Validation of the hypercapnic calibrated fMRI method using DOT-fMRI fusion imaging.

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. A subsequent acquisition is then required during which the subject inhales carbon dioxide for short periods of time. A calibration constant, typically labeled M, is then estimated from the hypercapnic data and is subsequently used together with the BOLD-ASL recordings to compute evoked changes in CMRO2 during the functional task. The computation of M assumes a constant CMRO2 during the CO2 inhalation, an assumption that has been questioned since the origin of calibrated fMRI. In this study we used diffuse optical tomography (DOT) together with BOLD and ASL--an alternative calibration method that does not require any gas manipulation and therefore no constant CMRO2 assumption--to cross-validate the estimation of M obtained from a traditional hypercapnic calibration. We found a high correlation between the M values (R=0.87, p<0.01) estimated using these two approaches. The findings serve to validate the hypercapnic fMRI calibration technique and suggest that the inter-subject variability routinely obtained for M is reproducible with an alternative method and might therefore reflect inter-subject physiological variability.

Reducing motion artifacts for long-term clinical NIRS monitoring using collodion-fixed prism-based optical fibers.

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. The method provides improved optode-scalp coupling through the use of miniaturized optical fiber tips fixed to the scalp using collodion, a clinical adhesive. We investigate and quantify the performance of this new method in minimizing motion artifacts in healthy subjects, and apply the technique to allow continuous NIRS monitoring throughout epileptic seizures in two epileptic in-patients. Using collodion-fixed fibers reduces the percent signal change of motion artifacts by 90% and increases the SNR by 6 and 3 fold at 690 and 830 nm wavelengths respectively when compared to a standard Velcro-based array of optical fibers. The SNR has also increased by 2 fold during rest conditions without motion with the new probe design because of better light coupling between the fiber and scalp. The change in both HbO and HbR during motion artifacts is found to be statistically lower for the collodion-fixed fiber probe. The collodion-fixed optical fiber approach has also allowed us to obtain good quality NIRS recording of three epileptic seizures in two patients despite excessive motion in each case.

Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data.

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. However, in most experimental circumstances the number of trials is limited, and multiple motion artifacts are common, particularly in challenging populations. Many methods have been proposed recently to correct for motion artifacts, including principle component analysis, spline interpolation, Kalman filtering, wavelet filtering and correlation-based signal improvement. The performance of different techniques has been often compared in simulations, but only rarely has it been assessed on real functional data. Here, we compare the performance of these motion correction techniques on real functional data acquired during a cognitive task, which required the participant to speak aloud, leading to a low-frequency, low-amplitude motion artifact that is correlated with the hemodynamic response. To compare the efficacy of these methods, objective metrics related to the physiology of the hemodynamic response have been derived. Our results show that it is always better to correct for motion artifacts than reject trials, and that wavelet filtering is the most effective approach to correcting this type of artifact, reducing the area under the curve where the artifact is present in 93% of the cases. Our results therefore support previous studies that have shown wavelet filtering to be the most promising and powerful technique for the correction of motion artifacts in fNIRS data. The analyses performed here can serve as a guide for others to objectively test the impact of different motion correction algorithms and therefore select the most appropriate for the analysis of their own fNIRS experiment.

In situ brain tumor detection using a Raman spectroscopy system-results of a multicenter study.

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. The Sentry System is a new real time, in situ brain tumor detection device that merges Raman spectroscopy with machine learning tissue classifiers. Nine hundred and seventy-six in situ spectroscopy measurements and colocalized tissue specimens were acquired from 67 patients undergoing surgery for glioblastoma, brain metastases, or meningioma to assess tumor classification. The device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. These data show that the Sentry System discriminated tumor containing tissue from non-tumoral brain in real time and prior to resection.

Experimental activation of the sphenopalatine ganglion provokes cluster-like attacks in humans.

