The outcome of brain tumor surgery is critically dependent on the neurosurgeon's ability to distinguish between abnormal and normal tissue in real-time. Our goal is to enhance this discrimination by using label-free Fluorescence Lifetime Imaging (FLIm) to detect tissue biochemical and metabolic characteristics that distinguish among different tissue types. We are integrating FLIm into the neurosurgical workflow to provide real-time information in a visual format that is useful for guiding tumor biopsy and resection.
We have investigated the discriminating ability of fluorescence lifetime spectroscopy and imaging for high- and low-grade gliomas as well as necrotic tissue as a result of radiation therapy. Current work focuses on the detection of glioblastoma multiforme (GBM) infiltrative edge and the ability of FLIm to identify tumors with IDH1/2 mutations.
Ongoing work will also develop new methods for integrating FLIm with current neuronavigation systems, augmenting FLIm data into the surgical field-of-view and developing data classification algorithms that provide real-time clinical feedback for neurosurgeons.
Collaborators
Dr. Orin Bloch, M.D. (UC Health)
Dr. Han Sung Lee, M.D., Ph.D. (UC Health)
Dr. Matthew Bobinski, M.D., Ph.D. (UC Health)
Funding
NIH (National Institutes of Health): R01CA250512, R21CA252510, R21CA178578