Diffuse optical tomography spatial prior for EEG source localization in human visual cortex.

Electroencephalography (EEG) and diffuse optical tomography (DOT) are imaging methods which are widely used for neuroimaging. While the temporal resolution of EEG is high, the spatial resolution is typically limited. DOT, on the other hand, has high spatial resolution, but the temporal resolution is inherently limited by the slow hemodynamics it measures. In our previous work, we showed using computer simulations that when using the results of DOT reconstruction as the spatial prior for EEG source reconstruction, high spatio-temporal resolution could be achieved. In this work, we experimentally validate the algorithm by alternatingly flashing two visual stimuli at a speed that is faster than the temporal resolution of DOT. We show that the joint reconstruction using both EEG and DOT clearly resolves the two stimuli temporally, and the spatial confinement is drastically improved in comparison to reconstruction using EEG alone.

A model of neurovascular coupling and its application to cortical spreading depolarization.

Cortical spreading depolarization (CSD) is a neuropathological condition involving propagating waves of neuronal silence, and is related to multiple diseases, such as migraine aura, traumatic brain injury (TBI), stroke, and cardiac arrest, as well as poor outcome of patients. While CSDs of different severity share similar roots on the ion exchange level, they can lead to different vascular responses (namely spreading hyperemia and spreading ischemia). In this paper, we propose a mathematical model relating neuronal activities to predict vascular changes as measured with near-infrared spectroscopy (NIRS) and fMRI recordings, and apply it to the extreme case of CSD, where sustained near-complete neuronal depolarization is seen. We utilize three serially connected models (namely, ion exchange, neurovascular coupling, and hemodynamic model) which are described by differential equations. Propagating waves of ion concentrations, as well as the associated vasodynamics and hemodynamics, are simulated by solving these equations. Our proposed model predicts vasodynamics and hemodynamics that agree both qualitatively and quantitatively with experimental literature. Mathematical modeling and simulation offer a powerful tool to help understand the underlying mechanisms of CSD and help interpret the data. In addition, it helps develop novel monitoring techniques prior to data collection. Our simulated results strongly suggest that fMRI is unable to reliably distinguish between spreading hyperemia and spreading ischemia, while NIRS signals are substantially distinct in the two cases.

Temporal Dynamics of Shape Processing Differentiate Contributions of Dorsal and Ventral Visual Pathways.

Although shape perception is primarily considered a function of the ventral visual pathway, previous research has shown that both dorsal and ventral pathways represent shape information. Here, we examine whether the shape-selective electrophysiological signals observed in dorsal cortex are a product of the connectivity to ventral cortex or are independently computed. We conducted multiple EEG studies in which we manipulated the input parameters of the stimuli so as to bias processing to either the dorsal or ventral visual pathway. Participants viewed displays of common objects with shape information parametrically degraded across five levels. We measured shape sensitivity by regressing the amplitude of the evoked signal against the degree of stimulus scrambling. Experiment 1, which included grayscale versions of the stimuli, served as a benchmark establishing the temporal pattern of shape processing during typical object perception. These stimuli evoked broad and sustained patterns of shape sensitivity beginning as early as 50 msec after stimulus onset. In Experiments 2 and 3, we calibrated the stimuli such that visual information was delivered primarily through parvocellular inputs, which mainly project to the ventral pathway, or through koniocellular inputs, which mainly project to the dorsal pathway. In the second and third experiments, shape sensitivity was observed, but in distinct spatio-temporal configurations from each other and from that elicited by grayscale inputs. Of particular interest, in the koniocellular condition, shape selectivity emerged earlier than in the parvocellular condition. These findings support the conclusion of distinct dorsal pathway computations of object shape, independent from the ventral pathway.

Optical Imaging Technology: A Useful Tool to Identify Remission in Cushing Disease After Surgery.