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. METHODS: In a double-blind randomized cross-over study, seven CH patients implanted with an SPG neurostimulator were randomly allocated to receive HF or LF stimulation for 3 min on 2 separate days. We recorded headache characteristics and autonomic symptoms during and after stimulation. RESULTS: Six patients completed the study. Three out of six patients (50%) reported ipsilateral cluster-like attacks during or within 30 min of LF SPG stimulation. These cluster-like attacks were all successfully treated with the therapeutic HF SPG stimulation. One out of six reported a cluster-like attack with 3 min HF SPG stimulation, which was also successfully treated with continued HF therapeutic SPG stimulation. DISCUSSION: LF SPG stimulation may induce cluster-like attacks with autonomic features, which can subsequently be treated by HF SPG stimulation. Efferent parasympathetic outflow from the SPG may initiate autonomic symptoms and activate trigeminovascular sensory afferents, which may initiate the onset of pain associated with CH.

Quantification of the cortical contribution to the NIRS signal over the motor cortex using concurrent NIRS-fMRI measurements.

Near-Infrared Spectroscopy (NIRS) measures the functional hemodynamic response occurring at the surface of the cortex. Large pial veins are located above the surface of the cerebral cortex. Following activation, these veins exhibit oxygenation changes but their volume likely stays constant. The back-reflection geometry of the NIRS measurement renders the signal very sensitive to these superficial pial veins. As such, the measured NIRS signal contains contributions from both the cortical region as well as the pial vasculature. In this work, the cortical contribution to the NIRS signal was investigated using (1) Monte Carlo simulations over a realistic geometry constructed from anatomical and vascular MRI and (2) multimodal NIRS-BOLD recordings during motor stimulation. A good agreement was found between the simulations and the modeling analysis of in vivo measurements. Our results suggest that the cortical contribution to the deoxyhemoglobin signal change (ΔHbR) is equal to 16-22% of the cortical contribution to the total hemoglobin signal change (ΔHbT). Similarly, the cortical contribution of the oxyhemoglobin signal change (ΔHbO) is equal to 73-79% of the cortical contribution to the ΔHbT signal. These results suggest that ΔHbT is far less sensitive to pial vein contamination and therefore, it is likely that the ΔHbT signal provides better spatial specificity and should be used instead of ΔHbO or ΔHbR to map cerebral activity with NIRS. While different stimuli will result in different pial vein contributions, our finger tapping results do reveal the importance of considering the pial contribution.

Low frequency oscillations in cephalic vessels assessed by near infrared spectroscopy.

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). The direct left-right phase shifts of oxyHb and Vmca were also assessed. We examined 44 healthy volunteers by simultaneous recordings of ABP, oxyHb and Vmca during spontaneous and paced breathing at 6 breaths per minute on two separate days. RESULTS: The variation between hemispheres had a prediction interval (PI) of ± 39° for ABP-oxyHb phase shift and ± 69% for gain. ABP-Vmca showed ± 57° PI phase shift and ± 158% PI for gain. The variation from day to day showed ± 61° PI for ABP-oxyHb phase shift and ± 297% PI for gain. ABP-Vmca showed ± 45° PI phase shift and ± 166% PI for gain. We found a linear relation between phase shift of oxyHb and Vmca at paced breathing (P=0.0005), but not at rest (P=0.235). CONCLUSION: Our results show that LFO phase shift ABP-oxyHb may be used as a robust measurement of differences in autoregulation between hemispheres and over time. In addition, we found a strong relation between oxyHb and Vmca during paced breathing. Gain showed too large variation for clinical use, as the SD was up to 100-fold of mean values.

Nitric oxide modulation of low-frequency oscillations in cortical vessels in FHM--a NIRS study.

