5-ALA-induced protoporphyrin IX (PpIX) fluorescence enables to guiding in intra-operative surgical glioma resection. However at present, it has yet to be shown that this method is able to identify infiltrative component of glioma. In extracted tumor tissues we measured a two-peaked emission in low grade gliomas and in the infiltrative component of glioblastomas due to multiple photochemical states of PpIX. The second emission peak appearing at 620 nm (shifted by 14 nm from the main peak at 634 nm) limits the sensibility of current methods to measured PpIX concentration. We propose new measured parameters, by taking into consideration the two-peaked emission, to overcome these limitations in sensitivity. These parameters clearly distinguish the solid component of glioblastomas from low grade gliomas and infiltrative component of glioblastomas.

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Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. However, it still lacks robustness to be used as a clinical standard. In particular, new biomarkers of brain functionality with improved sensitivity and specificity are needed. We present a method for the computation of hemodynamics-based functional brain maps using an RGB camera and a white light source. We measure the quantitative oxy and deoxyhemoglobin concentration changes in the human brain cortex with the modified Beer-Lambert law and Monte Carlo simulations. A functional model has been implemented to evaluate the functional brain areas following neuronal activation by physiological stimuli. The results show a good correlation between the computed quantitative functional maps and the brain areas localized by electrical brain stimulation (EBS). We demonstrate that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

5-ALA-induced protoporphyrin IX (PpIX) has shown its relevance in medical assisting techniques, notably in the detection of glioma (brain tumors). Validation of instruments on phantoms is mandatory and a standardization procedure has recently been proposed. This procedure yields phantoms recipes to realize a linear relationship between PpIX concentration and fluorescence emission intensity. The present study puts forward phantoms where this linear relationship cannot be used. We propose a model that considers two states of PpIX, corresponding to two different aggregates of PpIX, with fluorescence spectra peaking at 634 and 620 nm, respectively. We characterize the influence of these two states on PpIX fluorescence emission spectra in phantoms with steady concentration of PpIX and various microenvironment parameters (surfactant, Intralipid or bovine blood concentration, and pH). We show that, with fixed PpIX concentration, a modification of the microenvironment induces a variation of the emitted spectrum, notably a shift in its central wavelength. We show that this modification reveals a variation of proportions of the two states. This establishes phantom microenvironment regimes where the usual single state model is biased while a linear combination of the two spectra enables accurate recovering of any measured spectra.

Intraoperative optical imaging is a localization technique for the functional areas of the human brain cortex during neurosurgical procedures. These areas are assessed by monitoring the oxygenated (HbO2) and deoxygenated hemoglobin (Hb) concentration changes occurring in the brain. Sometimes, the functional status of the brain is assessed using metabolic biomarkers: the oxidative state of cytochrome-c-oxidase (oxCCO). A setup composed of a white light source and a hyperspectral or a standard RGB camera could be used to identify the functional areas. The choice of the best spectral configuration is still based on an empirical approach. We propose in this study a method to define the optimal spectral combinations of a commercial hyperspectral camera for the computation of hemodynamic and metabolic brain maps. The method is based on a Monte Carlo framework that simulates the acquisition of the intrinsic optical signal following a neuronal activation. The results indicate that the optimal spectral combination of a hyperspectral camera aims to accurately quantify the HbO2 (0.5% error), Hb (4.4% error), and oxCCO (15% error) responses in the brain following neuronal activation. We also show that RGB imaging is a low cost and accurate solution to compute Hb maps (4% error), but not accurate to compute HbO2 (48% error) or oxCCO (1036% error) maps.

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Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluorescence measurements are a clinical standard, but expert-based classification models still lack sensitivity and specificity. Here a fully automatic clustering method is proposed to discriminate glioma margin. This is obtained from spectroscopic fluorescent measurements acquired with a recently introduced intraoperative set up. We describe a data-driven selection of best spectral features and show how this improves results of margin prediction from healthy tissue by comparison with the standard biomarkerbased prediction. This pilot study based on 10 patients and 50 samples shows promising results with a best performance of 77% of accuracy in healthy tissue prediction from margin tissue. Gliomas account for more than fifty percent of primitive brain tumors. They are infiltrative tumors, with a margin difficult to identify and discriminate from the surrounding healthy tissues. The world health organization (WHO) classifies gliomas in 4 grades 1 , but most studies commonly consider two separate groups: High-Grade Gliomas (HGG) and Low-Grade Gliomas (LGG). Studies have shown that in 85% cases, recurrences of HGG are localized less than 2 centimeters away from the initial tumor 2. Then, improving the extent of resection is relevant to prevent recurrence and improve life quality and expectancy 3-5. Pre-operative MRI combined with neuro-navigation is currently used in the operating theater 6,7 but shows strong limitations 8-10. 5-aminolevulinic acid (5-ALA) induced protoporphyrin IX (PpIX) fluorescence microscopy has shown its relevance in neuro-oncology 11. PpIX absorbs light at 405 nm and emits fluorescence with a main peak centered at 634 nm. This technique is the actual clinical standard for PpIX-based surgical assistance. However, its sensitivity is still limited when applied to low-density infiltrative parts of HGG 12,13 or to LGG 14. Various 5-ALA induce PpIX fluorescence spectroscopy methods have been proposed to overcome these sensitivity issues. Previous works 6,15-24 , focus on the extraction of biomarkers from the measurements, based on a priori information on the link between the biomarkers and the microenvironment of PpIX. These approaches are known as expert-based, and various biomarker models have been proposed in the literature. Quantification of PpIX concentration 15 show enhanced sensitivity either in HGG 16 or in LGG 17. Normalization procedures of biomarkers can also increase their robustness 6,18,19. Other works suggest that relevant models could be obtained based on the shape of the PpIX emission spectrum 18-26. These works show that the PpIX fluorescence emission spectral complexity in tissue is closely linked with the pathological status. However, the still unsolved origin of this complexity impairs the extraction of the best features with an expert-based related method, thus preventing the classification of measurements into relevant pathological status.

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