Complete resection of tumor tissue remains one of the most important factors for survival in patients with cancer. Surgical removal is the most common front-line cancer therapy. Tumor resection in the brain is exceptionally difficult because leaving residual tumor tissue leads to decreased survival and removing normal healthy brain tissue leads to life-long neurological deficits. Brain surgery requires a very high degree of dexterity, accurate navigation, and niicro-precision cutting over long durations;thus it is an idel candidate for robotically assisted surgery. However, tumor resection is compounded by the need to make a small opening (keyhole) in the skull, and the difficulty of distinguishing normal from diseased tissue in an intraoperative setting. A minimally-invasive robotic system that allows surgeons to directly visualize and accurately discriminate neoplastic (cancer) from non-neoplastic tissue in a real-time intra-operative setting is currently not available, but an ideal gal for NRI. We propose to overcome two major limitations affecting robotically-assisted surgery in a team approach: inability to (1) automatically and (2) optically guide treatments in a miriimally-invasive intraoperative environment with advanced photonics and new cancer biomarkers. Dr. Hannaford will lead the integration of the RAVEN II open hardware and softvvare robotic system with laser-based endoscopic imaging. A single robot arm will hold a standard surgical tool for resecting/removing tumor, and a novel scanning fluorescence and reflectance imaging system to provide the advanced photonics in an ultra-small size. A team of three research neurosurgeons (Drs. Olson, Ellenbogen, Sekhar) will help develop clinically relevant phantoms and biological models of future image-guided brain surgery. PI, Dr. Seibel will provide a new multi-modal scanning fiber endoscope (mmSFE) technology that allows advanced laser imaging, diagnostic, and therapeutic biophotonics approaches to intra-operative keyhole surgery for improved performance and safety.

Public Health Relevance

Minimally-invasive, advanced biomedical imaging is required to distinguish between healthy and cancerous brain tissue during a keyhole robotic surgical procedure. This research project develops new fluorescence cancer imaging techniques and effective robot-assisted surgical procedures for enhancing cancer treatment which encourages multidisciplinary engineering graduate study with three participating neurosurgeons.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01EB016457-03
Application #
8717419
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Krosnick, Steven
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
City
Seattle
State
WA
Country
United States
Zip Code
98195
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McVeigh, Patrick Z; Sacho, Raphael; Weersink, Robert A et al. (2014) High-resolution angioscopic imaging during endovascular neurosurgery. Neurosurgery 75:171-80; discussion 179-80
Yang, Chenying; Hou, Vivian; Nelson, Leonard Y et al. (2013) Mitigating fluorescence spectral overlap in wide-field endoscopic imaging. J Biomed Opt 18:86012