Abstract #0970

Real-Time T1/PRF-Based MR Thermometry Using Deep Learning and VFA-mFFE for Guidance of HIFU Treatment

Jong-Min Kim^1,2,3, You-Jin Jeong^1,2,3, Han-Jae Cheong^1,2,3, Jae-Won Yoo^1,2,3, Jeong-Hee Kim^2,4, Chulhyun Lee⁵, and Chang-Hyun Oh^1,2,3,6

¹Department of Electronics and Information, Korea University, Seoul, Korea, Republic of, ²Korea Artificial Organ Center, Korea University, Seoul, Korea, Republic of, ³ICT Convergence Technology for Health and Safety, Korea University, Sejong, Korea, Republic of, ⁴Research Institute for Advanced Industrial Technology, Korea University, Sejong, Korea, Republic of, ⁵Bioimaging Research Team, Korea Basic Science Institute, Chungcheongbuk-do, Korea, Republic of, ⁶Correspoding author, ohch@korea.ac.kr, Seoul, Korea, Republic of

MR temperature mapping of adipose and aqueous tissues is crucial in ensuring the safety and efficacy of HIFU treatment in regions of the body where the adipose and aqueous tissues are treated. We suggest a simultaneous and real-time temperature mapping method for adipose and aqueous tissues by using deep learning and multi-echo fast field echo with variable flip angle. Additionally, an image reconstruction method to obtain the temperature maps from the undersampled data obtained in the treatment stage is proposed by additionally using the high-resolution image obtained in the planning stage.

This abstract and the presentation materials are available to members only; a login is required.

Join Here