Optimal Spectral Combination of a Hyperspectral Camera for Intraoperative Hemodynamic and Metabolic Brain Mapping  
[PERSON]  
1 Universite de Lyon, INSA-Lyon, Universite Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREAITS UMR 5220, U1206, F69100 Lyon, France; [PERSON]@creatis.insa-lyon. Hyperspectral imaging allows the in vivo monitoring of the hemodynamic and metabolic status of an exposed cortex. Hyperspectral imaging provides spatially and spectrally resolved images using numerous and contiguous spectral bands [7]. In comparison, a standard color camera (or RGB camera) acquires three colors (red, green, and blue) using broad and overlapping spectral detectors. Both techniques have the ability to measure the oxygenation changes in the tissue using the modified Beer-Lambert law [5; 8; 9; 10; 11; 12]. In functional brain mapping studies, the concentration changes of oxy- (\(\Delta C_{HbO_{2}}\)) and deoxy-hemoglobin (\(\Delta C_{Hb}\))can be analyzed to identify the activated cortical areas [5; 13; 14; 15; 16; 17; 18; 19; 20; 21]. The acquisition of the intrinsic signal in the near-infrared range offers the potential to monitor the brain metabolism with the quantification of the concentration changes of the oxidative state of cytochrome-c-oxidase (\(\Delta C_{oxCCO}\)) [22; 23; 24; 25]. Hyperspectral and color cameras combined with a white light illumination are simple and powerful tools for the computation of intraoperative functional brain maps. The objective is to guide the neurosurgeon during brain surgery to prevent any functional impairments after surgical procedures (tumor resection). In the literature, all wavelength bands acquired by hyperspectral imaging setups are used to measure the hemodynamic and metabolic changes in the brain [10; 24; 25; 26]. However, there are some studies in which the choice of the selected spectral bands is discussed. [PERSON] et al. [23] showed that tens to hundreds of spectral bands acquired with a broadband near-infrared spectroscopy setup (780 nm to 900 nm) can be used to measure the oxCCO concentration changes. [PERSON] et al. [27] showed that eight wavelength combinations between 780 nm and 900 nm give rise to the least possible estimation errors for the deconvolution of \(\Delta C_{HbO_{2}}\), \(\Delta C_{Hb}\), and \(\Delta C_{oxCCO}\) when compared to a gold standard (121 wavelengths included between 780 nm and 900 nm). [PERSON] et al. [28] proposed a Monte Carlo framework to investigate the performances of broadband spectroscopy to quantify the brain hemodynamic and metabolic responses. The results of this study indicated that eight wavelength between 780 nm and 900 nm should be selected to provide minimal differences in quantification compared to a gold standard of 121 wavelengths (780 nm to 900 nm). [PERSON] et al. [29] proposed a method based on the error propagation analysis and Monte Carlo simulations (three layer model: scalp, skull, and brain) allowing the estimation of the cytochrome-c-oxidase uncertainty in data measured with a multispectral time-resolved near-infrared spectroscopy device. The results of this study indicated that 16 wavelengths between 688 and 875 nm could be used to minimize the standard deviation of the cytochrome-c-oxidase concentration changes in the brain layer Wavelength optimization problems have also been studied for other optical imaging techniques such as near-infrared optical tomography. [PERSON] et al. [30] identified seven laser diodes among 38 commercially available diodes in the range of 633-980 nm to estimate four chromophores (HbO\({}_{2}\), Hb, water, and lipids) and the scattering prefactor in breast tissue. [PERSON] et al. used the condition number and the residual norm to identify the optimal matrix used for the resolution of a linear system and thus to estimate four chromophores and the scattering prefactor in breast tissue. The optimal wavelengths were identified for a large residual norm and small condition number.