SignificanceBedside cerebral blood flow (CBF) monitoring has the potential to inform and improve care for acute neurologic diseases, but technical challenges limit the use of existing techniques in clinical practice.AimHere, we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics.ApproachWe monitored 25 healthy adults with the Openwater system and concurrent transcranial Doppler (TCD) while performing a breath-hold maneuver to increase CBF. Relative blood flow (rBF) was derived from changes in speckle contrast, and relative blood volume (rBV) was derived from changes in speckle average intensity.ResultsA strong correlation was observed between beat-to-beat optical rBF and TCD-measured cerebral blood flow velocity (CBFv), R=0.79; the slope of the linear fit indicates good agreement, 0.87 (95% CI: 0.83 −0.92). Beat-to-beat rBV and CBFv were also strongly correlated, R=0.72, but as expected the two variables were not proportional; changes in rBV were smaller than CBFv changes, with linear fit slope of 0.18 (95% CI: 0.17 to 0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics.ConclusionsThis first in vivo validation of the Openwater optical system highlights its potential as a cerebral hemodynamic monitor, but additional validation is needed in disease states.
We introduce a tomographic approach for three-dimensional imaging of evoked hemodynamic activity, using broadband illumination and diffuse optical tomography (DOT) image reconstruction. Changes in diffuse reflectance in the rat somatosensory cortex due to stimulation of a single whisker were imaged at a frame rate of 5 Hz using a hyperspectral image mapping spectrometer. In each frame, images in 38 wavelength bands from 484 to 652 nm were acquired simultaneously. For data analysis, we developed a hyperspectral DOT algorithm that used the Rytov approximation to quantify changes in tissue concentration of oxyhemoglobin (ctHbO2) and deoxyhemoglobin (ctHb) in three dimensions. Using this algorithm, the maximum changes in ctHbO2 and ctHb were found to occur at 0.29±0.02 and 0.66±0.04 mm beneath the surface of the cortex, respectively. Rytov tomographic reconstructions revealed maximal spatially localized increases and decreases in ctHbO2 and ctHb of 321±53 and 555±96 nM, respectively, with these maximum changes occurring at 4±0.2 s poststimulus. The localized optical signals from the Rytov approximation were greater than those from modified Beer–Lambert, likely due in part to the inability of planar reflectance to account for partial volume effects.
There is a need for cost effective, quantitative tissue spectroscopy and imaging systems in clinical diagnostics and pre-clinical biomedical research. A platform that utilizes a commercially available light-emitting diode (LED) based projector, cameras, and scaled Monte Carlo model for calculating tissue optical properties is presented. These components are put together to perform spatial frequency domain imaging (SFDI), a model-based reflectance technique that measures and maps absorption coefficients (μ a ) and reduced scattering coefficients (μ ′ s ) in thick tissue such as skin or brain. We validate the performance of the flexible LED and modulation element (FLaME) system at 460, 530, and 632 nm across a range of physiologically relevant μ a values (0.07 to 1.5 mm −1 ) in tissue-simulating intralipid phantoms, showing an overall accuracy within 11% of spectrophotometer values for μ a and 3% for μ ′ s . Comparison of oxy- and total hemoglobin fits between the FLaME system and a spectrophotometer (450 to 1000 nm) is differed by 3%. Finally, we acquire optical property maps of a mouse brain in vivo with and without an overlying saline well. These results demonstrate the potential of FLaME to perform tissue optical property mapping in visible spectral regions and highlight how the optical clearing effect of saline is correlated to a decrease in μ ′ s of the skull.
Multifrequency (0 to 0.3 mm−1), multiwavelength (633, 680, 720, 800, and 820 nm) spatial frequency domain imaging (SFDI) of 5-aminolevulinic acid-induced protoporphyrin IX (PpIX) was used to recover absorption, scattering, and fluorescence properties of glioblastoma multiforme spheroids in tissue-simulating phantoms and in vivo in a mouse model. Three-dimensional tomographic reconstructions of the frequency-dependent remitted light localized the depths of the spheroids within 500 μm, and the total amount of PpIX in the reconstructed images was constant to within 30% when spheroid depth was varied. In vivo tumor-to-normal contrast was greater than ∼ 1.5 in reduced scattering coefficient for all wavelengths and was ∼ 1.3 for the tissue concentration of deoxyhemoglobin (ctHb). The study demonstrates the feasibility of SFDI for providing enhanced image guidance during surgical resection of brain tumors.