We recently reported the use of optical imaging technology to quantify facial plethora in endogenous Cushing syndrome (CS). In the present study, we studied a larger cohort of patients with Cushing disease (CD) and examined water content fraction as well as blood volume fraction as bio-optic markers for determining the efficacy of this methodology as a predictor of lasting remission after surgery for CS. We imaged 49 patients before and after transsphenoidal surgery (TSS) for Cushing disease (CD); 22 patients were also seen at 3-6 months, and 13 patients 12 months post-operatively. On all patients, we used multi-spectral imaging (MSI) to evaluate hemodynamic distributions as well as water content at a specific area of the face. We found a decrease in blood volume fraction after vs. before surgical treatment in the tested facial area in 37 of the 40 patients, as determined with biochemical markers (p<0.001). All patients that were followed up for up to 12 months showed the same decrease from preoperative values and they remained in remission from CD. We conclude that MSI can be used for the evaluation of remission from CD, at least in the immediate post-operative period and up to one year after surgery. The use of this technology can supplement biochemical and other testing for the evaluation of the various treatment modalities available for patients with CD.

Nonlinear extension of a hemodynamic linear model for coherent hemodynamics spectroscopy.

In this work, we are proposing an extension of a recent hemodynamic model (Fantini, 2014a), which was developed within the framework of a novel approach to the study of tissue hemodynamics, named coherent hemodynamics spectroscopy (CHS). The previous hemodynamic model, from a signal processing viewpoint, treats the tissue microvasculature as a linear time-invariant system, and considers changes of blood volume, capillary blood flow velocity and the rate of oxygen diffusion as inputs, and the changes of oxy-, deoxy-, and total hemoglobin concentrations (measured in near infrared spectroscopy) as outputs. The model has been used also as a forward solver in an inversion procedure to retrieve quantitative parameters that assess physiological and biological processes such as microcirculation, cerebral autoregulation, tissue metabolic rate of oxygen, and oxygen extraction fraction. Within the assumption of "small" capillary blood flow velocity oscillations the model showed that the capillary and venous compartments "respond" to this input as low pass filters, characterized by two distinct impulse response functions. In this work, we do not make the assumption of "small" perturbations of capillary blood flow velocity by solving without approximations the partial differential equation that governs the spatio-temporal behavior of hemoglobin saturation in capillary and venous blood. Preliminary comparison between the linear time-invariant model and the extended model (here identified as nonlinear model) are shown for the relevant parameters measured in CHS as a function of the oscillation frequency (CHS spectra). We have found that for capillary blood flow velocity oscillations with amplitudes up to 10% of the baseline value (which reflect typical scenarios in CHS), the discrepancies between CHS spectra obtained with the linear and nonlinear models are negligible. For larger oscillations (~50%) the linear and nonlinear models yield CHS spectra with differences within typical experimental errors, but further investigation is needed to assess the effect of these differences. Flow oscillations larger than 10-20% are not typically induced in CHS; therefore, the results presented in this work indicate that a linear hemodynamic model, combined with a method to elicit controlled hemodynamic oscillations (as done for CHS), is appropriate for the quantitative assessment of cerebral microcirculation.

Implantable, multifunctional, bioresorbable optics.

Advances in personalized medicine are symbiotic with the development of novel technologies for biomedical devices. We present an approach that combines enhanced imaging of malignancies, therapeutics, and feedback about therapeutics in a single implantable, biocompatible, and resorbable device. This confluence of form and function is accomplished by capitalizing on the unique properties of silk proteins as a mechanically robust, biocompatible, optically clear biomaterial matrix that can house, stabilize, and retain the function of therapeutic components. By developing a form of high-quality microstructured optical elements, improved imaging of malignancies and of treatment monitoring can be achieved. The results demonstrate a unique family of devices for in vitro and in vivo use that provide functional biomaterials with built-in optical signal and contrast enhancement, demonstrated here with simultaneous drug delivery and feedback about drug delivery with no adverse biological effects, all while slowly degrading to regenerate native tissue.

