Spectral unmixing designates techniques that allow to decompose measured spectra into linear or non-linear combination of spectra of all targets (endmembers). This technique was initially developed for satellite applications, but it is now also widely used in biomedical applications. However, several drawbacks limit the use of these techniques with standard optical devices like RGB cameras. The devices need to be calibrated and a a priori on the observed scene is often necessary. We propose a new method for estimating endmembers and their proportion automatically and without calibration of the acquisition device based on near separable non-negative matrix factorization. This method estimates the endmembers on spectra of absorbance changes presenting periodic events. This is very common in in vivo biomedical and medical optical imaging where hemodynamics dominate the absorbance fluctuations. We applied the method for identifying functional brain areas during neurosurgery using four different RGB cameras (an industrial camera, a smartphone and two surgical microscopes). Results obtained with the auto-calibration method were consistent with the intraoperative gold standards. Endmembers estimated with the auto-calibration method were similar to the calibrated endmembers used in the modified Beer-Lambert law. The similarity was particularly strong when both cardiac and respiratory periodic events were considered. This work can allow a widespread use of spectral imaging in the industrial or medical field.

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard. In particular, a robust quantification of biomarkers of brain functionality is needed to assist neurosurgeons. We propose a methodology to evaluate and optimize intraoperative identification of brain functional areas by RGB imaging. This consist in a numerical 3D brain model based on Monte Carlo simulations to evaluate intraoperative optical setups for identifying functional brain areas. We also adapted fMRI Statistical Parametric Mapping technique to identify functional brain areas in RGB videos acquired for 12 patients. Simulation and experimental results were consistent and showed that the intraoperative identification of functional brain areas is possible with RGB imaging using deoxygenated hemoglobin contrast. Optical functional identifications were consistent with those provided by EBS and preoperative fMRI. We also demonstrated that a halogen lighting may be particularity adapted for functional optical imaging. We showed 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 and fMRI.

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.

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.

Objective: The objective of this work was to propose an alternative solution to NMR signal transmission by replacing the coaxial cables of the receiver radiofrequency (RF) coil in the context of MRI so as to improve safety. Starting from the analysis of previous studies and reports on the topic, the difficulty of supplying power wirelessly to an RF coil was identified. To avoid this difficult task, the development of a passive analog optical link was studied. Methods: In order to quantify the requirements for achieving an analog conversion, the performance of the link was evaluated based on the input NMR signal amplitude and the optical power and compared with that of a galvanic link. Acquisitions were performed on a 7-T preclinical MRI system with a doped saline solution as phantom. A passive and MRI-compatible polarization-state custom-made modulator was tested as well as a commercial Mach–Zehnder interferometer. Results: The conversion was not sensitive enough to keep similar SNRs, but the main source of noise was identified along with parameters for improvement. Optical power emitted by the laser, insertion loss, and full-phase inversion voltage of the modulators were found to be crucial characteristics for the application. These data indicate that custom application devices are required since the frequency, bandwidth, and amplitude of NMR signals are quite different to usual telecommunication signals. Conclusion: An electro-optic modulation and a transmission channel were successfully conceived and tested. Images were reconstructed with some significant SNR drawbacks that are expected to be compensated with an appropriate modulator. Significance: While technical challenges remain, our approach to a two-decades-long problem could solve a major issue of MRI safety by removing the need for supplying on-coil electrical current.

The coaxial cables connecting coils to the MRI are subject to many unwanted interactions with RF pulses and with patients’ tissues. Currents flowing on the shielding of the cable can lead to local SAR increase and RF-induced burns. Despite their limitations and the amount of effort to discard them, there is still no satisfying alternative. One of the issue for competing technologies is to safely provide on coil power supply without cables inside the MRI. In this work, we propose to evaluate the feasibility of passive optical conversion and transmission of the signal to the MRI console.

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.

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).

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.

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. Magnetic resonance imaging (fMRI) and functional near infra-red spectroscopy (fNIRS) resting-state procedures cannot be used intraoperatively but RGB imaging provides an ideal solution to identify resting-state networks during a neurosurgical operation. We applied resting-state methodologies to intraoperative RGB imaging and evaluated their ability to identify resting-state networks. We adapted two resting-state methodologies from fMRI for the identification of resting-state networks using intraoperative RGB imaging. Measurements were performed in 3 patients who underwent resection of lesions adjacent to motor sites. The resting-state networks were compared to the identifications provided by RGB task-based imaging and electrical brain stimulation. Intraoperative RGB resting-state networks corresponded to RGB task-based imaging (DICE:0.55±0.29). Resting state procedures showed a strong correspondence between them (DICE:0.66±0.11) and with electrical brain stimulation. RGB imaging is a relevant technique for intraoperative resting-state networks identification. Intraoperative resting-state imaging has several advantages compared to functional task-based analyses: data acquisition is shorter, less complex, and less demanding for the patients, especially for those unable to perform the tasks.

We present a multispectral endoscope using visible and near infrared illumination that can be easily adapted to flexible endoscopes. The results show that this device could be used for semi-quantitative detection of pathological tissues.

Nous proposons dans cette etude une methode de mesure du champ electrique directe dans un IRM 7T. La mesure absolue et vectorielle est effectuee au moyen d'une sonde electrooptique. La sonde utilisee est entierement dielectrique, amagnetique et ne perturbe pas l'acquisition de l'image.

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 (HbO(2)) 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 HbO(2)(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 HbO(2)(48%error) or oxCCO (1036%error) maps.

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.