OBJECTIVE: The role of autofluorescence spectroscopy in the detection and staging of benign and malignant brain tumors is being investigated in this study, with an additional aim of determining an optimum excitation wavelength for the spectroscopic identification of brain tumors. MATERIALS AND METHODS: The present study involves in-vitro autofluorescence monitoring of different human brain tumor samples to assess their spectroscopic properties. The autofluorescence measurement at four different excitation wavelengths 320, 370, 410, and 470 nm, were carried out for five different brain tumor types: glioma, astrocytoma, meningioma, pituitary adenoma, and schwannoma. RESULTS: The fluorescence spectra of tumor tissues showed significant differences, both in intensity and in spectral profile, from those of adjacent normal brain tissues at all four excitation wavelengths. The data were then subjected to multivariate statistical analysis and the sensitivities and specificities were calculated for each group. Of the four excitation wavelengths being considered, 470 nm appeared to be the optimal wavelength for detecting tissue fluorescence of brain tumor tissues. CONCLUSIONS: In conclusion, the spectroscopic luminescence measurements carried out in this study revealed significant differences between tumor tissue and adjacent normal tissue of human brains for all the tumor types tested, except for pituitary adenoma. From the results of this study we conclude that excitation wavelengths ranging from 410-470 nm are most suitable for the detection of brain tumor tissue. Moreover, in this particular study, only excitation at 470 nm indicated that samples we considered to be normal tissue were not normal, and that these were indeed pituitary adenoma tissues. This distinction was not clear at other excitation wavelengths.
OBJECTIVE: The role of autofluorescence spectroscopy in the detection and staging of benign and malignant brain tumors is being investigated in this study, with an additional aim of determining an optimum excitation wavelength for the spectroscopic identification of brain tumors. MATERIALS AND METHODS: The present study involves in-vitro autofluorescence monitoring of different humanbrain tumor samples to assess their spectroscopic properties. The autofluorescence measurement at four different excitation wavelengths 320, 370, 410, and 470 nm, were carried out for five different brain tumor types: glioma, astrocytoma, meningioma, pituitary adenoma, and schwannoma. RESULTS: The fluorescence spectra of tumor tissues showed significant differences, both in intensity and in spectral profile, from those of adjacent normal brain tissues at all four excitation wavelengths. The data were then subjected to multivariate statistical analysis and the sensitivities and specificities were calculated for each group. Of the four excitation wavelengths being considered, 470 nm appeared to be the optimal wavelength for detecting tissue fluorescence of brain tumor tissues. CONCLUSIONS: In conclusion, the spectroscopic luminescence measurements carried out in this study revealed significant differences between tumor tissue and adjacent normal tissue of human brains for all the tumor types tested, except for pituitary adenoma. From the results of this study we conclude that excitation wavelengths ranging from 410-470 nm are most suitable for the detection of brain tumor tissue. Moreover, in this particular study, only excitation at 470 nm indicated that samples we considered to be normal tissue were not normal, and that these were indeed pituitary adenoma tissues. This distinction was not clear at other excitation wavelengths.
Authors: Daphne Meza; Danni Wang; Yu Wang; Sabine Borwege; Nader Sanai; Jonathan T C Liu Journal: Lasers Surg Med Date: 2015-04-14 Impact factor: 4.025
Authors: Marc Zanello; Fanny Poulon; Johan Pallud; Pascale Varlet; H Hamzeh; Georges Abi Lahoud; Felipe Andreiuolo; Ali Ibrahim; Mélanie Pages; Fabrice Chretien; Federico Di Rocco; Edouard Dezamis; François Nataf; Baris Turak; Bertrand Devaux; Darine Abi Haidar Journal: Sci Rep Date: 2017-02-02 Impact factor: 4.379