Validation of a novel hemodynamic model for coherent hemodynamics spectroscopy (CHS) and functional brain studies with fNIRS and fMRI.

We report an experimental validation and applications of the new hemodynamic model presented in the companion article (Fantini, 2014-this issue) both in the frequency domain and in the time domain. In the frequency domain, we have performed diffuse optical measurements for coherent hemodynamics spectroscopy (CHS) on the brain and calf muscle of human subjects, showing that the hemodynamic model predictions (both in terms of spectral shapes and absolute spectral values) are confirmed experimentally. We show how the quantitative analysis based on the new model allows for autoregulation measurements from brain data, and provides an analytical description of near-infrared spiroximetry from muscle data. In the time domain, we have used data from the literature to perform a comparison between brain activation signals measured with functional near-infrared spectroscopy (fNIRS) or with blood oxygenation level dependent (BOLD) fMRI, and the corresponding signals predicted by the new model. This comparison shows an excellent agreement between the model predictions and the reported fNIRS and BOLD fMRI signals. This new hemodynamic model provides a valuable tool for brain studies with hemodynamic-based techniques.

Pulsatile microvascular cerebral blood flow waveforms change with intracranial compliance and age.

Significance: Diffuse correlation spectroscopy (DCS) is an optical method to measure relative changes in cerebral blood flow (rCBF) in the microvasculature. Each heartbeat generates a pulsatile signal with distinct morphological features that we hypothesized to be related to intracranial compliance (ICC). Aim: We aim to study how three features of the pulsatile rCBF waveforms: the augmentation index (AIx), the pulsatility index, and the area under the curve, change with respect to ICC. We describe ICC as a combination of vascular compliance and extravascular compliance. Approach: Since patients with Chiari malformations (CM) (n=30) have been shown to have altered extravascular compliance, we compare the morphology of rCBF waveforms in CM patients with age-matched healthy control (n=30). Results: AIx measured in the supine position was significantly less in patients with CM compared to healthy controls (p<0.05). Since physiologic aging also leads to changes in vessel stiffness and intravascular compliance, we evaluate how the rCBF waveform changes with respect to age and find that the AIx feature was strongly correlated with age (Rhealthy subjects=-0.63, Rpreoperative CM patient=-0.70, and Rpostoperative CM patients=-0.62, p<0.01). Conclusions: These results suggest that the AIx measured in the cerebral microvasculature using DCS may be correlated to changes in ICC.

Cerebrovascular impedance estimation with near-infrared and diffuse correlation spectroscopy.

Significance: Cerebrovascular impedance (CVI) is related to cerebral autoregulation (CA), which is the mechanism of the brain to maintain near-constant cerebral blood flow (CBF) despite changes in cerebral perfusion pressure (CPP). Changes in blood vessel impedance enable the stabilization of blood flow. Due to the interplay between CVI and CA, assessment of CVI may enable quantification of CA and may serve as a biomarker for cerebral health. Aim: We developed a method to quantify CVI based on a combination of diffuse correlation spectroscopy (DCS) and continuous wave (CW) near-infrared spectroscopy (NIRS). Data on healthy human volunteers were used to validate the method. Approach: A combined high-speed DCS-NIRS system was developed, allowing for simultaneous, noninvasive blood flow, and volume measurements in the same tissue compartment. Blood volume was used as a surrogate measurement for blood pressure and CVI was calculated as the spectral ratio of blood volume and blood flow changes. This technique was validated on six healthy human volunteers undergoing postural changes to elicit CVI changes. Results: Averaged across the six subjects, a decrease in CVI was found for a head of bed (HOB) tilting of - 40 deg . These impedance changes were reversed when returning to the horizontal (0 deg) HOB baseline. Conclusions: We developed a combined DCS-NIRS system, which measures CBF and volume changes, which we demonstrate can be used to measure CVI. Using CVI as a metric of CA may be beneficial for assessing cerebral health, especially in patients where CPP is altered.

