Multimodal Analysis of Central Nervous System Tumor Tissue Endogenous Fluorescence With Multiscale Excitation - Imagerie et Modélisation en Neurobiologie et Cancérologie
Article Dans Une Revue Frontiers in Physics Année : 2018

Multimodal Analysis of Central Nervous System Tumor Tissue Endogenous Fluorescence With Multiscale Excitation

Résumé

The primary therapeutic approach for high-grade brain tumor is surgical resection. However, identifying tumor margins in vivo remains a major challenge. Biopsy analysis remains the standard diagnostic technique on tumor margins. This ex vivo analysis is time consuming and delays treatment. The aim of this study is tissue discrimination using label free autofluorescence and application in intraoperative optical probe for optical biopsy. Biopsy samples from 51 patients who underwent brain tumor surgery (21 metastasis tumors, 17 glioblastoma tumors, GBM, and 13 control samples) were included in this study. The samples underwent a multiscale and multi-contrast optical analysis. The excitation were performed with a deep-UV synchrotron beam, at 275 nm, and a near-infrared Ti:sapphire pulsed laser, from 690 to 1,040 nm. The detection modalities were fluorescence imaging, spectroscopy and fluorescence lifetime. Using deep-UV excitation, and combining three molecular ratios (tyrosin-tryptophan, tryptophan-collagen, tryptophan-NADH) resulted in discrimination with a sensitivity of 90% and a specificity of 73%. Using a two-photon excitation, and combining average lifetime, NADH-FAD ratio and Porphyrin-NADH ratio, resulted in discrimination with a sensitivity of 97% and a specificity of 100%. A multiscale algorithm resulted in an overlap of only 1.8% between control and tumor samples.
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Dates et versions

hal-01937812 , version 1 (30-07-2024)

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Fanny Poulon, Audrey Chalumeau, Frederic Jamme, Johan Pallud, Pascale Varlet, et al.. Multimodal Analysis of Central Nervous System Tumor Tissue Endogenous Fluorescence With Multiscale Excitation. Frontiers in Physics, 2018, 6, pp.109. ⟨10.3389/fphy.2018.00109⟩. ⟨hal-01937812⟩
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