Early neurovascular coupling (NVC) changes in Alzheimer's disease can potentially provide imaging biomarkers to
assist with diagnosis and treatment. Previous efforts to quantify NVC with intrinsic signal imaging have required
assumptions of baseline optical pathlength to calculate changes in oxy- and deoxy-hemoglobin concentrations
during evoked stimuli. In this work, we present an economical spatial frequency domain imaging (SFDI) platform
utilizing a commercially available LED projector, camera, and off-the-shelf optical components suitable for imaging
dynamic optical properties. The fast acquisition platform described in this work is validated on silicone phantoms
and demonstrated in neuroimaging of a mouse model.
Optical imaging techniques based on multiple light scattering generally have poor sensitivity to the orientation and direction of microscopic light scattering structures. In order to address this limitation, we introduce a spatial frequency domain method for imaging contrast from oriented scattering structures by measuring the angular-dependence of structured light reflectance. The measurement is made by projecting sinusoidal patterns of light intensity on a sample, and measuring the degree to which the patterns are blurred as a function of the projection angle. We derive a spatial Fourier domain solution to an anisotropic diffusion model. This solution predicts the effects of bulk scattering orientation on the amplitude and phase of the projected patterns. We introduce a new contrast function based on a scattering orientation index (SOI) which is sensitive to the degree to which light scattering is directionally dependent. We validate the technique using tissue simulating phantoms, and ex vivo samples of muscle and brain. Our results show that SOI is independent of the overall amount of bulk light scattering and absorption, and that isotropic versus oriented scattering structures can be clearly distinguished. We determine the orientation of subsurface microscopic scattering structures located up to 600 μm beneath highly scattering (μ′s = 1.5 mm−1) material.
We present a rapid, noncontact imaging technique which can obtain the spectrally- and spatially-resolved scattering
and absorption coefficients of a turbid medium. The measurement involves combining a spatially modulated
illumination pattern with a snapshot imaging spectrometer for measurement. After capture of an (x, y, λ)
datacube, an image demodulation scheme is applied in post-processing to obtain the spatial maps of diffuse
reflectance, absorption coefficient, and reduced scattering coefficient. The resulting system is used to dynamic
maps (in 1 s intervals) of the brain's intrinsic optical signal.
We have developed a novel parallel-plate diffuse optical tomography (DOT) system for three-dimensional in vivo imaging of human breast tumor based on large optical data sets. Images of oxy-, deoxy-, and total hemoglobin concentration as well as blood oxygen saturation and tissue scattering were reconstructed. Tumor margins were derived using the optical data with guidance from radiology reports and magnetic resonance imaging. Tumor-to-normal ratios of these endogenous physiological parameters and an optical index were computed for 51 biopsy-proven lesions from 47 subjects. Malignant cancers (N=41) showed statistically significant higher total hemoglobin, oxy-hemoglobin concentration, and scattering compared to normal tissue. Furthermore, malignant lesions exhibited a twofold average increase in optical index. The influence of core biopsy on DOT results was also explored; the difference between the malignant group measured before core biopsy and the group measured more than 1 week after core biopsy was not significant. Benign tumors (N=10) did not exhibit statistical significance in the tumor-to-normal ratios of any parameter. Optical index and tumor-to-normal ratios of total hemoglobin, oxy-hemoglobin concentration, and scattering exhibited high area under the receiver operating characteristic curve values from 0.90 to 0.99, suggesting good discriminatory power. The data demonstrate that benign and malignant lesions can be distinguished by quantitative three-dimensional DOT.
We present a novel methodology for combining breast image data obtained at different times, in different geometries, and by different techniques. We combine data based on diffuse optical tomography (DOT) and magnetic resonance imaging (MRI). The software platform integrates advanced multimodal registration and segmentation algorithms, requires minimal user experience, and employs computationally efficient techniques. The resulting superposed 3-D tomographs facilitate tissue analyses based on structural and functional data derived from both modalities, and readily permit enhancement of DOT data reconstruction using MRI-derived a-priori structural information. We demonstrate the multimodal registration method using a simulated phantom, and we present initial patient studies that confirm that tumorous regions in a patient breast found by both imaging modalities exhibit significantly higher total hemoglobin concentration (THC) than surrounding normal tissues. The average THC in the tumorous regions is one to three standard deviations larger than the overall breast average THC for all patients.