Scaling of Algorithmic Bias in Pulse Oximetry with Signal-to-Noise Ratio.

Recent work has noted a skin-color bias in existing pulse oximetry systems in their estimation of arterial oxygen saturation. Frequently, the algorithm used by these systems estimate a "ratio-of-ratios", called the "R-value", on their way to estimating the oxygen saturation. In this work, we focus on an "SNR-related" bias that is due to noise in measurements. We derive expressions for the SNR-related bias in R-value estimation, and observe how it scales with the signal-to-noise ratio (SNR). We show that the bias can arise at two steps of R-value estimation: in estimating the max and min of a pulsatile signal, and, additionally in taking ratios to estimate the R-value. We assess the bias resulting from the combination of the two steps, but also separate out contributions of each step. By doing so, we deduce that the bias induced in max and min estimation is likely to dominate. Because the SNR tends to get worse with higher melanin concentration, our result provides a sense of scaling of this bias with melanin concentration.

Evaluating feasibility of functional near-infrared spectroscopy in dolphins.

Significance: Using functional near-infrared spectroscopy (fNIRS) in bottlenose dolphins (Tursiops truncatus) could help to understand how echolocating animals perceive their environment and how they focus on specific auditory objects, such as fish, in noisy marine settings. Aim: To test the feasibility of near-infrared spectroscopy (NIRS) in medium-sized marine mammals, such as dolphins, we modeled the light propagation with computational tools to determine the wavelengths, optode locations, and separation distances that maximize sensitivity to brain tissue. Approach: Using frequency-domain NIRS, we measured the absorption and reduced scattering coefficient of dolphin sculp. We assigned muscle, bone, and brain optical properties from the literature and modeled light propagation in a spatially accurate and biologically relevant model of a dolphin head, using finite-element modeling. We assessed tissue sensitivities for a range of wavelengths (600 to 1700 nm), source-detector distances (50 to 120 mm), and animal sizes (juvenile model 25% smaller than adult). Results: We found that the wavelengths most suitable for imaging the brain fell into two ranges: 700 to 900 nm and 1100 to 1150 nm. The optimal location for brain sensing positioned the center point between source and detector 30 to 50 mm caudal of the blowhole and at an angle 45 deg to 90 deg lateral off the midsagittal plane. Brain tissue sensitivity comparable to human measurements appears achievable only for smaller animals, such as juvenile bottlenose dolphins or smaller species of cetaceans, such as porpoises, or with source-detector separations ≫100 mm in adult dolphins. Conclusions: Brain measurements in juvenile or subadult dolphins, or smaller dolphin species, may be possible using specialized fNIRS devices that support optode separations of >100 mm. We speculate that many measurement repetitions will be required to overcome hemodynamic signals originating predominantly from the muscle layer above the skull. NIRS measurements of muscle tissue are feasible today with source-detector separations of 50 mm, or even less.

Cerebrovascular Impedance as a Function of Cerebral Perfusion Pressure.

Goal: Cerebrovascular impedance is modulated by a vasoactive autoregulative mechanism in response to changes in cerebral perfusion pressure. Characterization of impedance and the limits of autoregulation are important biomarkers of cerebral health. We developed a method to quantify impedance based on the spectral content of cerebral blood flow and volume at the cardiac frequency, measured with diffuse optical methods. Methods: In three non-human primates, we modulated cerebral perfusion pressure beyond the limits of autoregulation. Cerebral blood flow and volume were measured with diffuse correlation spectroscopy and near-infrared spectroscopy, respectively. Results: We show that impedance can be used to identify the lower and upper limits of autoregulation. Conclusions: This impedance method may be an alternative method to measure autoregulation and a way of assessing cerebral health non-invasively at the clinical bedside.

Self-calibrated pulse oximetry algorithm based on photon pathlength change and the application in human freedivers.

