The present disclosure relates generally to biomedical imaging, and more particularly to exemplary methods and apparatus for providing imaging (e.g., high-resolution imaging) of one or more blood flow properties in the microvasculature.
Quantitative measurements of blood flow properties can play an important role in clinical disease diagnosis and animal model research. Procedures which do not require a use of contrast agents are being developed since they may be ready for in situ/clinical/pre-clinical applications. For example, Doppler Optical Coherence Tomography (“OCT”) procedure can be used for ophthalmic imaging of blood flow (see, e.g., Chen et al., 2005, “Spectral domain optical coherence tomography: Ultra-high speed, ultra-high resolution ophthalmic imaging”. Archives of Ophthalmology, 123, 1715-1720), and ultrasound, imaging is used for studies of blood volume dynamics in the whole brain (see, e.g., Mace et al., 2011, “Functional ultrasound imaging of the brain”, Nat Meth. 8, 662-664).
Unfortunately, it appears that no technique to date has facilitated label-free identification of individual red blood cell (“RBC”) flow and rapid volumetric imaging of its flow properties especially in the microvasculature such as capillaries. Doppler OCT can monitor changes in the phase of light reflected from blood flow and thereby measures the flow's axial velocity (see, e.g., Srinivasan et al., 2010b ”Quantitative cerebral blood flow with optical coherence tomography”, Opt. Express, 18, 2477-94). However, Doppler OCT and other decorrelation-based methods (see, e.g., Lee et al., 2012, “Dynamic light scattering optical coherence tomography”, Opt. Express, 20, 22262-22277) may not be suitable for measuring the other flow properties such as the RBC flux and linear density. These properties can be physiologically important, and their quantitative measurement requires identification of individual RBC passage as the flux represents how many RBCs pass for unit time with the unit of RBC/s. Doppler OCT generally does not identify individual RBC passage and only measures the axial velocity while many capillaries lie in the transverse direction. Furthermore, as RBCs generally flow one by one in capillaries, the measurement by conventional procedures of the RBC speed may not be accurate in capillaries. Further, ultrasound imaging procedures did not achieve a sufficiently high spatial resolution to identify individual RBCs (e.g., ˜8 μm in diameter).
When labeling RBCs or plasma with fluorescence, it may be possible to identify individual RBC passage in capillaries. Fluorescence two-photon microscopy can perform continuous line scanning along a capillary, and obtain stripe patterns over the capillary axis versus time space, where the slope of the stripes represents the speed of RBC flow (see, e.g., Kleinfeld et al., 1998, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex” Proc. Natl. Acad. Sci., 95, 15741-15746). The flux can be quantified by the number of the stripes per unit time. These measurements of the speed [mm/s]and flux [RBC/s] can lead to the linear density [RBC/mm] and hematocrit (% volume fraction). Fluorescence microscopy also can identify individual RBC flow but only within its depth of focus (see, e.g., Tomita et al., 2011, “Oscillating neuro-capillary coupling during conical spreading depression as observed by tracking of FITC-labeled RBCs in single capillaries”, Neuroimage, 56, 1001-1010). As these procedures perform either line scans along the capillary or imaging within the dun depth of focus, they may not be suitable for rapid volumetric imaging of capillary RBC flow dynamics. High-speed volumetric imaging over a large number of capillaries can be beneficial because capillaries are known to exhibit large fluctuations during baseline and diverse responses to functional activation, even with negative responses. Further, the described fluorescence-based procedures likely require exogenous contrast agents, thus limiting their in situ diagnosis applications.
In the research industry, interest in the brain's blood flow regulation has been evolving toward understanding the role of the spatio-temporal dynamics of capillary networks. In distinction to arterioles, capillaries have been reported to exhibit highly heterogeneous responses to neural activation, capillary by capillary, nearly stochastic distributions during baseline masking neural activity-induced responses within single capillaries. Therefore, a technique/procedure/system/method to measure RBC flow properties at a number of capillaries at the same time may be beneficial so that, it is possible to study the capillary flow responses in a statistical manner with high statistical significance. Furthermore, a functional study can be performed to measure the flow properties with high, temporal resolution of ˜1 s during functional activation.
