LAVA HyperSense and deep-learning reconstruction for near-isotropic (3D) enhanced magnetic resonance enterography in patients with Crohn’s disease: utility in noise reduction and image quality improvement
Jung Hee Son, Yedaun Lee, Ho‐Joon Lee, Joonsung Lee, Hyun-Woong Kim, R. Marc Lebel
Abstract
PURPOSE: This study aimed to compare near-isotropic contrast-enhanced T1-weighted (CE-T1W) magnetic resonance enterography (MRE) images reconstructed with vendor-supplied deep-learning reconstruction (DLR) with those reconstructed conventionally in terms of image quality. METHODS: Recon DL 3D (DLR), which were then reformatted into the axial plane to generate six image sets per patient. Two radiologists independently assessed the images for overall image quality, contrast, sharpness, presence of motion artifacts, blurring, and synthetic appearance for qualitative analysis, and the signal-to-noise ratio (SNR) was measured for quantitative analysis. RESULTS: < 0.001). CONCLUSION: Using DLR for near-isotropic CE-T1W MRE improved the image quality and increased the SNR.