Significance: Pulse oximetry estimates the arterial oxygen saturation of hemoglobin (SaO2) based on relative changes in light intensity at the cardiac frequency. Commercial pulse oximeters require empirical calibration on healthy volunteers, resulting in limited accuracy at low oxygen levels. An accurate, self-calibrated method for estimating SaO2 is needed to improve patient monitoring and diagnosis. Aim: Given the challenges of calibration at low SaO2 levels, we pursued the creation of a self-calibrated algorithm that can effectively estimate SaO2 across its full range. Our primary objective was to design and validate our calibration-free method using data collected from human subjects. Approach: We developed an algorithm based on diffuse optical spectroscopy measurements of cardiac pulses and the modified Beer-Lambert law (mBLL). Recognizing that the photon mean pathlength (⟨L⟩) varies with SaO2 related absorption changes, our algorithm aligns/fits the normalized ⟨L⟩ (across wavelengths) obtained from optical measurements with its analytical representation. We tested the algorithm with human freedivers performing breath-hold dives. A continuous-wave near-infrared spectroscopy probe was attached to their foreheads, and an arterial cannula was inserted in the radial artery to collect arterial blood samples at different stages of the dive. These samples provided ground-truth SaO2 via a blood gas analyzer, enabling us to evaluate the accuracy of SaO2 estimation derived from the NIRS measurement using our self-calibrated algorithm. Results: The self-calibrated algorithm significantly outperformed the conventional method (mBLL with a constant ⟨L⟩ ratio) for SaO2 estimation through the diving period. Analyzing 23 ground-truth SaO2 data points ranging from 41% to 100%, the average absolute difference between the estimated SaO2 and the ground truth SaO2 is 4.23%±5.16% for our algorithm, significantly lower than the 11.25%±13.74% observed with the conventional approach. Conclusions: By factoring in the variations in the spectral shape of ⟨L⟩ relative to SaO2, our self-calibrated algorithm enables accurate SaO2 estimation, even in subjects with low SaO2 levels.

Clinical translation of noninvasive intracranial pressure sensing with diffuse correlation spectroscopy.

OBJECTIVE: Intracranial pressure (ICP) is an important therapeutic target in many critical neuropathologies. The current tools for ICP measurements are invasive; hence, these are only selectively applied in critical cases where the benefits surpass the risks. To address the need for low-risk ICP monitoring, the authors developed a noninvasive alternative. METHODS: The authors recently demonstrated noninvasive quantification of ICP in an animal model by using morphological analysis of microvascular cerebral blood flow (CBF) measured with diffuse correlation spectroscopy (DCS). The current prospective observational study expanded on this preclinical study by translating the method to pediatric patients. Here, the CBF features, along with mean arterial pressure (MAP) and heart rate (HR) data, were used to build a random decision forest, machine learning model for estimation of ICP; the results of this model were compared with those of invasive monitoring. RESULTS: Fifteen patients (mean age ± SD [range] 9.8 ± 5.1 [0.3-17.5] years; median age [interquartile range] 11 [7.4] years; 10 males and 5 females) who underwent invasive neuromonitoring for any purpose were enrolled. Estimated ICP (ICPest) very closely matched invasive ICP (ICPinv), with a root mean square error (RMSE) of 1.01 mm Hg and 95% limit of agreement of ≤ 1.99 mm Hg for ICPinv 0.01-41.25 mm Hg. When the ICP range (ICPinv 0.01-29.05 mm Hg) was narrowed on the basis of the sample population, both RMSE and limit of agreement improved to 0.81 mm Hg and ≤ 1.6 mm Hg, respectively. In addition, 0.3% of the test samples for ICPinv ≤ 20 mm Hg and 5.4% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg, which may be considered the acceptable limit of agreement for clinical validity of ICP sensing. For the narrower case, 0.1% of test samples for ICPinv ≤ 20 mm Hg and 1.1% of the test samples for ICPinv > 20 mm Hg had a limit of agreement > 5 mm Hg. Although the CBF features were crucial, the best prediction accuracy was achieved when these features were combined with MAP and HR data. Lastly, preliminary leave-one-out analysis showed model accuracy with an RMSE of 6 mm Hg and limit of agreement of ≤ 7 mm Hg. CONCLUSIONS: The authors have shown that DCS may enable ICP monitoring with additional clinical validation. The lower risk of such monitoring would allow ICP to be estimated for a wide spectrum of indications, thereby both reducing the use of invasive monitors and increasing the types of patients who may benefit from ICP-directed therapies.