According to the Mie scattering theory suggesting that 1-μm wavelength light scattering is sensitive to scatterers of 0.1-10 μm in size (see, e.g., Lee et al., 2013, “Quantitative imaging of cerebral blood flow velocity and intracellular motility using dynamic light, scattering-optical coherence tomography”, J Cereb Blood Flow Metab, 33, 819-825), large backscattering can result from RBCs. Assuming this is the case, the intrinsic scattering intensity signal of a certain position should go up and come back down when an RBC passes through the position, which in turn can facilitate a label-free identification of individual RBC passage. According to one of the objects of the present disclosure, it is possible to combine such exemplary procedure with three-dimensional (“3D”) imaging techniques that can measure the scattering intensity with sufficiently high spatial resolution can facilitate label-free volumetric imaging of blood flow properties in the microvasculature, as described in further detailed herein.
OCT procedures facilitate three-dimensional (3D) imaging of tissue structures with micrometer resolution (see, e.g., Huang et al., 1991, “Optical coherence tomography”, Science, 254, 1178-1181). It needs no contrast agents and can image at depth (up to ˜1 mm in tissue). Furthermore, such exemplary OCT procedures can simultaneously resolve ail voxels along the axial direction over the depth of focus thus improving the volumetric imaging speed by 1-2 orders of magnitude (see, e.g., Srinivasan et al., 2010a, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography”, Opt. Lett., 35, 43-5) when compared with traditional confocal and two-photon microscopes (see, e.g., Kleinfeld et al., 1998, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex”, Proc. Natl. Acad. Sci. 95, 15741-15746; and Kamoun et al., 2010, “Simultaneous measurement of RBC velocity, flux, hematocrit and shear rate in vascular networks”, Nat Meth. 7, 655-660).
Accordingly, it may be beneficial to address and/or overcome at least some of the current technical barriers described herein above.
One of the objects of the present disclosure is to overcome certain barriers and shortcomings of the conventional arrangements and methods (including those described herein above), and provide exemplary embodiments of apparatus, systems and methods for facilitating microscopic imaging of blood flow, e.g., to measure RBC flow properties in the microvasculature with intrinsic scattering contrast.
According to an exemplary embodiment of the present disclosure, the intrinsic scattering intensity signal at a certain position fluctuates as an RBC passes through the position. Based on this determination, e.g., according to such exemplary embodiment, any technique that images the intrinsic scattering contrast with sufficiently high spatial resolution can be used for capturing individual RBC passage through capillaries, and thus quantifying the RBC flow properties. The exemplary apparatus, systems and methods according to the exemplary embodiment of the present disclosure can further utilizes such determination to provide an exemplary metric of statistical intensity variation (“SIV”) to replace the continuous monitoring of RBC passage with ensemble averaging along the capillary paths. Such further exemplary utilization can facilitate a rapid volumetric imaging of the RBC flow properties over microvasculature networks.
For example, according to another exemplary embodiment of the present disclosure, OCT exemplary procedures, systems and/or methods can be used for a continuous imaging of a cross-section through which many capillaries pass, and for capturing individual RBC passage through the capillaries and thereby for measuring the flow properties over the capillaries at the same time. As another example, exemplary rapid volumetric OCT scanning of a microvasculature network can be used for high-temporal-resolution imaging of the RBC flow properties over the capillaries consisting of the network. Such exemplary imaging procedures can be beneficial for ophthalmology diagnosis including diabetic retinopathy as the retinal capillary flow and its response to functional activation can be imaged quantitatively and in a capillary network level.
In further exemplary embodiments of the present disclosure, exemplary dynamic OCT imaging procedures can capture information regarding individual RBC passages over many vessels located at different depths at the same time. When such exemplary OCT procedure repeats continuous imaging of a cross-sectional plane through which many capillaries pass, the OCT intensity signal of a voxel located at a capillary center exhibits can peak when RBCs pass through the vessel. As each peak can represent a single RBC passage, counting the number of the peaks per unit time results in the RBC flux [RBC/s]. This exemplary measurement can be performed for each capillary passing through the imaging plane. In addition, as the peak is likely sharper when an RBC passes faster, the RBC speed [mm/s] can be determined and/or estimated from the width of the peak. By moving the cross-sectional scanning plane and repeating the above exemplary processing procedure, it is possible to obtain three-dimensional maps of the RBC flow properties over a microvasculature network. A residence time line scanning method of fluorescence two-photon microscopy has been previously described (see, e.g., Kamoun et al., 2010, ”Simultaneous measurement of RBC velocity, flux, hematocrit and shear rate in vascular networks”, Nat Meth, 7, 655-660). However, in contrast, the exemplary embodiments of the system, apparatus and method according to exemplary embodiments of the present disclosure does not require the use of contrast agents, and can monitor more than a few vessels located at different depths at the same time.
