Resolution analysis of a volumetric coded aperture X-ray diffraction imaging system.

BACKGROUND: A coded aperture X-ray diffraction (XRD) imaging system can measure the X-ray diffraction form factor from an object in three dimensions -X, Y and Z (depth), broadening the potential application of this technology. However, to optimize XRD systems for specific applications, it is critical to understand how to predict and quantify system performance for each use case. OBJECTIVE: The purpose of this work is to present and validate 3D spatial resolution models for XRD imaging systems with a detector-side coded aperture. METHODS: A fan beam coded aperture XRD system was used to scan 3D printed resolution phantoms placed at various locations throughout the system's field of view. The multiplexed scatter data were reconstructed using a model-based iterative reconstruction algorithm, and the resulting volumetric images were evaluated using multiple resolution criteria to compare against the known phantom resolution. We considered the full width at half max and Sparrow criterion as measures of the resolution and compared our results against analytical resolution models from the literature as well as a new theory for predicting the system resolution based on geometric arguments. RESULTS: We show that our experimental measurements are bounded by the multitude of theoretical resolution predictions, which accurately predict the observed trends and order of magnitude of the spatial and form factor resolutions. However, we find that the expected and observed resolution can vary by approximately a factor of two depending on the choice of metric and model considered. We observe depth resolutions of 7-16 mm and transverse resolutions of 0.6-2 mm for objects throughout the field of view. Furthermore, we observe tradeoffs between the spatial resolution and XRD form factor resolution as a function of sample location. CONCLUSION: The theories evaluated in this study provide a useful framework for estimating the 3D spatial resolution of a detector side coded aperture XRD imaging system. The assumptions and simplifications required by these theories can impact the overall accuracy of describing a particular system, but they also can add to the generalizability of their predictions. Furthermore, understanding the implications of the assumptions behind each theory can help predict performance, as shown by our data's placement between the conservative and idealized theories, and better guide future systems for optimized designs.

Oxyhemoglobin and Cerebral Blood Flow Transients Detect Infarction in Rat Focal Brain Ischemia.

Spreading depolarizations (SD) refer to the near-complete depolarization of neurons that is associated with brain injuries such as ischemic stroke. The present gold standard for SD monitoring in humans is invasive electrocorticography (ECoG). A promising non-invasive alternative to ECoG is diffuse optical monitoring of SD-related flow and hemoglobin transients. To investigate the clinical utility of flow and hemoglobin transients, we analyzed their association with infarction in rat focal brain ischemia. Optical images of flow, oxy-hemoglobin, and deoxy-hemoglobin were continuously acquired with Laser Speckle and Optical Intrinsic Signal imaging for 2 h after photochemically induced distal middle cerebral artery occlusion in Sprague-Dawley rats (n = 10). Imaging was performed through a 6 × 6 mm window centered 3 mm posterior and 4 mm lateral to Bregma. Rats were sacrificed after 24 h, and the brain slices were stained for assessment of infarction. We mapped the infarcted area onto the imaging data and used nine circular regions of interest (ROI) to distinguish infarcted from non-infarcted tissue. Transients propagating through each ROI were characterized with six parameters (negative, positive, and total amplitude; negative and positive slope; duration). Transients were also classified into three morphology types (positive monophasic, biphasic, negative monophasic). Flow transient morphology, positive amplitude, positive slope, and total amplitude were all strongly associated with infarction (p < 0.001). Associations with infarction were also observed for oxy-hemoglobin morphology, oxy-hemoglobin positive amplitude and slope, and deoxy-hemoglobin positive slope and duration (all p < 0.01). These results suggest that flow and hemoglobin transients accompanying SD have value for detecting infarction.

Real-time tracking of brain oxygen gradients and blood flow during functional activation.

Significance: Cerebral metabolic rate of oxygen ( CMRO 2 ) consumption is a key physiological variable that characterizes brain metabolism in a steady state and during functional activation. Aim: We aim to develop a minimally invasive optical technique for real-time measurement of CMRO 2 concurrently with cerebral blood flow (CBF). Approach: We used a pair of macromolecular phosphorescent probes with nonoverlapping optical spectra, which were localized in the intra- and extravascular compartments of the brain tissue, thus providing a readout of oxygen gradients between these two compartments. In parallel, we measured CBF using laser speckle contrast imaging. Results: The method enables computation and tracking of CMRO 2 during functional activation with high temporal resolution ( ∼ 7 Hz ). In contrast to other approaches, our assessment of CMRO 2 does not require measurements of CBF or hemoglobin oxygen saturation. Conclusions: The independent records of intravascular and extravascular partial pressures of oxygen, CBF, and CMRO 2 provide information about the physiological events that accompany neuronal activation, creating opportunities for dynamic quantification of brain metabolism.

