Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning: A Prospective Study.

OBJECTIVE

The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T2-w FSE Dixon sequence (T2) for breast magnetic resonance imaging (MRI).

MATERIALS AND METHODS

This prospective study was conducted between November 2022 and April 2023 using a 3T scanner. Both T2 and T2 sequences were acquired for each patient. Quantitative analysis was based on region-of-interest (ROI) measurements of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed independently by two radiologists using Likert scales to evaluate various image quality features, morphology, and diagnostic confidence for cysts and breast cancers. Reader preference between T2 and T2 was assessed via side-by-side comparison, and inter-reader reliability was also analyzed.

RESULTS

Total of 151 women were enrolled, with 140 women (mean age: 52 ± 14 years; 85 cysts and 31 breast cancers) included in the final analysis. The acquisition time was 110 s ± 0 for T2 compared to 266 s ± 0 for T2. SNR and CNR were significantly higher in T2 ( < 0.001). T2 was associated with higher image quality scores, reduced noise, and fewer artifacts ( < 0.001). All evaluated anatomical regions (breast and axilla), breast implants, and bone margins were rated higher in T2 ( ≤ 0.008), except for bone marrow, which scored higher in T2 ( < 0.001). Scores for conspicuity, sharpness/margins, and microstructure of cysts and breast cancers were higher in T2 ( ≤ 0.002). Diagnostic confidence for cysts was improved with T2 ( < 0.001). Readers significantly preferred T2 over T2 in side-by-side comparisons ( < 0.001).

CONCLUSION

T2 effectively corrected for SNR loss caused by accelerated image acquisition and provided a 58% reduction in acquisition time compared to T2. This led to fewer artifacts and improved overall image quality. Thus, T2 is feasible and has the potential to replace conventional T2-w sequences for breast MRI examinations.