Diagnosis of meningioma by time-resolved fluorescence spectroscopy

Abstract

We investigate the use of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) as an adjunctive tool for the intraoperative rapid evaluation of tumor specimens and delineation of tumor from surrounding normal tissue. Tissue autofluorescence is induced with a pulsed nitrogen laser (337 nm, 1.2 ns) and the intensity decay profiles are recorded in the 370 to 500 nm spectral range with a fast digitizer (0.2 ns resolution). Experiments are conducted on excised specimens (meningioma, dura mater, cerebral cortex) from 26 patients (97 sites). Spectral intensities and time-dependent parameters derived from the time-resolved spectra of each site are used for tissue characterization. A linear discriminant analysis algorithm is used for tissue classification. Our results reveal that meningioma is characterized by unique fluorescence characteristics that enable discrimination of tumor from normal tissue with high sensitivity (>89%) and specificity (100%). The accuracy of classification is found to increase (92.8% cases in the training set and 91.8% in the cross-validated set correctly classified) when parameters from both the spectral and the time domain are used for discrimination. Our findings establish the feasibility of using TR-LIFS as a tool for the identification of meningiomas and enables further development of real-time diagnostic tools for analyzing surgical tissue specimens of meningioma or other brain tumors.

Time-resolved fluorescence lifetime for cutaneous melanoma detection

“…Tumor metabolic stages and the amount of molecules present in tissue may be the responsible of changes in the decays. Butte et al (2005) described the potential use of time-resolved fluorescence spectroscopy as an adjunctive tool for the intraoperative rapid evaluation of meningioma diagnosis. They evaluated the technique on ex vivo tissue specimens from patients undergoing brain tumor surgery and the results showed a sensitivity higher than 89%, specificity of 100% and an accuracy of classification around 92% [13].…”

In vivo measurements of diffuse reflectance and time‐resolved autofluorescence emission spectra of basal cell carcinomas

“…Changes in the fluorescence properties of these molecules can report on altered metabolism, protein cross links, cell signalling and even disease state [15,[17][18][19]. In particular the fluorescence lifetime of endogenous fluorophores, which is relatively insensitive to fluorophore concentration and to signal attenuation by the sample, has been shown (both ex vivo and in vivo) to effectively differentiate between healthy and diseased tissue, for example in atherosclerotic plaques [20,21] and in various types of cancer [22][23][24][25][26][27][28][29][30][31]. Accordingly, there is significant interest in the development of instruments that can measure the autofluorescence properties of skin for clinical diagnosis, e.g.…”

Multifunctional in vivo imaging of pancreatic islets during diabetes development

“…The dynamics of lipid partitioning and fatty acid oxidation can be modeled by monitoring electron transfer flavoprotein autofluorescence (Lam et al, 2012). Finally, quantitative studies using cellular autofluorescence have revealed distinct differences between healthy and cancer cells (Butte et al, 2005;Mayevsky and Barbiro-Michaely, 2013;Pavlova et al, 2008). As multiphoton excitation microscopy, fluorescence lifetime imaging and timeresolved fluorescence anisotropy techniques become readily available from commercial sources, applying measurements of autofluorescence to intraocular imaging will enable in vivo longitudinal studies in a variety of biological systems.…”