Application of machine learning classifiers to X-ray diffraction imaging with medically relevant phantoms.

PURPOSE: Recent studies have demonstrated the ability to rapidly produce large field of view X-ray diffraction (XRD) images, which provide rich new data relevant to the understanding and analysis of disease. However, work has only just begun on developing algorithms that maximize the performance toward decision-making and diagnostic tasks. In this study, we present the implementation of and comparison between rules-based and machine learning (ML) classifiers on XRD images of medically relevant phantoms to explore the potential for increased classification performance. METHODS: Medically relevant phantoms were utilized to provide well-characterized ground-truths for comparing classifier performance. Water and polylactic acid (PLA) plastic were used as surrogates for cancerous and healthy tissue, respectively, and phantoms were created with varying levels of spatial complexity and biologically relevant features for quantitative testing of classifier performance. Our previously developed X-ray scanner was used to acquire co-registered X-ray transmission and diffraction images of the phantoms. For classification algorithms, we explored and compared two rules-based classifiers (cross-correlation, or matched-filter, and linear least-squares unmixing) and two ML classifiers (support vector machines and shallow neural networks). Reference XRD spectra (measured by a commercial diffractometer) were provided to the rules-based algorithms, while 60% of the measured XRD pixels were used for training of the ML algorithms. The area under the receiver operating characteristic curve (AUC) was used as a comparative metric between the classification algorithms, along with the accuracy performance at the midpoint threshold for each classifier. RESULTS: The AUC values for material classification were 0.994 (cross-correlation [CC]), 0.994 (least-squares [LS]), 0.995 (support vector machine [SVM]), and 0.999 (shallow neural network [SNN]). Setting the classification threshold to the midpoint for each classifier resulted in accuracy values of CC = 96.48%, LS = 96.48%, SVM = 97.36%, and SNN = 98.94%. If only considering pixels ±3 mm from water-PLA boundaries (where partial volume effects could occur due to imaging resolution limits), the classification accuracies were CC = 89.32%, LS = 89.32%, SVM = 92.03%, and SNN = 96.79%, demonstrating an even larger improvement produced by the machine-learned algorithms in spatial regions critical for imaging tasks. Classification by transmission data alone produced an AUC of 0.773 and accuracy of 85.45%, well below the performance levels of any of the classifiers applied to XRD image data. CONCLUSIONS: We demonstrated that ML-based classifiers outperformed rules-based approaches in terms of overall classification accuracy and improved the spatially resolved classification performance on XRD images of medical phantoms. In particular, the ML algorithms demonstrated considerably improved performance whenever multiple materials existed in a single voxel. The quantitative performance gains demonstrate an avenue to extract and harness XRD imaging data to improve material analysis for research, industrial, and clinical applications.

X-ray fan beam coded aperture transmission and diffraction imaging for fast material analysis.

X-ray transmission imaging has been used in a variety of applications for high-resolution measurements based on shape and density. Similarly, X-ray diffraction (XRD) imaging has been used widely for molecular structure-based identification of materials. Combining these X-ray methods has the potential to provide high-resolution material identification, exceeding the capabilities of either modality alone. However, XRD imaging methods have been limited in application by their long measurement times and poor spatial resolution, which has generally precluded combined, rapid measurements of X-ray transmission and diffraction. In this work, we present a novel X-ray fan beam coded aperture transmission and diffraction imaging system, developed using commercially available components, for rapid and accurate non-destructive imaging of industrial and biomedical specimens. The imaging system uses a 160 kV Bremsstrahlung X-ray source while achieving a spatial resolution of ≈ 1 × 1 mm2 and a spectral accuracy of > 95% with only 15 s exposures per 150 mm fan beam slice. Applications of this technology are reported in geological imaging, pharmaceutical inspection, and medical diagnosis. The performance of the imaging system indicates improved material differentiation relative to transmission imaging alone at scan times suitable for a variety of industrial and biomedical applications.

Blood flow response to orthostatic challenge identifies signatures of the failure of static cerebral autoregulation in patients with cerebrovascular disease.

