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Abstract #3177

Self-supervised Liver  T1rho ¬†Mapping with Physics-constrained Regularization

Chaoxing Huang1, Yurui Qian1, Jian Hou1, Baiyan Jiang1,2, Queenie Chan3, Vincent Wong4, Winnie Chu1, and Weitian Chen1
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong, 2Illuminatio Medical Technology Limited, Hong Kong, China, 3Philips Healthcare, Hong Kong, China, 4Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong


Quantification of liver T1rho has gained interest in liver pathological study. Traditional fitting method requires acquisition of multiple T1rho-weighted images and it can be affected by respiratory motion. We propose a physics-informed self-supervised mapping method by taking only one T1rho-weighted image to do the mapping. Our preliminary experimental results show that our method has the potential to outperform the traditional multi-TSL acquisition method, particularly in the scenario of free-breathing MRI scan.

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