Deep learning-accelerated T2-weighted imaging of the prostate: Impact of further acceleration with lower spatial resolution on image quality.

Researchers

Journal

Modalities

Models

Abstract

To compare image quality in prostate MRI among standard T2-weighted imaging (T2-std), accelerated T2-weighted imaging (T2WI) with high resolution (T2-HR) and more accelerated T2WI with lower resolution (T2-LR) using both conventional reconstruction (C) and deep learning reconstruction (DL).In 46 consecutive patients, T2-std, T2-HR and T2-LR were acquired in 3:32 min, 1:06 min and 0.52 min, respectively. Both reconstruction techniques (C and DL) were applied to T2-HR and T2-LR. Five sets of images (T2-std, T2-HRC, T2-LRC, T2-HRDL, and T2-LRDL) for each patient were independently evaluated by two radiologists. Quantitative analysis including the signal-to-noise ratio (SNR) and contrast ratio (CR) and qualitative analysis with a 5-point scale for the sharpness of structures, ghosting or other artifacts, noise and overall image quality were performed.The SNR was not different in either the peripheral zone (PZ) or transition zone (TZ) between T2-LRDL and T2-std with the median value of 21.7 versus 22.6 in PZ and 16.5 versus 17.3 in TZ, respectively. The CR between the prostate gland and muscle was significantly lower on T2-HRC and T2-LRC than on T2-std. Most of the evaluated factors showed significantly lower scores on T2-HRC and T2-LRC than on T2-std. Although noise and overall image quality on T2-HRDL and other artifacts on T2-LRDL were rated significantly lower than on T2-std (median value 4.0 versus 4.5, P < 0.001; 4.5 versus 5.0, P = 0.001; 4.5 versus 5.0, P = 0.006, respectively), other factors did not differ between T2-std and T2-HRDL or T2-LRDL.DL is useful to improve image quality in accelerated T2WI of the prostate gland. Using DL, accelerated T2WI with lower spatial resolution than T2-std can be achieved with similar image quality in much shorter scan time (75.5% reduction in the acquisition time).Copyright © 2021 Elsevier B.V. All rights reserved.