BACKGROUND: The cortical microvascular cerebral blood flow response (CBF) to different changes in head-of-bed (HOB) position has been shown to be altered in acute ischemic stroke (AIS) by diffuse correlation spectroscopy (DCS) technique. However, the relationship between these relative ΔCBF changes and associated systemic blood pressure changes has not been studied, even though blood pressure is a major driver of cerebral blood flow. METHODS: Transcranial DCS data from four studies measuring bilateral frontal microvascular cerebral blood flow in healthy controls (n = 15), patients with asymptomatic severe internal carotid artery stenosis (ICA, n = 27), and patients with acute ischemic stroke (AIS, n = 72) were aggregated. DCS-measured CBF was measured in response to a short head-of-bed (HOB) position manipulation protocol (supine/elevated/supine, 5 min at each position). In a sub-group (AIS, n = 26; ICA, n = 14; control, n = 15), mean arterial pressure (MAP) was measured dynamically during the protocol. RESULTS: After elevated positioning, DCS CBF returned to baseline supine values in controls (p = 0.890) but not in patients with AIS (9.6% [6.0,13.3], mean 95% CI, p < 0.001) or ICA stenosis (8.6% [3.1,14.0], p = 0.003)). MAP in AIS patients did not return to baseline values (2.6 mmHg [0.5, 4.7], p = 0.018), but in ICA stenosis patients and controls did. Instead ipsilesional but not contralesional CBF was correlated with MAP (AIS 6.0%/mmHg [- 2.4,14.3], p = 0.038; ICA stenosis 11.0%/mmHg [2.4,19.5], p < 0.001). CONCLUSIONS: The observed associations between ipsilateral CBF and MAP suggest that short HOB position changes may elicit deficits in cerebral autoregulation in cerebrovascular disorders. Additional research is required to further characterize this phenomenon.

Simulation based evaluation of a fan beam coded aperture x-ray diffraction imaging system for biospecimen analysis.

X-ray diffraction (XRD) imaging yields spatially resolved, material-specific information, which can aid medical diagnosis and inform treatment. In this work we used simulations to analyze the utility of fan beam coded aperture XRD imaging for fast, high-resolution scatter imaging of biospecimens for tissue assessment. To evaluate the proposed system's utility in a specific task, we employed a deterministic model to produce simulated data from biologically realistic breast tissue phantoms and model-based reconstruction to recover a spatial map of the XRD signatures throughout the phantoms. We found an XRD spatial resolution of ≈1 mm with a mean reconstructed spectral accuracy of 0.98 ± 0.01 for a simulated 1 × 150 mm2 fan beam operating at 160 kVp, 10 mA, and 4.5 s exposures. A classifier for cancer detection was developed utilizing cross-correlation of XRD spectra against a spectral library, with a receiver operating characteristic curve with an area under the curve value of 0.972. Our results indicated a potential diagnostic modality that could aid in tasks ranging from analysis of ex-vivo pathology biospecimens to intraoperative cancer margin assessment, motivating future work to develop an experimental system while enabling the development of improved algorithms for imaging and tissue analysis-based classification performance.

Single-shot memory-effect video.

Imaging through opaque scattering media is critically important in applications ranging from biological and astronomical imaging to metrology and security. While the random process of scattering in turbid media produces scattered light that appears uninformative to the human eye, a wealth of information is contained in the signal and can be recovered using computational post-processing techniques. Recent studies have shown that statistical correlations present in the scattered light, known as 'memory effects', allow for diffraction-limited imaging through opaque media without detailed knowledge of (or access to) the source or scatterer. However, previous methods require that the object and/or scatterer be static during the measurement. We overcome this limitation by combining traditional memory effect imaging with coded-aperture-based computational imaging techniques, which enables us to realize for the first time single-shot video of arbitrary dynamic scenes through dynamic, opaque media. This has important implications for a wide range of real-world imaging scenarios.

In vivo GluCEST MRI: Reproducibility, background contribution and source of glutamate changes in the MPTP model of Parkinson's disease.

