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Tissue database of autofluorescence response to improve intra-operative diagnosis of primitive brain tumors

Abstract : The first standard approach for brain tumor treatment is the surgical resection. In this protocol an important challenge remains, the identification of tumor margins to ensure a complete resection and avoid risk of tumor recurrence. Nowadays no intra-operative means of contrast are able to resolve infiltrated regions from healthy tissue. The standard for tumor margin diagnosis is the histological analysis of biopsies. An ex vivo method that requires one to several days to issue a final pathological reports, a time lapse that could be fatal to the patient. Optical microscopy have recently been developed towards an intra-operative clinical use to answer this challenge. In this work, the technique of two-photon microscopy based on the autofluorescence of tissue have been favored. This technique gives access to two imaging contrasts, the second-harmonic generation and emission of fluorescence, and can be combined to quantitative measurements, such as spectroscopy and fluorescence lifetime. The combination of these four modalities of detection will give a complete structural and metabolic information on the observed region. To support the technical development towards an endomicroscopic probe, the resulted data have to be reliable and proved to be of interest for the surgeon. Consequently, an extensive database of the autofluorescence response of brain tumor tissue have been constructed and presented in this manuscript, with algorithms able to discriminate with reliability tumoral from healthy regions. Algorithms that have shown potential to be automatized in a clinical setting, in order to give a real-time answer to the surgeons.
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Submitted on : Saturday, November 2, 2019 - 1:08:06 AM
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  • HAL Id : tel-02343182, version 1


Fanny Poulon. Tissue database of autofluorescence response to improve intra-operative diagnosis of primitive brain tumors. Optics / Photonic. Université Paris Saclay (COmUE), 2018. English. ⟨NNT : 2018SACLS236⟩. ⟨tel-02343182⟩



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