Abstract
.Significance: We present a Monte Carlo (MC) computational framework that simulates near-infrared (NIR) hyperspectral imaging (HSI) aimed at assisting quantification of the in vivo hemodynamic and metabolic states of the exposed cerebral cortex in small animal experiments. This can be done by targeting the NIR spectral signatures of oxygenated () and deoxygenated (HHb) hemoglobin for hemodynamics as well as the oxidative state of cytochrome-c-oxidase (oxCCO) for measuring tissue metabolism.Aim: The aim of this work is to investigate the performances of HSI for this specific application as well as to assess key factors for the future design and operation of a benchtop system.Approach: The MC framework, based on Mesh-based Monte Carlo (MMC), reproduces a section of the exposed cortex of a mouse from an in vivo image and replicates hyperspectral illumination and detection at multiple NIR wavelengths (up to 121).Results: The results demonstrate: (1) the fitness of the MC framework to correctly simulate hyperspectral data acquisition; (2) the capability of HSI to reconstruct spatial changes in the concentrations of , HHb, and oxCCO during a simulated hypoxic condition; (3) that eight optimally selected wavelengths between 780 and 900 nm provide minimal differences in the accuracy of the hyperspectral results, compared to the “gold standard” of 121 wavelengths; and (4) the possibility to mitigate partial pathlength effects in the reconstructed data and to enhance quantification of the hemodynamic and metabolic responses.Conclusions: The MC framework is proved to be a flexible and useful tool for simulating HSI also for different applications and targets.
Highlights
Hyperspectral imaging (HSI) is an emerging optical technique for biomedical applications that can be potentially used to quantitatively monitor in vivo changes in the metabolic and hemodynamic states of the brain, on the exposed cortex
The large vascular hemodynamic response related to both chromophores is accurately localized within the boundaries of the pial vasculature, resolving both major and minor vessels, as well as showing a decrease in the concentration of HbO2 and an increase in the concentration of HHb, as theoretically expected
A minor hemodynamic response from HbO2 and HHb is reconstructed in the surrounding tissue that is consistent with the simulate changes in oxygen saturation and blood volume in the subpial gray matter
Summary
Hyperspectral imaging (HSI) is an emerging optical technique for biomedical applications that can be potentially used to quantitatively monitor in vivo changes in the metabolic and hemodynamic states of the brain, on the exposed cortex. HSI provides extensive spectral information, in addition to spatial data, by acquiring images over a broad range of the light spectrum at numerous and contiguous wavelength bands.[1,2] Changes in the concentrations of relevant biomarkers, such as oxyhemoglobin (HbO2) and deoxyhemoglobin (HHb), can be retrieved by measuring the intensity changes of multiple different wavelengths of reflected light after having interacted with the cerebral tissue. These light intensity changes originate from variations in the optical properties of brain tissue during physiological processes, e.g., changes. CCO has a high specificity as a biomarker for monitoring brain metabolism, due to its high concentration in the cortical tissue.[5,6]
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