Generating Contrast-Enhanced Liver MRI Images from Native Sequences

• Published in: Current directions in biomedical engineering Vol. 10; no. 1; pp. 33 - 36
• Main Authors: Hürtgen, Janine, Hille, Georg, Saalfeld, Sylvia, Kreher, Robert, Hensen, Bennet, Wacker, Frank, Rose, Georg, Ringe, Kristina I.
• Format: Journal Article
• Language: English
• Published: De Gruyter 01.09.2024
• Subjects: Contrast-enhanced MRI; Image-to-Image Translation; Liver; Medical Image Synthesis; ResViT
• ISSN: 2364-5504
• DOI: 10.1515/cdbme-2024-0109

Generating synthetic contrast-enhanced liver MRI scans from native MRI images can serve to mitigate the issue of sparse contrast-enhanced image datasets while concurrently circumventing the time-consuming and costly process of administering contrast agents during image acquisition. In this study, we conducted three experiments using paired image-to-image translation techniques. Native T1 sequences showing the abdominal liver region served as the input, while contrast-enhanced T1 sequences were the target. The data preprocessing methods and image boundaries were varied for the individual experiments in addition to the implementation of a 5-fold cross-validation for the top-performing approach. Focusing on liver regions achieved the best results with a mean absolute error (MAE) of 0.0837 ± 0.0068, a mean squared error (MSE) of 0.0128 ± 0.0023 and a peak signal-to-noise ratio (PSNR) of 18.99 ± 0.81 dB. Our findings serve as a proof-of-concept, demonstrating the feasibility of generating contrast-enhanced MRI images. However, the current state necessitates further enhancements for effectively addressing the challenge posed by limited dataset sizes with difficult anatomical circumstances as well as MR imaging-related heterogenous tissue contrasts.