Objectives: The aim of this study was to investigate the impact of a novel edge enhancement and iterative denoising algorithm in 1.5-T T1-weighted dynamic contrast-enhanced (DCE) gradient echo (GRE) magnetic resonance imaging of the abdomen on image quality, noise levels, diagnostic confidence, and lesion detectability.
Materials and methods: Fifty patients who underwent a clinically indicated magnetic resonance imaging with DCE imaging of the abdomen between June and August 2020 were included in this retrospective, monocentric, institutional review board-approved study. For DCE imaging, a series of 3 volume interpolated breath-hold examinations (VIBEs) was performed. The raw data of all DCE imaging studies were processed twice, once using standard reconstruction (DCES) and again using an edge enhancement and iterative denoising approach (DCEDE). All imaging studies were randomly reviewed by 2 radiologists independently regarding noise levels, arterial contrast, sharpness of vessels, overall image quality, and diagnostic confidence using a Likert scale ranging from 1 to 4, with 4 being the best. Furthermore, lesion detectability was evaluated using the same ranking system.
Results: All 50 imaging studies were successfully reconstructed with both methods. Interreader agreement (Cohen κ) was substantial to perfect for both readers. Arterial contrast and sharpness of vessels were rated superior by both readers with a median of 4 in DCEDE versus a median of 3 in DCES (P < 0.001). Furthermore, noise levels as well as overall image quality were rated higher with a median of 4 in DCEDE compared with a median of 3 in DCES (P < 0.001). Lesion detectability was evaluated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001). Consequently, diagnostic confidence was also rated to be superior in DCEDE with a median of 4 versus DCES with a median of 3 (P < 0.001).
Conclusions: Iterative denoising and edge enhancement are feasible in DCE imaging of the abdomen providing superior arterial contrast, noise levels, and overall image quality. Furthermore, lesion detectability and diagnostic confidence were significantly improved using this novel reconstruction method. Further reduction of acquisition time might be possible via reduction of increased noise levels using this presented method.
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