Abstract #5034

AI-based mapping from MRI to MR thermometry for MR-guided laser interstitial thermal therapy using a conditional generative adversarial network

Saba Sadatamin^1,2, Steven Robbins³, Richard Tyc³, Adam C. Waspe^2,4, Lueder A. Kahrs^1,5,6,7, and James M. Drake^1,2,8

¹Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada, ²Posluns Centre for Image Guided Innovation & Therapeutic Intervention, Hospital of Sick Children, Toronto, ON, Canada, ³Monteris Medical, Winnipeg, MB, Canada, ⁴Department of Medical Imaging, University of Toronto, Toronto, ON, Canada, ⁵Medical Computer Vision and Robotics Lab, University of Toronto, Toronto, ON, Canada, ⁶Department of Mathematical & Computational Sciences, University of Toronto Mississauga, Toronto, ON, Canada, ⁷Department of Computer Science, University of Toronto, Toronto, ON, Canada, ⁸Department of Surgery, University of Toronto, Toronto, ON, Canada

Synopsis

Keywords: Machine Learning/Artificial Intelligence, MR-Guided Interventions, Laser Interstitial Thermal TherapyMR-guided laser interstitial thermal therapy (MRgLITT) is a minimally-invasive treatment for brain tumors where a surgeon inserts a laser fiber along a fixed trajectory. Repositioning the laser is invasive and predicting thermal spread close to heat sinks is difficult. To address this problem, MR thermometry prediction using artificial intelligence (AI) modeling will be developed to aid the surgeon to determine whether a selected laser position is ideal before the treatment starts. AI algorithms will be trained to model the nonlinear mapping from anatomical MRI planning images to MR thermometry. A surgeon will choose a better fiber trajectory by AI model.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.