BACKGROUND: The pathophysiological alterations in patients with familial hemiplegic migraine (FHM) are not yet fully known. The headache characteristics in patients with FHM mutations have been examined in a series of glyceryl trinitrate (GTN) provocation studies in FHM patients, but the cortical vascular response to GTN in FHM patients has never been investigated before. OBJECTIVE: To investigate changes in spontaneous low-frequency oscillations (LFO) of cortical vessels in response to the nitric oxide donor GTN by near-infrared spectroscopy in FHM patients. METHODS: Twenty-three FHM patients without known mutations and 9 healthy controls received a continuous intravenous infusion of GTN 0.5 µg/kg/minute over 20 minutes. Using near-infrared spectroscopy, we recorded oxygenated hemoglobin (oxyHb) LFO amplitude bilateral at the frontal cortex at baseline and 15 minutes and 40 minutes after start of the GTN infusion. RESULTS: GTN changed oxyHb LFO amplitude in FHM patients (P = .002), but not in healthy controls (P = .121). Only in FHM patients with coexisting common migraine types did GTN infusion induced changes in LFO amplitudes (P < .001), where post-hoc analysis revealed an increase in LFO amplitude 15 minutes (P = .003) and 40 (P = .013) minutes after start of infusion compared with baseline. Interestingly, GTN infusion induced no changes in LFO amplitude in patients with a pure FHM phenotype (P = .695). CONCLUSION: FHM patients with a mixed phenotype (coexisting common type of migraine) showed an increase in oxyHb LFO amplitude during GTN infusion, whereas FHM patients with pure phenotype showed no changes. These data suggest possible differences in frontal cortical nitric oxide vascular sensitivity between FHM patients with a mixed phenotype and patients with pure FHM.

Combined optical and X-ray tomosynthesis breast imaging.

PURPOSE: To explore the optical and physiologic properties of normal and lesion-bearing breasts by using a combined optical and digital breast tomosynthesis (DBT) imaging system. MATERIALS AND METHODS: Institutional review board approval and patient informed consent were obtained for this HIPAA-compliant study. Combined optical and tomosynthesis imaging analysis was performed in 189 breasts from 125 subjects (mean age, 56 years ± 13 [standard deviation]), including 138 breasts with negative findings and 51 breasts with lesions. Three-dimensional (3D) maps of total hemoglobin concentration (Hb(T)), oxygen saturation (So(2)), and tissue reduced scattering coefficients were interpreted by using the coregistered DBT images. Paired and unpaired t tests were performed between various tissue types to identify significant differences. RESULTS: The estimated average bulk Hb(T) from 138 normal breasts was 19.2 µmol/L. The corresponding mean So(2) was 0.73, within the range of values in the literature. A linear correlation (R = 0.57, P < .0001) was found between Hb(T) and the fibroglandular volume fraction derived from the 3D DBT scans. Optical reconstructions of normal breasts revealed structures corresponding to chest-wall muscle, fibroglandular, and adipose tissues in the Hb(T), So(2), and scattering images. In 26 malignant tumors of 0.6-2.5 cm in size, Hb(T) was significantly greater than that in the fibroglandular tissue of the same breast (P = .0062). Solid benign lesions (n = 17) and cysts (n = 8) had significantly lower Hb(T) contrast than did the malignant lesions (P = .025 and P = .0033, respectively). CONCLUSION: The optical and DBT images were structurally consistent. The malignant tumors and benign lesions demonstrated different Hb(T) and scattering contrasts, which can potentially be exploited to reduce the false-positive rate of conventional mammography and unnecessary biopsies.

Spontaneous low-frequency oscillations in cerebral vessels: applications in carotid artery disease and ischemic stroke.

The etiology behind and physiological significance of spontaneous oscillations in the low-frequency spectrum in both systemic and cerebral vessels remain unknown. Experimental studies have proposed that spontaneous oscillations in cerebral blood flow reflect impaired cerebral autoregulation (CA). Analysis of CA by measurement of spontaneous oscillations in the low-frequency spectrum in cerebral vessels might be a useful tool for assessing risk and investigating different treatment strategies in carotid artery disease (CAD) and stroke. We reviewed studies exploring spontaneous oscillations in the low-frequency spectrum in patients with CAD and ischemic stroke, conditions known to involve impaired CA. Several studies have reported changes in oscillations after CAD and stroke after surgery and over time compared with healthy controls. Phase shift in the frequency domain and correlation coefficients in the time domain are the most frequently used parameters for analyzing spontaneous oscillations in systemic and cerebral vessels. At present, there is no gold standard for analyzing spontaneous oscillations in the low-frequency spectrum, and simplistic models of CA have failed to predict or explain the spontaneous oscillation changes found in CAD and stroke studies. Near-infrared spectroscopy is suggested as a future complementary tool for assessing changes affecting the cortical arterial system.