According to still another exemplary embodiment of the present disclosure, it is possible to obtain three-dimensional maps of the RBC flow properties more rapidly by using the proposed metric of SIV. In the above-described exemplary embodiment, the cross-sectional scanning plane can be anchored for a moment to capture at least several RBC passage. In contrast, based on the determination that the OCT intensity fluctuates by RBC passage, the exemplary procedure of such exemplary embodiment gathers statistical information of intensity variation along a capillary path. This collection of the statistical information can be done from, a more rapidly scanned volume data, where, e.g., only at least two scans are repeated for each cross-sectional plane. Such exemplary scanning protocol can be the one commonly used for rapid volumetric OCT angiogram (see, e.g., Srinivasan et al., 2010a, “Rapid volumetric angiography of cortical microvasculature with optical coherence tomography”, Opt. Lett., 35, 43-5). Thus, such exemplary scanning can result in obtaining the volume data of both angiogram and SIV. Mathematically, whereas the angiogram data is generally obtained from the displacement of the phase-resolved signal in the complex plane, the SIV can be obtained only from the difference in the intensity signal. There can be a number of ways to define SIV, but one definition can be:
where I(z,x,t1:y) can be the intensity data of the first B-scan over the cross-sectional plane at y, and I(z,x,t2;y) can be the second B-scan data.
Indeed, the exemplary embodiments of the present disclosure can be implemented with, but not limited by or to, exemplary OCT systems, apparatus and/or methods.
Further, according to yet another exemplary embodiment of the present disclosure, it is possible to trace and vectorize vessel segments from either angiogram or SIV data. For a certain exemplary vectorized vessel segment, SIVs can be gathered and/or obtained along the segment path from the volume data of SIV(z,x,y). This exemplary SIV information gathered and/or obtained along the capillary segment can be used for estimating the RBC flow properties of the capillary. For example, the mean of SIV can be proportional to the RBC flax. Further statistical analysis of the SIV values (e.g., histogram) can estimate the linear density. The RBC speed can be obtained from the flux and density using the relation of (flux)=(density)×(speed). By repeating this exemplary estimation for each vectorized vessel segment, it is possible to obtain three-dimensional network maps of the RBC flow properties.
It is also possible to enhance the exemplary SIV-based estimation of the RBC flow properties by utilizing multiple time gaps. The amount that the intensity varies by RBC passage can depend on the time gap between the consecutively acquired two intensities. Using an exemplary scanning protocol according to an exemplary embodiment of the present disclosure, it is possible to obtain three or more SIV volume data with three or more different respective time gaps from the volumetric scan that repeats three B-scans for each cross-sectional plane. As such exemplary multiple-time-gap SIV data provides more plentiful statistical information, an exemplary analysis of the data can improve both the estimation accuracy and dynamic ranges.
In a further exemplary embodiment of the present disclosure, the exemplary SIV-based rapid volumetric imaging of capillary RBC flow properties can facilitate determinations of how the capillary network flow pattern varies in physiology and pathology. For example, according to one exemplary embodiment of the present disclosure, it is possible to generate and/or utilize quantitative mapping of the capillary network's RBC flow properties in the human retina, and determine how the pattern responds to various functional activation for diagnosis of various pathologies, e.g., diabetic retinopathy. In the research respective, such rapid volumetric imaging of the capillary networks flow pattern with, e.g., ˜1 s temporal resolution can facilitate monitoring of how the pattern in the cerebral cortex varies in response to somatosensory activation. Since conventional techniques did not provide simultaneous monitoring of RBC flow over hundreds of capillaries with such a high temporal resolution, such research can lead to important findings on physiological and pathological behaviors of the capillary network flow during brain's energy supply regulation, thus likely facilitating a development of various therapeutics approaches to a range of disorders of the brain.
