We develop a method to measure liver steatosis percentage through relative quantification of fat with near infrared diffuse reflectance spectroscopy. The results obtained show a good correlation with the gold standard anatomopathological analysis.
Separable spectral unmixing designates techniques that allow to decompose spectra as a linear or non-linear combination of spectra of the targets (endmembers) collected. These techniques allow quantitative measurements but several drawbacks limit its use with standard optical devices like RGB cameras. We propose a new method for estimating endmembers and their proportion without calibration of the acquisition device with the analysis of periodic events in the signal. We evaluated the performances of the method for identifying functional brain areas during neurosurgery using RGB imaging. Results were consistent with clinical gold standards. This work can allow a widespread use of spectral imaging in the industrial or medical field.
Protoporphyrin IX (PpIX) is a fluorophore being currently used to localize tumoral tissues. The tissue is usually excited at one wavelength, e.g., 405 nm, and the fluorescence signal is used to estimate the amount of PpIX during surgery. However, other fluorophores (baseline) whose emission spectra are close to the one of PpIX impair the quantification of PpIX and consequently the tissue pathological status classification. An efficient multi-excitation wavelengths method, free from any a priori on the baseline shape, has been proposed to cope with this issue. This method requires decorrelated measurements in the range of PpIX emission at multiple excitation wavelengths. We investigated the influence of the source bandwith on this decorelation by comparing two experimental setups using either LED or laser diode sources. The experimental setup using laser diodes for excitation increases the decorrelation by 35.3 % compared to the one using LEDs in the spectral range of PpIX emission.
RGB imaging is a non-invasive technique that is able to monitor hemodynamic brain responses following neuronal activation during neurosurgery. These cameras are often present in operating rooms, but a robust quantification is complicated to perform during neurosurgery. Liquid blood have been proposed, but it is not possible to model hemodynamic responses similar to those that occur in the brain. To overcome this issue, we propose a 3D brain model, including activated, non-activated grey matter and temporal hemodynamic fluctuations using Monte Carlo simulations. Several setups were modeled to evaluate their impact for identifying activated brain areas using statistical parametric mapping.
We present a method to assess steatosis percentage and relative quantification of fat in the liver using near infrared diffuse reflectance spectroscopy. Measurements performed are in good agreement with the gold standard anatomopathological results.
RGB optical imaging is a marker-free, contactless, and non-invasive technique that is able to monitor hemodynamic brain response following neuronal activation using task-based and resting-state procedures. As opposed to functional task-based analyses, resting-state functional connectivity aims to identify the low frequency cortical hemodynamic fluctuations during patient rest that are linked to resting-state networks. Using intraoperative optical imaging, the main issues of using resting-state procedures come from the partial access to the brain cortex, whereas fMRI or fNIRS resting-state models used whole brain imaging. Task-based fMRI brain maps were compared to intraoperative optical functional brain maps by registering these maps to a preoperative anatomical MRI volume. The objective is to improve the patient care process before, during and after neurosurgery. With the task-based procedure, the RGB brain map showed a good correspondence with task-based fMRI (DICE = 0:75). With the resting-state procedure, the RGB brain map showed a good correspondence with task-based fMRI (seed correlation method: DICE = 0:58 and ICA method: DICE = 0:75).
Protoporphyrin IX (PpIX) is a fluorophore now used to identify tumoral tissues. The tissue is usually excited at one wavelength, e.g., 405 nm, and the fluorescence signal generated by this molecule and other fluorophores (the baseline) is used to estimate the amount of PpIX. However, fluorophores too close to PpIX impair the estimation and resulting classifications. Thus, we handle this issue by suggesting an efficient multi-excitation wavelengths method, free from any a priori on the baseline. Our method aims to distinguish healthy tissues from tumor margins, while being more robust to baseline variability. It keeps an ability to distinguish healthy from tumor tissues up to 87% in cases where existing methods’ ability drops near 0%.
The optical imaging described here is a marker-free, contactless, and non-invasive technique that is able to monitor hemodynamic brain response following neuronal activation during neurosurgery. However, a robust quantification is complicated to perform during neurosurgery due the critical context of the operating room, which makes the calibration and adjustment of optical devices more complex. To overcome this issue, tissue-simulating objects that mimic the properties of biological tissues are required for the development of detection or diagnostic imaging systems. In this study, we evaluated the performance of quantification of chromophore concentration changes measured by experimental setups using two phantoms: a liquid and a numeric brain-simulating phantom. These phantoms mimicked an exposed cerebral cortex as well as the slow concentration changes that occur after neuronal stimulation and the periodic changes due to heartbeat.
We present a Monte-Carlo study for the identification of the hyperspectral camera’ spectral bands for intraoperative hemodynamic and metabolic brain mapping. We also show that a RGB camera is suitable for hemodynamic brain mapping.
We present the methodology for the intraoperative pixel-wise identification of activated cortical areas using RGB imaging. The results indicate that RGB imaging could be a useful complement to the electrical brain stimulation.
We present the methodology for the intraoperative identification of resting state networks using RGB imaging. The results show a good correlation between the resting state and the brain areas identified by electrical brain stimulation.
The acquisition of narrow wavelength bands in the Near-Infrared (NIR) range using hyperspectral imaging have the potential to yield functional and metabolic information during a neurosurgical operation. The analysis of the reflectance spectra through the modified Beer-Lambert law and Monte Carlo simulations enable us to measure the concentration changes of oxy, deoxygenated hemoglobin and cytochrome-c-oxidase during the video acquisition. 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 identified by electrical brain stimulation. This work demonstrates that a quantitative modeling of the brain hemodynamic and metabolic biomarkers could evaluate in a robust way the functional areas and the cellular energy metabolism during neurosurgery.
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.
A RGB camera and a continuous wave white light illumination is a suitable approach to intraoperatively localize the sensory and motor areas of the patient brain. The analysis of the reflectance spectra through the modified Beer-Lambert law enables us to measure the concentration changes of oxygenated and deoxygenated hemoglobin during the video acquisition. However these concentration changes depend on the wavelength dependent optical mean path length. A manual image segmentation and Monte-Carlo simulations allow us to precisely choose the mean path length in a pixel-wise manner.
We demonstrate that a RGB camera and a continuous wave white light illumination is a suitable approach to intraoperatively localize in real time the sensory and motor areas of the patient brain. The analysis of the reflectance spectra of the acquired light and Monte Carlo simulations allow us to measure the concentration changes of oxygenated and deoxygenated hemoglobin during the video acquisition. These measures are compared to the expected hemodynamic response to precisely localize the functional areas of the patient brain.
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