study. Results: Contributing to the improved time resolution and reduced noise, SSFSE-DL demonstrated better repeatability in FC and OV assessment compared to the widely used motion-robust PROPELLER technique. Impact: High-resolution SSFSE sequence with DL reconstruction can be a reliable imaging method in the assessment of ovarian morphology. It has a potential in determining the threshold value of FC for PCOM identification in future studies.