EE Seminar: Robust registration between high-field preoperative and low-field intraoperative brain MRI

~~Speaker: Ori Weber
M.Sc. student under the supervision of Prof. Nahum Kiryati

Wednesday, February 24th, 2016 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering

Robust registration between high-field preoperative and low-field intraoperative brain MRI

Abstract

Preoperative high-resolution brain MRI is commonly used to produce high quality anatomical MRI as well as diffusion tensor imaging trachtography and functional MRI. While preoperative high-resolution MRI is very useful for lesion detection and surgery planning, it has only a limited validity as an anatomical reference for navigation during open brain surgery. When the skull is opened (craniotomy), at the beginning of surgery, cerebrospinal fluid leaks out, causing the brain to drift progressively with regard to the skull. As surgery progresses, local deformations caused by ongoing tissue resection further increase the discrepancy between preoperative MRI and the actual brain anatomy.

During the last decade, low-field (.15T) intraoperative MRI (iMRI) has been developed to provide updated MRI images during brain surgery, thereby providing real-time images of the brain for improved navigation. While low-field intraoperative MRI provides some degree of anatomical guidance during surgery, it cannot replicate the functionality, in terms of resolution, signal-to-noise, field-of-view and the ability of diagnostic systems to provide fMRI and DTI information. Therefore, the ability to quickly map information obtained from the preoperative images directly to the intraoperative environment, while taking into account brain-shift and tissue resection, would provide significant improvement in image quality, leading to higher accuracy of navigation during surgery.

This thesis proposes a robust, automatic and real-time framework of coupling high-field preoperative and low-field intraoperative MRI, and projecting preoperatively acquired fMRI and tractography maps during the ongoing surgery. In the proposed method, open brain surgery is analyzed as a succession of three consecutive phases: pre-craniotomy, post-craniotomy and post-resection. Each phase has a tailor-made pipeline which explicitly takes into account its respective challenge: the limited intraoperative MRI field-of-view, the brain-shift effect, and the extracted brain tissues following resection. Quantitative validation results are presented on a set of 20 real interventional cases.