Abstract #3985

Contrast-enhanced Cardiac MRI Generation Using Contrast-free Cardiac Cine MRI

Puguang Xie¹, Zhongsen Li², Wei Chen³, Yu Ma¹, and Jingjing Xiao⁴

¹Chongqing Emergency Medical Centre, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China, ²Center for Biomdical Imaging Research, Tsinghua University, Beijing, China, Beijing, China, ³MR Research Collaboration Team, Siemens Healthineers Ltd., Guangzhou, China, ⁴Bio-Med Informatics Research Centre \& Clinical Research Centre, Xinqiao Hospital, Army Medical University, Chongqing, China

Synopsis

Keywords: AI Diffusion Models, Diffusion Modeling

Motivation: Generating late gadolinium enhancement (LGE) images from contrast-free cardiac magnetic resonance (CMR) images is crucial for patients with severe renal failure or contrast agent allergies.

Goal(s): This study aims to develop a method that can generate LGE images from cine images based on diffusion models.

Approach: We introduced a novel multi-task diffusion model that generates LGE images from contrast-free cine images and evaluate the probability of enhancement presence in LGE images based on cine images.

Results: In external validation, Cine2LGE generates LGE images with good consistency compared to actual LGE images, exhibiting fewer artifacts and improved contrast.

Impact: We demonstrate the potential of diffusion models in generating LGE using contrast-free cine images. The proposed method is expected to provide a valuable alternative for patients who cannot obtain LGE images due to contraindications.

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