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Abstract #2143

Acquiring and Reconstructing UTE-Dixon Fat and Water Images for Generation of Synthetic CT in Thorax on an MR-Linac

Rosie Goodburn1, Wajiha Bano1, Uwe Oelfke1, and Andreas Wetscherek1
1Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom


Generation of synthetic CT (synCT) for adaptive MR-guided radiotherapy is particularly challenging in the thorax due to the impact of respiratory motion, short-T2* tissues in lung, and a complex tissue-density structure. To address these challenges and provide data suitable for generating thoracic synCTs, we developed a UTE-Dixon sequence with a golden-angle stack-of-stars trajectory. We have demonstrated successful online acquisition and offline reconstruction of UTE, fat, water and B0 images as well as retrospective respiratory gating. Work is ongoing to optimize processing of respiratory-resolution of UTE and Dixon images that will form the input to synCT in thorax on an MR-Linac.

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