Glutamate Chemical Exchange Saturation Transfer (GluCEST) MRI is a recently developed technique to image glutamate. In the present study, we evaluated the reproducibility and background contamination to the GluCEST and source of the GluCEST changes in a mouse model of Parkinson's disease. Repeated measurements in five mice demonstrated an intra-animal coefficient of variation (CV) of GluCEST signal to be 2.3 ± 1.3% and inter-animal CV of GluCEST to be 3.3 ± 0.3%. Mice were treated with MPTP to create a localized striatal elevation of glutamate. We found an elevation in the GluCEST contrast of the striatum following MPTP treatment (Control: 23.3 ± 0.8%, n = 16; MPTP: 26.2 ± 0.8%, n = 19; p ≤ 0.001). Additionally, the positive association between glutamate concentration measured via 1H MRS and GluCEST signal was used to estimate background contribution to the measured GluCEST. The contribution of signal from non-glutamate sources was found to be ~28% of the total GluCEST. Immunohistochemical analysis of the brain showed co-localization of glutamate with GFAP in the striatum. This suggests that the elevated glutamate present in the striatum in this mouse model reflects astroglial proliferation or reactivity due to the action of MPTP. The potential of GluCEST as a biomarker for imaging inflammation mediated gliosis is discussed.

X-ray diffraction tomography with limited projection information.

X-ray diffraction tomography (XDT) records the spatially-resolved X-ray diffraction profile of an extended object. Compared to conventional transmission-based tomography, XDT displays high intrinsic contrast among materials of similar electron density and improves the accuracy in material identification thanks to the molecular structural information carried by diffracted photons. However, due to the weak diffraction signal, a tomographic scan covering the entire object typically requires a synchrotron facility to make the acquisition time more manageable. Imaging applications in medical and industrial settings usually do not require the examination of the entire object. Therefore, a diffraction tomography modality covering only the region of interest (ROI) and subsequent image reconstruction techniques with truncated projections are highly desirable. Here we propose a table-top diffraction tomography system that can resolve the spatially-variant diffraction form factor from internal regions within extended samples. We demonstrate that the interior reconstruction maintains the material contrast while reducing the imaging time by 6 folds. The presented method could accelerate the acquisition of XDT and be applied in portable imaging applications with a reduced radiation dose.

Noninvasive optical monitoring of critical closing pressure and arteriole compliance in human subjects.

The critical closing pressure ( CrCP) of the cerebral circulation depends on both tissue intracranial pressure and vasomotor tone. CrCP defines the arterial blood pressure ( ABP) at which cerebral blood flow approaches zero, and their difference ( ABP - CrCP) is an accurate estimate of cerebral perfusion pressure. Here we demonstrate a novel non-invasive technique for continuous monitoring of CrCP at the bedside. The methodology combines optical diffuse correlation spectroscopy (DCS) measurements of pulsatile cerebral blood flow in arterioles with concurrent ABP data during the cardiac cycle. Together, the two waveforms permit calculation of CrCP via the two-compartment Windkessel model for flow in the cerebral arterioles. Measurements of CrCP by optics (DCS) and transcranial Doppler ultrasound (TCD) were carried out in 18 healthy adults; they demonstrated good agreement (R = 0.66, slope = 1.14 ± 0.23) with means of 11.1 ± 5.0 and 13.0 ± 7.5 mmHg, respectively. Additionally, a potentially useful and rarely measured arteriole compliance parameter was derived from the phase difference between ABP and DCS arteriole blood flow waveforms. The measurements provide evidence that DCS signals originate predominantly from arteriole blood flow and are well suited for long-term continuous monitoring of CrCP and assessment of arteriole compliance in the clinic.

Accuracy assessment and characterization of x-ray coded aperture coherent scatter spectral imaging for breast cancer classification.

Although transmission-based x-ray imaging is the most commonly used imaging approach for breast cancer detection, it exhibits false negative rates higher than 15%. To improve cancer detection accuracy, x-ray coherent scatter computed tomography (CSCT) has been explored to potentially detect cancer with greater consistency. However, the 10-min scan duration of CSCT limits its possible clinical applications. The coded aperture coherent scatter spectral imaging (CACSSI) technique has been shown to reduce scan time through enabling single-angle imaging while providing high detection accuracy. Here, we use Monte Carlo simulations to test analytical optimization studies of the CACSSI technique, specifically for detecting cancer in ex vivo breast samples. An anthropomorphic breast tissue phantom was modeled, a CACSSI imaging system was virtually simulated to image the phantom, a diagnostic voxel classification algorithm was applied to all reconstructed voxels in the phantom, and receiver-operator characteristics analysis of the voxel classification was used to evaluate and characterize the imaging system for a range of parameters that have been optimized in a prior analytical study. The results indicate that CACSSI is able to identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) in tissue samples with a cancerous voxel identification area-under-the-curve of 0.94 through a scan lasting less than 10 s per slice. These results show that coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue within ex vivo samples. Furthermore, the results indicate potential CACSSI imaging system configurations for implementation in subsequent imaging development studies.

