Publications by authors named "Juliette Selb"

Safe and effective brain tumor surgery aims to remove tumor tissue, not non-tumoral brain. This is a challenge since tumor cells are often not visually distinguishable from peritumoral brain during surgery. To address this, we conducted a multicenter study testing whether the Sentry System could distinguish the three most common types of brain tumors from brain tissue in a label-free manner.

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Significance: Raman spectroscopy (RS) applied to surgical guidance is attracting attention among scientists in biomedical optics. Offering a computational platform for studying depth-resolved RS and probing molecular specificity of different tissue layers is of crucial importance to increase the precision of these techniques and facilitate their clinical adoption.

Aim: The aim of this work was to present a rigorous analysis of inelastic scattering depth sampling and elucidate the relationship between sensing depth of the Raman effect and optical properties of the tissue under interrogation.

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Background: The origin of low frequency cerebral hemodynamic fluctuations (CHF) in the resting state remains unknown. Breath-by breath O2-CO2 exchange ratio (bER) has been reported to correlate with the cerebrovascular response to brief breath hold challenge at the frequency range of 0.008-0.

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Background: Hypercapnia during breath holding is believed to be the dominant driver behind the modulation of cerebral blood flow (CBF). However, increasing evidence show that mild hypoxia and mild hypercapnia in breath hold (BH) could work synergistically to enhance CBF response. We hypothesized that breath-by-breath O2-CO2 exchange ratio (bER), defined as the ratio of the change in partial pressure of oxygen (ΔPO2) to that of carbon dioxide (ΔPCO2) between end inspiration and end expiration, would be able to better correlate with the global and regional cerebral hemodynamic responses (CHR) to BH challenge.

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Monitoring of cerebral blood flow (CBF) and autoregulation are essential components of neurocritical care, but continuous noninvasive methods for CBF monitoring are lacking. Diffuse correlation spectroscopy (DCS) is a noninvasive diffuse optical modality that measures a CBF index ( ) in the cortex microvasculature by monitoring the rapid fluctuations of near-infrared light diffusing through moving red blood cells. We tested the feasibility of monitoring with DCS in at-risk patients in the Neurosciences Intensive Care Unit.

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Functional Near-Infrared Spectroscopy (fNIRS) maps human brain function by measuring and imaging local changes in hemoglobin concentrations in the brain that arise from the modulation of cerebral blood flow and oxygen metabolism by neural activity. Since its advent over 20 years ago, researchers have exploited and continuously advanced the ability of near infrared light to penetrate through the scalp and skull in order to non-invasively monitor changes in cerebral hemoglobin concentrations that reflect brain activity. We review recent advances in signal processing and hardware that significantly improve the capabilities of fNIRS by reducing the impact of confounding signals to improve statistical robustness of the brain signals and by enhancing the density, spatial coverage, and wearability of measuring devices respectively.

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Vascular changes during spontaneous headache attacks have been studied over the last 30 years. The interest in cerebral vessels in headache research was initially due to the hypothesis of cerebral vessels as the pain source. Here, we review the knowledge gained by measuring the cerebral vasculature during spontaneous primary headache attacks with the use of single photon emission tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRA) and transcranial Doppler (TCD).

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Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology.

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Physiological monitoring of oxygen delivery to the brain has great significance for improving the management of patients at risk for brain injury. Diffuse correlation spectroscopy (DCS) is a rapidly growing optical technology able to non-invasively assess the blood flow index (BFi) at the bedside. The current limitations of DCS are the contamination introduced by extracerebral tissue and the need to know the tissue's optical properties to correctly quantify the BFi.

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Analysis of cerebral hemodynamics reveals a wide spectrum of oscillations ranging from 0.0095 to 2 Hz. While most of these oscillations can be filtered out during analysis of functional near-infrared spectroscopy (fNIRS) signals when estimating stimulus evoked hemodynamic responses, oscillations around 0.

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Diffuse correlation spectroscopy (DCS) measurements of blood flow rely on the sensitivity of the temporal autocorrelation function of diffusively scattered light to red blood cell (RBC) mean square displacement (MSD). For RBCs flowing with convective velocity [Formula: see text], the autocorrelation is expected to decay exponentially with [Formula: see text], where [Formula: see text] is the delay time. RBCs also experience shear-induced diffusion with a diffusion coefficient [Formula: see text] and an MSD of [Formula: see text].

