Abstract

To determine the impact on acquisition time reduction and image quality of a deep learning (DL) reconstruction for accelerated diffusion-weighted imaging (DWI) of the pelvis at 1.5 Tcompared to standard DWI. A total of 55 patients (mean age, 61±13 years; range, 27-89; 20 men, 35 women) were consecutively included in this retrospective, monocentric study between February and November 2022. Inclusion criteria were (1) standard DWI (DWIS) in clinically indicated magnetic resonance imaging (MRI) at 1.5 Tand (2) DL-reconstructed DWI (DWIDL). All patients were examined using the institution's standard MRI protocol according to their diagnosis including DWI with two different b-values (0and 800s/mm2) and calculation of apparent diffusion coefficient (ADC) maps. Image quality was qualitatively assessed by four radiologists using a visual 5-point Likert scale (5= best) for the following criteria: overall image quality, noise level, extent of artifacts, sharpness, and diagnostic confidence. The qualitative scores for DWIS and DWIDL were compared with the Wilcoxon signed-rank test. The overall image quality was evaluated to be significantly superior in DWIDL compared to DWIS for b =0s/mm2, b =800s/mm2, and ADC maps by all readers (P<.05). The extent of noise was evaluated to be significantly less in DWIDL compared to DWIS for b =0s/mm2, b=800s/mm2, and ADC maps by all readers (P<.001). No significant differences were found regarding artifacts, lesion detectability, sharpness of organs, and diagnostic confidence (P>.05). Acquisition time for DWIS was 2:06minutes, and simulated acquisition time for DWIDL was 1:12minutes. DL image reconstruction improves image quality, and simulation results suggest that a reduction in acquisition time for diffusion-weighted MRI of the pelvis at 1.5 Tis possible.

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