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Abstract #4292

Gadolinium-free Contrast-enhanced MRI (GFCE-MRI) Synthesis via Generalizable MHDgN-Net for Patients with Nasopharyngeal Carcinoma

Wen Li1, Saikit Lam1, Haonan Xiao1, Tian Li1, Ge Ren1, Shaohua Zhi1, Xinzhi Teng1, Chenyang Liu1, Jiang Zhang1, Francis Kar-ho Lee2, Kwok-hung Au2, Victor Ho-fun Lee3, Amy Tien Yee Chang4, and Jing Cai1
1The Hong Kong Polytechnic University, HONG KONG, Hong Kong, 2Queen Elizabeth Hospital, HONG KONG, Hong Kong, 3The University of Hong Kong, HONG KONG, Hong Kong, 4Hong Kong Sanatorium & Hospital, HONG KONG, Hong Kong


We have developed and validated a MHDgN-Net for gadolinium-free contrast-enhanced MRI (GFCE-MRI) synthesis in patients with nasopharyngeal carcinoma (NPC). The developed MHDgN-Net was featured with high generalizability. We first modelled the MHDgN-Net using three hospital datasets to improve the diversity of training samples. Then, the external hospital data was matched to the distribution of training dataset by EDM. Compared to traditional models, the proposed MHDgN-Net can accurately enhance tumor and significantly improve the quality of GFCE-MRI when applying to external hospital data. This technique holds great potential in providing a generalizable gadolinium-free tumor enhancement alternative on data from other hospitals.

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