In this paper, we describe a novel clinical breast diffuse optical tomography (DOT) instrument for CW and RF data acquisition in transmission geometry. It is designed to be able to acquire a massive amount of data in a short amount of time available for patient measurement by using a 209-channel galvo-based fast optical switch
and a fast electron-multiplying CCD. In addition to CW measurements, RF measurements were made by using an electro-optic modulator for source modulation and a gain-modulated image intensifier for detection. The patient bed has many clinically-oriented features as well as improved data acquisition rate and transmission RF
measurement capability. A series of preliminary results will be shown, including a heterodyne RF experiment
for bulk property measurement and a CW experiment for 3D imaging. In order to deal with large data size, a
linear reconstruction algorithm that exploits separability of the inverse problem in Fourier domain is used for
fast and memory-load-free reconstruction.
We have developed a novel method for combining non-concurrent MR and DOT data, which integrates advanced
multimodal registration and segmentation algorithms within a well-defined workflow. The method requires little user
interaction, is computationally efficient for practical applications, and enables joint MR/DOT analysis. The method
presents additional advantages: More flexibility than integrated MR/DOT imaging systems, The ability to independently
develop a standalone DOT system without the stringent limitations imposed by the MRI device environment, Enhancement
of sensitivity and specificity for breast tumor detection, Combined analysis of structural and functional data,
Enhancement of DOT data reconstruction through the use of MR-derived a priori structural information. We have
conducted an initial patient study which asks an important question: how can functional information on a tumor
obtained from DOT data be combined with the anatomy of that tumor derived from MRI data? The study confirms that
tumor areas in the patient breasts exhibit significantly higher total hemoglobin concentration (THC) than their
surroundings. The results show significance in intra-patient THC variations, and justify the use of our normalized
difference measure defined as the distance from the average THC inside the breast, to the average THC inside the tumor
volume in terms of the THC standard deviation inside the breast. This method contributes to the long-term goal of
enabling standardized direct comparison of MRI and DOT and facilitating validation of DOT imaging methods in
clinical studies.
We have developed a software platform for multimodal integration and visualization of diffuse optical tomography and magnetic resonance imaging. Novel registration and segmentation algorithms have been integrated into the platform. The multimodal registration technique enables the alignment of non-concurrently acquired MR and DOT breast data. The non-rigid registration algorithm uses two-dimensional signatures (2D digitally reconstructed radiographs) of the reference and moving volumes in order to register them. Multiple two-dimensional signatures can robustly represent the volume depending on the way signatures are generated. An easy way to conceptualize the idea is to understand the motion of an object by tracking three perpendicular shadows of the object. The breast MR image segmentation
technique enables a priori structural information derived from MRI to be incorporated into the reconstruction of DOT data. The segmentation algorithm is based on "Random walkers". Both registration and segmentation algorithms were tested and have shown promising results. The average Target Registration Error (TRE) for phantom models simulating the large breast compression differences was always below 5%. Tests on patient datasets also showed satisfying visual results. Several tests were also conducted for segmentation assessment and results have shown high quality MR breast image segmentation.
We have developed a software platform for multimodal integration and visualization of diffuse optical tomography (DOT) and magnetic resonance imaging (MRI) of breast cancer. The image visualization platform allows multimodality 3D image visualization and manipulation of datasets, such as a variety of 3D rendering technique, and the ability to simultaneously control multiple fields of view. This platform enables quantitative and qualitative analysis of structural and functional diagnostic data, using both conventional & molecular imaging. The functional parameters, together with morphological parameters from MR can be suitably combined and correlated to the absolute diagnosis from histopathology. Fusion of the multimodal datasets will eventually lead to a significant improvement in the sensitivity and specificity of breast cancer detection. Fusion may also allow a priori structural information derived from MRI to be incorporated into the reconstruction of diffuse optical tomography images. We will present the early results of image visualization and registration on multimodal breast cancer data, DOT and MRI.
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