Abstract #3156
Highly accelerated sub-millimeter 3D T2 FLAIR based on deep learning and its application in robot-assist PBC for trigeminal neuralgia
Qiangqiang Liu1,2, Shuheng Zhang3, Jiwen Xu1,4, Jiachen Zhu3, Yiwen Shen5, Changquan Wang2, Wenzhe Chen2, Jun Yang3, and Jianmin Yuan6
1Department of Neurosurgery, Clinical Neuroscience Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, Shanghai, China, 3United Imaging Healthcare, Shanghai, China, 4Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 5Department of Radiology, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 6Central Research Institute, United Imaging Healthcare, Shanghai, China
Synopsis
With 3D T2 FLAIR imaging, trigeminal nerve is clearly demonstrated with CSF nulled, while low SNR and low spatial resolution is always the limitation. In this study, we introduced a 0.75mm isotropic resolution whole brain 3D T2 FLAIR imaging in 5min 40sec based on a novel deep learning framework, and evaluated on a small patient cohort who underwent MR-guided robot-assist percutaneous balloon compression (PBC). To our knowledge, this is the first clinical report of MR-guided robot-assist PBC surgery based on DL accelerated 3D scan.
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