Experimental validation of a spectroscopic Monte Carlo light transport simulation technique and Raman scattering depth sensing analysis in biological tissue.

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. APPROACH: A new Monte Carlo (MC) package was developed to simulate absorption, fluorescence, elastic, and inelastic scattering of light in tissue. The validity of the MC algorithm was demonstrated by comparison with experimental Raman spectra in phantoms of known optical properties using nylon and polydimethylsiloxane as Raman-active compounds. A series of MC simulations were performed to study the effects of optical properties on Raman sensing depth for an imaging geometry consistent with single-point detection using a handheld fiber optics probe system. RESULTS: The MC code was used to estimate the Raman sensing depth of a handheld fiber optics system. For absorption and reduced scattering coefficients of 0.001 and 1 mm - 1, the sensing depth varied from 105 to 225 µm for a range of Raman probabilities from 10 - 6 to 10 - 3. Further, for a realistic Raman probability of 10 - 6, the sensing depth ranged between 10 and 600 µm for the range of absorption coefficients 0.001 to 1.4 mm - 1 and reduced scattering coefficients of 0.5 to 30 mm - 1. CONCLUSIONS: A spectroscopic MC light transport simulation platform was developed and validated against experimental measurements in tissue phantoms and used to predict depth sensing in tissue. It is hoped that the current package and reported results provide the research community with an effective simulating tool to improve the development of clinical applications of RS.

Erratum: Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients.

[This corrects the article DOI: 10.1117/1.NPh.5.4.045005.].

Dynamic brain-body coupling of breath-by-breath O2-CO2 exchange ratio with resting state cerebral hemodynamic fluctuations.

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 0.008-0.03Hz in healthy adults. bER is defined as the ratio of the change in the partial pressure of oxygen (ΔPO2) to that of carbon dioxide (ΔPCO2) between end inspiration and end expiration. In this study, we aimed to investigate the contribution of respiratory gas exchange (RGE) metrics (bER, ΔPO2 and ΔPCO2) to low frequency CHF during spontaneous breathing. METHODS: Twenty-two healthy adults were included. We used transcranial Doppler sonography to evaluate CHF by measuring the changes in cerebral blood flow velocity (ΔCBFv) in bilateral middle cerebral arteries. The regional CHF were mapped with blood oxygenation level dependent (ΔBOLD) signal changes using functional magnetic resonance imaging. Temporal features and frequency characteristics of RGE metrics during spontaneous breathing were examined, and the simultaneous measurements of RGE metrics and CHF (ΔCBFv and ΔBOLD) were studied for their correlation. RESULTS: We found that the time courses of ΔPO2 and ΔPCO2 were interdependent but not redundant. The oscillations of RGE metrics were coherent with resting state CHF at the frequency range of 0.008-0.03Hz. Both bER and ΔPO2 were superior to ΔPCO2 in association with CHF while CHF could correlate more strongly with bER than with ΔPO2 in some brain regions. Brain regions with the strongest coupling between bER and ΔBOLD overlapped with many areas of default mode network including precuneus and posterior cingulate. CONCLUSION: Although the physiological mechanisms underlying the strong correlation between bER and CHF are unclear, our findings suggest the contribution of bER to low frequency resting state CHF, providing a novel insight of brain-body interaction via CHF and oscillations of RGE metrics.

Cerebrovascular reactivity assessment with O2-CO2 exchange ratio under brief breath hold challenge.

