Thin-Slice Prostate MRI Enabled by Deep Learning Image Reconstruction

Thin-slice prostate MRI might be beneficial for prostate cancer diagnostics. However, prolongation of acquisition time is a major drawback of thin-slice imaging. Therefore, the purpose of this study was to investigate the impact of a thin-slice deep learning accelerated T2-weighted (w) TSE imaging sequence (T2_DLR) of the prostate as compared to conventional T2w TSE imaging (T2_S).

Thirty patients were included in this prospective study at one university center after obtaining written informed consent. T2_S (3 mm slice thickness) was acquired first in three orthogonal planes followed by thin-slice T2_DLR (2 mm slice thickness) in axial plane. Acquisition time of axial conventional T2_S was 4:12 min compared to 4:37 min for T2_DLR. Imaging datasets were evaluated by two radiologists using a Likert-scale ranging from 1-4, with 4 being the best regarding the following parameters: sharpness, lesion detectability, artifacts, overall image quality, and diagnostic confidence. Furthermore, preference of T2_S versus T2_DLR was evaluated.

The mean patient age was 68 ± 8 years. Sharpness of images and lesion detectability were rated better in T2_DLR with a median of 4 versus a median of 3 in T2_S (p < 0.001 for both readers). Image noise was evaluated to be significantly worse in T2_DLR as compared to T2_S (p < 0.001 and p = 0.021, respectively). Overall image quality was also evaluated to be superior in T2_DLR versus T2_S with a median of 4 versus 3 (p < 0.001 for both readers). Both readers chose T2_DLR in 29 cases as their preference.

Thin-slice T2_DLR of the prostate provides a significant improvement of image quality without significant prolongation of acquisition time.