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Autonomic nervous system response is known to be highly task-dependent. The sensitivity of near-infrared spectroscopy (NIRS) measurements to superficial layers, particularly to the scalp, makes it highly susceptible to systemic physiological changes. Thus, one critical step in NIRS data processing is to remove the contribution of superficial layers to the NIRS signal and to obtain the actual brain response.

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Functional near-infrared spectroscopy is prone to contamination by motion artifacts (MAs). Motion correction algorithms have previously been proposed and their respective performance compared for evoked rain activation studies. We study instead the effect of MAs on "oscillation" data which is at the basis of functional connectivity and autoregulation studies.

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Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS.

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As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation.

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Calibrated functional magnetic resonance imaging (fMRI) is a widely used method to investigate brain function in terms of physiological quantities such as the cerebral metabolic rate of oxygen (CMRO2). The first and one of the most common methods of fMRI calibration is hypercapnic calibration. This is achieved via simultaneous measures of the blood-oxygenation-level dependent (BOLD) and the arterial spin labeling (ASL) signals during a functional task that evokes regional changes in CMRO2.

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Near-infrared spectroscopy (NIRS) estimations of the adult brain baseline optical properties based on a homogeneous model of the head are known to introduce significant contamination from extracerebral layers. More complex models have been proposed and occasionally applied to in vivo data, but their performances have never been characterized on realistic head structures. Here we implement a flexible fitting routine of time-domain NIRS data using graphics processing unit based Monte Carlo simulations.

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Analysis of cerebral autoregulation by measuring spontaneous oscillations in the low frequency spectrum of cerebral cortical vessels might be a useful tool for assessing risk and investigating different treatment strategies in carotid artery disease and stroke. Near infrared spectroscopy (NIRS) is a non-invasive optical method to investigate regional changes in oxygenated (oxyHb) and deoxygenated hemoglobin (deoxyHb) in the outermost layers of the cerebral cortex. In the present study we examined oxyHb low frequency oscillations, believed to reflect cortical cerebral autoregulation, in 16 patients with both symptomatic carotid occlusive disease and cerebral hypoperfusion in comparison to healthy controls.

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As the applications of near-infrared spectroscopy (NIRS) continue to broaden and long-term clinical monitoring becomes more common, minimizing signal artifacts due to patient movement becomes more pressing. This is particularly true in applications where clinically and physiologically interesting events are intrinsically linked to patient movement, as is the case in the study of epileptic seizures. In this study, we apply an approach common in the application of EEG electrodes to the application of specialized NIRS optical fibers.

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Motion artifacts are a significant source of noise in many functional near-infrared spectroscopy (fNIRS) experiments. Despite this, there is no well-established method for their removal. Instead, functional trials of fNIRS data containing a motion artifact are often rejected completely.

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Objectives: Effective nasal continuous positive airway pressure (CPAP) therapy reduces the cardiovascular outcomes associated with obstructive sleep apnea (OSA), but the mechanism behind this effect is unclear. We investigated if OSA patients during wakefulness showed signs of increased sympathetic activity and decreased vasoreactivity in cerebral cortical vessels as measured with near-infrared spectroscopy (NIRS), and if this may be reversed by CPAP treatment.

Subjects And Methods: 23 OSA patients (mean age, 55y) naive to CPAP were included in a prospective interventional study.

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Background: High frequency (HF) stimulation of the sphenopalatine ganglion (SPG) is an emerging abortive treatment for cluster headache (CH) attacks. HF SPG stimulation is thought to exert its effect by physiologically blocking parasympathetic outflow. We hypothesized that low frequency (LF) SPG stimulation may activate the SPG, causing increased parasympathetic outflow and thereby provoking cluster attacks in CH patients.

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Near-infrared spectroscopy (NIRS) is susceptible to signal artifacts caused by relative motion between NIRS optical fibers and the scalp. These artifacts can be very damaging to the utility of functional NIRS, particularly in challenging subject groups where motion can be unavoidable. A number of approaches to the removal of motion artifacts from NIRS data have been suggested.

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Background And Methods: Low frequency oscillations (LFO) of cerebral vessels are believed to reflect cerebral autoregulation. We investigated day-to-day and hemispheric variations in 0.1 Hz LFO with near infrared spectroscopy (NIRS) and transcranial Doppler (TCD) to determine phase shift and gain of oxygenated haemoglobin (oxyHb) and the velocity of the middle cerebral artery (Vmca) to the arterial blood pressure (ABP).

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