Normative database of judgment of complexity task with functional near infrared spectroscopy--application for TBI.

The ability to assess frontal lobe function in a rapid, objective, and standardized way, without the need for expertise in cognitive test administration might be particularly helpful in mild traumatic brain injury (TBI), where objective measures are needed. Functional near infrared spectroscopy (fNIRS) is a reliable technique to noninvasively measure local hemodynamic changes in brain areas near the head surface. In this paper, we are combining fNIRS and frameless stereotaxy which allowed us to co-register the functional images with previously acquired anatomical MRI volumes. In our experiment, the subjects were asked to perform a task, evaluating the complexity of daily life activities, previously shown with fMRI to activate areas of the anterior frontal cortex. We reconstructed averaged oxyhemoglobin and deoxyhemoglobin data from 20 healthy subjects in a spherical coordinate. The spherical coordinate is a natural representation of surface brain activation projection. Our results show surface activation projected from the medial frontopolar cortex which is consistent with previous fMRI results. With this original technique, we will construct a normative database for a simple cognitive test which can be useful in evaluating cognitive disability such as mild traumatic brain injury.

Erratum: Estimating intracranial pressure using pulsatile cerebral blood flow measured with diffuse correlation spectroscopy: erratum.

[This corrects the article on p. 1462 in vol. 11, PMID: 32206422.].

Review of optical methods for fetal monitoring in utero.

The current technology for monitoring fetal wellbeing during child birth is cardiotocography. However, CTG has high false positive rates that lead to unnecessary emergency Cesarean deliveries and false negatives that result in birth injuries. To curtail these issues, fetal pulse oximetery has been a topic of interest for many decades. Fetal pulse oximetry would yield the oxygen saturation of the fetus in utero and provide a more robust marker for clinicians to make decisions about performing emergency Cesarean deliveries. Here, we present a review of biomedical optical developments related to transabdominal fetal pulse oximetery in the biophotonics field and the challenges that must be overcome to make transabdominal pulse oximetry a clinical reality.

Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy.

Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow.

Changes in neurovascular coupling with cerebral perfusion pressure indicate a link to cerebral autoregulation.

Cerebral autoregulation ensures a stable average blood supply to brain tissue across steady state cerebral perfusion pressure (CPP) levels. Neurovascular coupling, in turn, relies on sufficient blood flow to meet neuronal demands during activation. These mechanisms break down in pathologies where extreme levels of CPP can cause dysregulation in cerebral blood flow. Here, we experimentally tested the influence of changes in CPP on neurovascular coupling in a hydrocephalus-type non-human primate model (n = 3). We recorded local neural and vascular evoked responses to a checkerboard visual stimulus, non-invasively, using electroencephalography and near-infrared spectroscopy respectively. The evoked signals showed changes in various waveform features in the visual evoked potentials and the hemodynamic responses, with CPP. We further used these signals to fit for a hemodynamic response function (HRF) to describe neurovascular coupling. We estimated n = 26 distinct HRFs at a subset of CPP values ranging from 40-120 mmHg across all subjects. The HRFs, when compared to a subject dependent healthy baseline (CPP 70-90 mmHg) HRF, showed significant changes in shape with increasing CPP (ρCPP = -0.55, p-valueCPP = 0.0049). Our study provides preliminary experimental evidence on the relationship between neurovascular coupling and CPP changes, especially when beyond the limits of static autoregulation.