Mapping the alterations in glutamate with GluCEST MRI in a mouse model of dopamine deficiency.

Glutamate chemical exchange saturation transfer (GluCEST) MRI was used to measure metabolic changes in mice treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) by mapping regional cerebral glutamate. The GluCEST contrast following MPTP treatment was correlated with 1 H-MR spectroscopy, motor function, and immunohistochemical measures. The GluCEST contrast was found to be significantly higher in the striatum and motor cortex of mice treated with MPTP than in controls (p < 0.001), which was confirmed by localized 1 H-MR spectroscopy. Elevated striatal GluCEST was positively associated with local astrogliosis measured by immunohistochemistry for glial fibrillary acidic protein. Additionally, a negative correlation was found between motor function, measured by the four-limb grip strength test, and GluCEST of the striatum (R = -0.705, p < 0.001) and the motor cortex (R = -0.617, p < 0.01), suggesting a role of elevated glutamate in the abnormal cerebral motor function regulation. The GluCEST contrast and glial fibrillary acidic protein immunostaining were unaltered in the thalamus indicating glutamate elevation was localized to the striatum and the motor cortex. These findings suggest that in addition to measuring spatial changes in glutamate, GluCEST may serve as an in vivo biomarker of metabolic and functional changes that may be applied to the assessment of a broad range of neuropathologies. Read the Editorial Highlight for this article on page 346.

Snapshot fan beam coded aperture coherent scatter tomography.

We use coherently scattered X-rays to measure the molecular composition of an object throughout its volume. We image a planar slice of the object in a single snapshot by illuminating it with a fan beam and placing a coded aperture between the object and the detectors. We characterize the system and demonstrate a resolution of 13 mm in range and 2 mm in cross-range and a fractional momentum transfer resolution of 15%. In addition, we show that this technique allows a 100x speedup compared to previously-studied pencil beam systems using the same components. Finally, by scanning an object through the beam, we image the full 4-dimensional data cube (3 spatial and 1 material dimension) for complete volumetric molecular imaging.

Design and implementation of coded aperture coherent scatter spectral imaging of cancerous and healthy breast tissue samples.

A scatter imaging technique for the differentiation of cancerous and healthy breast tissue in a heterogeneous sample is introduced in this work. Such a technique has potential utility in intraoperative margin assessment during lumpectomy procedures. In this work, we investigate the feasibility of the imaging method for tumor classification using Monte Carlo simulations and physical experiments. The coded aperture coherent scatter spectral imaging technique was used to reconstruct three-dimensional (3-D) images of breast tissue samples acquired through a single-position snapshot acquisition, without rotation as is required in coherent scatter computed tomography. We perform a quantitative assessment of the accuracy of the cancerous voxel classification using Monte Carlo simulations of the imaging system; describe our experimental implementation of coded aperture scatter imaging; show the reconstructed images of the breast tissue samples; and present segmentations of the 3-D images in order to identify the cancerous and healthy tissue in the samples. From the Monte Carlo simulations, we find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside them with a cancerous voxel identification sensitivity, specificity, and accuracy of 92.4%, 91.9%, and 92.0%, respectively. From the experimental results, we find that the technique is able to identify cancerous and healthy tissue samples and reconstruct differential coherent scatter cross sections that are highly correlated with those measured by other groups using x-ray diffraction. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside samples within a time on the order of a minute per slice.

Pressure modulation algorithm to separate cerebral hemodynamic signals from extracerebral artifacts.

We introduce and validate a pressure measurement paradigm that reduces extracerebral contamination from superficial tissues in optical monitoring of cerebral blood flow with diffuse correlation spectroscopy (DCS). The scheme determines subject-specific contributions of extracerebral and cerebral tissues to the DCS signal by utilizing probe pressure modulation to induce variations in extracerebral blood flow. For analysis, the head is modeled as a two-layer medium and is probed with long and short source-detector separations. Then a combination of pressure modulation and a modified Beer-Lambert law for flow enables experimenters to linearly relate differential DCS signals to cerebral and extracerebral blood flow variation without a priori anatomical information. We demonstrate the algorithm's ability to isolate cerebral blood flow during a finger-tapping task and during graded scalp ischemia in healthy adults. Finally, we adapt the pressure modulation algorithm to ameliorate extracerebral contamination in monitoring of cerebral blood oxygenation and blood volume by near-infrared spectroscopy.

