In recent years, hyperspectral imaging (HSI) has demonstrated the capacity to non-invasively differentiate tumours from healthy tissues and identify cancerous regions during surgery, particularly for glioma resection. This is thanks to the use of a relatively large number of adjacent wavelength bands, in order to reconstruct full reflectance spectra of each pixel in the acquired images of the target, thus providing information about its morpho-chemical composition. However, current HSI analysis approaches seem not to fully exploit such advantage, since they mostly tend to focus on tissue features recognition and cancer identification based on supervised algorithm trained upon diagnostic evaluations made by the neurosurgeons or from other diagnostic tools (e.g., histopathology). There is indeed a lack of proper broad-range, optical characterisation of tumour tissue, specifically gliomas, which could provide a more objective, comprehensive and quantitative insight in the spectro-chemistry of the tumour itself and help identifying novel biomarkers for cancer imaging via HSI. For this purpose, we present a fully optical characterisation of fresh ex vivo samples of glioma from surgical biopsies using both a laboratory spectrophotometer and an in-house, high-spectral density HSI system. The latter is based on spectral scanning of the samples via supercontinuum laser (SCL) illumination filtered with acousto-optic tunable filters (AOTF). The results of the spectral characterisation are analysed and compared to extract optical signatures for potential glioma biomarkers in order to further aid neuronavigation via HSI during glioma resection, in particular in the framework of our recently started HyperProbe project.

Optical characterisation and study of ex vivo glioma tissue for hyperspectral imaging during neurosurgery / Giannoni L.; Bonaudo C.; Marradi M.; Della Puppa A.; Pavone F.S.. - ELETTRONICO. - 12628:(2023), pp. 81-81. (Intervento presentato al convegno SPIE proceedings series) [10.1117/12.2670854].

Optical characterisation and study of ex vivo glioma tissue for hyperspectral imaging during neurosurgery

Giannoni L.
;
Bonaudo C.;Della Puppa A.;Pavone F. S.
2023

Abstract

In recent years, hyperspectral imaging (HSI) has demonstrated the capacity to non-invasively differentiate tumours from healthy tissues and identify cancerous regions during surgery, particularly for glioma resection. This is thanks to the use of a relatively large number of adjacent wavelength bands, in order to reconstruct full reflectance spectra of each pixel in the acquired images of the target, thus providing information about its morpho-chemical composition. However, current HSI analysis approaches seem not to fully exploit such advantage, since they mostly tend to focus on tissue features recognition and cancer identification based on supervised algorithm trained upon diagnostic evaluations made by the neurosurgeons or from other diagnostic tools (e.g., histopathology). There is indeed a lack of proper broad-range, optical characterisation of tumour tissue, specifically gliomas, which could provide a more objective, comprehensive and quantitative insight in the spectro-chemistry of the tumour itself and help identifying novel biomarkers for cancer imaging via HSI. For this purpose, we present a fully optical characterisation of fresh ex vivo samples of glioma from surgical biopsies using both a laboratory spectrophotometer and an in-house, high-spectral density HSI system. The latter is based on spectral scanning of the samples via supercontinuum laser (SCL) illumination filtered with acousto-optic tunable filters (AOTF). The results of the spectral characterisation are analysed and compared to extract optical signatures for potential glioma biomarkers in order to further aid neuronavigation via HSI during glioma resection, in particular in the framework of our recently started HyperProbe project.
2023
SPIE proceedings series
SPIE proceedings series
Giannoni L.; Bonaudo C.; Marradi M.; Della Puppa A.; Pavone F.S.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1340651
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