We propose clinical evaluation and optimization studies of time-resolved fluorescence spectroscopy (TR-LIFS) technique for the intraoperative identification of tumor vs. normal brain during neurosurgical resection of brain tumors. A critical need currently for neurosurgeons operating on infiltrative glial neoplasms is the ability to distinguish between normal brain and glial tumor. This project is to demonstrate the feasibility of further development of a fluorescencebased device that will enhance the ability of neurosurgeons to distinguish tumor from normal brain intraoperatively without the need for biopsy. The device will use TR-LIFS technique to identify tumor margins and assess the efficacy of diagnostic procedures. If successful, this work will: (i) enhance the ability of neurosurgeons to distinguish tumor from normal brain tissue intraoperatively, (ii) improved specificity of diagnostic in brain biopsy, and (iii) increase the opportunity of image complete resection of brain tumors and decrease risk of resection of normal brain tissue. By measuring intraoperatively the time-resolved autofluorescence of human brain tumors (glioma, meningioma, metastatic) using an existing TR-LIFS research prototype apparatus and methodology, this STTR Phase I project will address 3 specific aims that combine clinical research and functionality studies over a period of 2 years: (1) To obtain a detailed knowledge of the measurability of time-resolved spectra from human brain tumors and surrounding normal tissue and to evaluate sources of experimental errors and optical loss including brain movements and blood absorption. (2) To identify the optimal TR-LIFS features/parameters which provide the best discrimination between tumor and the normal surrounding tissue by analyzing the characteristics of tissue fluorescence and comparing the spectroscopic findings to the tissue histopathology, immunohistochemical, and conventional pre-and intra-operative diagnostic techniques (MRI, Ultrasound). (3) To develop and test algorithms/software for near real-time TR-LIFS data analysis and brain tissue classification based on a representative subset of spectroscopic features. The result of Phase I will be a basis of knowledge sufficient to permit a TR-LIFS prototype device fabrication, optimized software design, and continued development in Phase II. While this project is initially tailored to brain tumors demarcation, the device could potentially be also applied to diagnosis of other tumor types. ? ? ?
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