Modified Beer-Lambert law for blood flow.

We develop and validate a Modified Beer-Lambert law for blood flow based on diffuse correlation spectroscopy (DCS) measurements. The new formulation enables blood flow monitoring from temporal intensity autocorrelation function data taken at single or multiple delay-times. Consequentially, the speed of the optical blood flow measurement can be substantially increased. The scheme facilitates blood flow monitoring of highly scattering tissues in geometries wherein light propagation is diffusive or non-diffusive, and it is particularly well-suited for utilization with pressure measurement paradigms that employ differential flow signals to reduce contributions of superficial tissues.

Complementary coded apertures for 4-dimensional x-ray coherent scatter imaging.

X-ray scattering has played a key role in non-destructive materials characterization due to the material-specific coherent scattering signatures. In the current energy dispersive coherent scatter imaging systems, including selected volume tomography and coherent scatter computed tomography, each object voxel is measured at a single scatter angle, which suffers from slow acquisition time. The employment of coded apertures in x-ray scatter imaging systems improves the photon collection efficiency, making it promising for real time volumetric imaging and material identification. In this paper, we propose a volumetric x-ray scatter imaging system using a pair of complementary coded apertures: a coded aperture on the detector side introduces multiplexed measurement on an energy-sensitive detector array; a complementary source-side coded aperture selectively illuminates the object to decouple the ambiguity due to the increased parallelization for 4D imaging. The system yields the 1D coherent scattering form factor at each voxel in 3D. We demonstrate tomographic imaging and material identification with the system and achieve a spatial resolution ~1 cm and a normalized momentum transfer resolution, Δq/q, of 0.2.

Giant all-optical tunable group velocity dispersion in an optical fiber.

We realize a strongly dispersive material with large tunable group velocity dispersion (GVD) in a commercially-available photonic crystal fiber. Specifically, we pump the fiber with a two-frequency pump field that induces an absorbing resonance adjacent to an amplifying resonance via the stimulated Brillouin processes. We demonstrate all-optical control of the GVD by measuring the linear frequency chirp impressed on a 28-nanosecond-duration optical pulse by the medium and find that it is tunable over the range ± 7.8 ns(2)/m. The maximum observed value of the GVD is 10(9) times larger than that in a typical single-mode silica optical fiber. Our observations are in good agreement with a theoretical model of the process.

Optical bedside monitoring of cerebral blood flow in acute ischemic stroke patients during head-of-bed manipulation.

BACKGROUND AND PURPOSE: A primary goal of acute ischemic stroke (AIS) management is to maximize perfusion in the affected region and surrounding ischemic penumbra. However, interventions to maximize perfusion, such as flat head-of-bed (HOB) positioning, are currently prescribed empirically. Bedside monitoring of cerebral blood flow (CBF) allows the effects of interventions such as flat HOB to be monitored and may ultimately be used to guide clinical management. METHODS: Cerebral perfusion was measured during HOB manipulations in 17 patients with unilateral AIS affecting large cortical territories in the anterior circulation. Simultaneous measurements of frontal CBF and arterial flow velocity were performed with diffuse correlation spectroscopy and transcranial Doppler ultrasound, respectively. Results were analyzed in the context of available clinical data and a previous study. RESULTS: Frontal CBF, averaged over the patient cohort, decreased by 17% (P=0.034) and 15% (P=0.011) in the ipsilesional and contralesional hemispheres, respectively, when HOB was changed from flat to 30°. Significant (cohort-averaged) changes in blood velocity were not observed. Individually, varying responses to HOB manipulation were observed, including paradoxical increases in CBF with increasing HOB angle. Clinical features, stroke volume, and distance to the optical probe could not explain this paradoxical response. CONCLUSIONS: A lower HOB angle results in an increase in cortical CBF without a significant change in arterial flow velocity in AIS, but there is variability across patients in this response. Bedside CBF monitoring with diffuse correlation spectroscopy provides a potential means to individualize interventions designed to optimize CBF in AIS.