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Abstract #3187

Real-time Reconstruction for Accelerated MR Thermometry Using CRNN in MRgLITT Treatment

Ziyi Pan1, Jieying Zhang1, Kai Zhang2, Hao Sun3, Meng Han3, Yawei Kuang3, Jiaqi Dou1, Wenbo Liu3, and Hua Guo1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3Sinovation Medical, Beijing, China


MRI-guided laser-interstitial thermal therapy (MRgLITT) is a minimally invasive therapeutic method in neurosurgery. Accelerating the data acquisition of thermometry for MRgLITT treatment is crucial in achieving high temporal-spatial resolution and large volume coverage. In this work, we suggest using the convolutional recurrent neural network (CRNN) to achieve real-time reconstruction for accelerated temperature mapping, because CRNN is capable of utilizing the temporal correlations of dynamic data to resolve aliasing artifacts. Results demonstrate that 6-fold acceleration can be achieved in MRgLITT treatment using CRNN with clinically acceptable reconstruction time and temperature measurement errors.

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