Utility of accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction in female pelvic MRI: a multi-reader study.

OBJECTIVES: To determine the clinical feasibility of T2-weighted turbo spin-echo (T2-TSE) imaging with deep learning reconstruction (DLR) in female pelvic MRI compared with conventional T2 TSE in terms of image quality and scan time.

METHODS: Between May 2021 and September 2021, 52 women (mean age, 44 years ± 12) who underwent 3-T pelvic MRI with additional T2-TSE using a DLR algorithm were included in this single-center prospective study with patient's informed consents. Conventional, DLR, and DLR T2-TSE images with reduced scan times were independently assessed and compared by four radiologists. The overall image quality, differentiation of anatomic details, lesion conspicuity, and artifacts were evaluated using a 5-point scale. Inter-observer agreement of the qualitative scores was compared and reader protocol preferences were then evaluated.

RESULTS: In the qualitative analysis of all readers, fast DLR T2-TSE showed significantly better overall image quality, differentiation of anatomic regions, lesion conspicuity, and lesser artifacts than conventional T2-TSE and DLR T2-TSE, despite approximately 50% reduction in scan time (all p < 0.05). The inter-reader agreement for the qualitative analysis was moderate to good. All readers preferred DLR over conventional T2-TSE regardless of scan time and preferred fast DLR T2-TSE (57.7-78.8%), except for one who preferred DLR over fast DLR T2-TSE (53.8% vs. 46.1%).

CONCLUSION: In female pelvic MRI, image quality and accelerated image acquisition for T2-TSE can be significantly improved by using DLR compared to conventional T2-TSE. Fast DLR T2-TSE was non-inferior to DLR T2-TSE in terms of reader preference and image quality.

CLINICAL RELEVANCE STATEMENT: DLR of T2-TSE in female pelvic MRI enables fast imaging along with maintaining optimal image quality compared with parallel imaging-based conventional T2-TSE.

KEY POINTS: • Conventional T2 turbo spin-echo based on parallel imaging has limitations for accelerated image acquisition while maintaining good image quality. • Deep learning image reconstruction showed better image quality in both images obtained using the same or accelerated image acquisition parameters compared with conventional T2 turbo spin-echo in female pelvic MRI. • Deep learning image reconstruction enables accelerated image acquisition while maintaining good image quality in the T2-TSE of female pelvic MRI.