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. We aimed to investigate whether bER is a more useful index than end-tidal PCO2 to characterize cerebrovascular reactivity (CVR) under BH challenge. METHODS: We used transcranial Doppler ultrasound (TCD) to evaluate CHR under BH challenge by measuring cerebral blood flow velocity (CBFv) in the middle cerebral arteries. Regional changes in CHR to BH and exogenous CO2 challenges were mapped with blood oxygenation level dependent (BOLD) signal changes using functional magnetic resonance imaging (fMRI). We correlated respiratory gas exchange (RGE) metrics (bER, ΔPO2, ΔPCO2, end-tidal PCO2 and PO2, and time of breaths) with CHR (CBFv and BOLD) to BH challenge. Temporal features and frequency characteristics of RGE metrics and their coherence with CHR were examined. RESULTS: CHR to brief BH epochs and free breathing were coupled with both ΔPO2 and ΔPCO2. We found that bER was superior to either ΔPO2 or ΔPCO2 alone in coupling with the changes of CBFv and BOLD signals under breath hold challenge. The regional CVR results derived by regressing BOLD signal changes on bER under BH challenge resembled those derived by regressing BOLD signal changes on end-tidal PCO2 under exogenous CO2 challenge. CONCLUSION: Our findings provide a novel insight on the potential of using bER to better quantify CVR changes under BH challenge.

Non-invasive methods for measuring vascular changes in neurovascular headaches.

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). Furthermore, the use of near-infrared spectroscopy in headache research is reviewed. Existing TCD studies of migraine and other headache disorders do not provide solid evidence for cerebral blood flow velocity changes during spontaneous attacks of migraine headache. SPECT studies have clearly shown cortical vascular changes following migraine aura and the differences between migraine with aura compared to migraine without aura. PET studies have shown focal activation in brain structures related to headache, but whether the changes are specific to different primary headaches have yet to be demonstrated. MR angiography has shown precise changes in large cerebral vessels during spontaneous migraine without aura attacks. Future development in more precise imaging methods may further elucidate the pathophysiological mechanisms in primary headaches.

Double-layer estimation of intra- and extracerebral hemoglobin concentration with a time-resolved system.

We present in vivo measurements of baseline physiology from five subjects with a four-wavelength (690, 750, 800, and 850 nm) time-resolved optical system. The measurements were taken at four distances: 10, 15, 25, and 30 mm. All distances were fit simultaneously with a two-layered analytical model for the absorption and reduced scattering coefficient of both layers. The thickness of the first layer, comprising the skin, scalp, and cerebrospinal fluid, was obtained from anatomical magnetic resonance images. The fitting procedure was first tested with simulations before being applied to in vivo measurements and verified that this procedure permits accurate characterization of the hemoglobin concentrations in the extra- and intracerebral tissues. Baseline oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations and oxygen saturation were recovered from in vivo measurements and compared to the literature. We observed a noticeable intersubject variability of the hemoglobin concentrations, but constant values for the cerebral hemoglobin oxygen saturation.

Prolonged monitoring of cerebral blood flow and autoregulation with diffuse correlation spectroscopy in neurocritical care patients.

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 ( CBF i ) 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 CBF i with DCS in at-risk patients in the Neurosciences Intensive Care Unit. DCS data were acquired continuously for up to 20 h in six patients with aneurysmal subarachnoid hemorrhage, as permitted by clinical care. Mean arterial blood pressure was recorded synchronously, allowing us to derive autoregulation curves and to compute an autoregulation index. The autoregulation curves suggest disrupted cerebral autoregulation in most patients, with the severity of disruption and the limits of preserved autoregulation varying between subjects. Our findings suggest the potential of the DCS modality for noninvasive, long-term monitoring of cerebral perfusion, and autoregulation.

Linear 3D reconstruction of time-domain diffuse optical imaging differential data: improved depth localization and lateral resolution.

We present 3D linear reconstructions of time-domain (TD) diffuse optical imaging differential data. We first compute the sensitivity matrix at different delay gates within the diffusion approximation for a homogeneous semi-infinite medium. The matrix is then inverted using spatially varying regularization. The performances of the method and the influence of a number of parameters are evaluated with simulated data and compared to continuous-wave (CW) imaging. In addition to the expected depth resolution provided by TD, we show improved lateral resolution and localization. The method is then applied to reconstructing phantom data consisting of an absorbing inclusion located at different depths within a scattering medium.

Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography.

We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatio-temporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition, localized changes are observed which correspond to the glandular region of the breast.

Functional Near Infrared Spectroscopy: Enabling Routine Functional Brain Imaging.

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. We then summarize the application areas that are experiencing rapid growth as fNIRS begins to enable routine functional brain imaging.