Deep Learning-Enhanced Diffusion-Weighted Imaging of the Abdomen at 0.55 T: Image Quality and Apparent Diffusion...

Low-field diffusion-weighted imaging (DWI) is limited by inherently lower signal-to-noise ratios. This study evaluated the technical feasibility, image quality, and apparent diffusion coefficient (ADC) reliability of deep learning (DL)-enhanced DWI at low field strength.

Thirty-three healthy volunteers (mean age: 30 ± 4 years; 13 men) underwent 0.55 T abdominal magnetic resonance imaging from 07/2024-09/2024. Conventional and DL-enhanced DWI were acquired with two b values (b50 s/mm², b800 s/mm²). Three fellowship-trained abdominal radiologists rated the scans for quality parameters and artifacts (Likert scales, 1-5). Quantitative b50 and b800 signal intensity and ADC values were measured in the right and left liver lobes, spleen and Th12 vertebral body by one reader. Interreader reliability, intermethod concordance, and Bland-Altman analyses were performed.

DL-enhanced scans demonstrated higher quality across all diffusion weightings (all: P < .001): b50 images (median: 4 [IQR: 4-5] vs 3 [3-4]), b800 images (4 [4-4] vs 3 [3-3]), and ADC maps (4 [4-4] vs 3 [3-3]) with good or better interreader agreement (κ ≥ 0.63). Image noise, spatial resolution, organ sharpness and artifacts were rated better for DL-enhanced DWI (all: P < .001). Mean b50 and b800 signal intensities were lower with DL reconstruction (all: P < .001). ADC values showed at least strong intermethod correlation (r ≥ 0.61; all: P < .001) with mean differences of 0.3%-4.5% in normal tissues. Bland-Altman plots and interchangeability analysis confirmed intermethod ADC value deviations within expected margins of ±20% (all: P < .001).

DL superresolution reconstruction enables faster and higher quality abdominal DWI at 0.55 T without relevant ADC deviations, supporting interchangeability with conventional DWI.