For example, according to one exemplary embodiment of the present disclosure, apparatus, method and computer accessible medium can be provided for determining presence of individual scattering objects in at least one blood vessel.
It is possible to determine the presence of the individual red blood cells in the portion of the blood vessel e.g., using a computer arrangement, by identifying the individual scattering objects that pass through a particular position within the blood vessel or through multiple individual positions within the blood vessel. It is also possible to determine the presence of the individual scattering objects in the portion of the blood vessel without a contrast agent provided in the blood vessel. The blood vessel can be within the eye and/or the brain. The individual scattering objects can include individual red blood cells.
According to another exemplary embodiment of the present disclosure, the presence of the individual red blood cells in respective portions of multiple blood vessels can be determined based on the data. The individual scattering objects can include individual light scattering objects. The individual light scattering objects can include individual red blood cells. At least one characteristic of a plurality of the individual blood cells can be determined based on a determination of the presence thereof. Such characteristic(s) can include (i) flux, (ii) speed, (iii) hematocrit, and/or (iv) density.
In yet another exemplary embodiment of the present disclosure, it is possible to generate at least one image of the blood vessel based on the determination of the presence of the individual red blood cells with an intensity of scattering of the objects. Such image(s) of the blood vessel can include a volumetric image.
According to a further exemplary embodiment of the present disclosure, a detector arrangement which can be used to perform the detection of the interferometric radiation can obtain first and second intensities of the interferometric radiation at a first location of the multiple individual positions. It is further possible to determine differences between the first and second intensities to form first information, and generate statistical data regarding at least one characteristic of a plurality of the red blood cells based on the first information. The detector arrangement can also obtain third and fourth intensities of the interferometric radiation at a second location or a subsequent time at the first location of the multiple individual positions. It is possible, e.g., with the computer arrangement, to determine differences between the third and fourth intensities to form second information and generate the statistical data further based on the second information.
In yet another exemplary embodiment of the present disclosure, the detector arrangement can (i) obtain at least one intensity of the interferometric radiation along the blood vessel, and (ii) generate stripe pattern information representing a passage of the individual red blood cells through at least one segment of the blood vessel(s). It is possible, e.g., with the computer arrangement, to determine at least one characteristic of the plurality of the individual blood cells based on the stripe pattern information. It is also possible, e.g., with the computer arrangement, to process at least one two-dimensional image of blood vessels so as to automatically identify a position of the blood vessel(s). In one exemplary variant, it is further possible, e.g., with the computer arrangement, to (i) process at least one intensity time course associated with the blood vessel(s) so as to automatically detect peaks representing a passage of the individual red blood cells, and (ii) determine at least one characteristic of the plurality of the red blood cells based on information for the detected peaks. It is further possible, e.g., with the computer arrangement, to (i) process volumetric image data based on Hessian matrix's eigenvalues and eigenvectors of the volumetric image data to form particular information, and (ii) automatically trace and vectorize segments of a plurality of vessel based on the particular information.
In addition, according to still another exemplary embodiment of the present disclosure, the determination of the characteristic(s) of the plurality of the individual blood cells can include an estimation of at least one flow property of the individual blood cells. Such exemplary estimation can be performed, e.g., using a computer arrangement, using multiple time gaps.
These and other objects, features and advantages of the exemplary embodiments of the present disclosure will become apparent upon reading the following detailed description of the exemplary embodiments of the present disclosure, when taken in conjunction with the appended claims.
Further objects, features and advantages of the present disclosure will become apparent from the following detailed description taken in conjunction with the accompanying figures showing illustrative embodiments of the present disclosure, in which:
Throughout the figures, the same reference numerals and characters, unless otherwise stated, are used to denote like features, elements, components or portions of the illustrated embodiments. Moreover, while the subject disclosure will now be described in detail with reference to the figures, it is done so in connection with the illustrative embodiments. It is intended that changes and modifications can be made to the described exemplary embodiments without departing from the true scope and spirit of the subject disclosure as defined by the appended claims.
Various exemplary embodiment of the present disclosure can utilize the determination that the intrinsic scattering intensity signal fluctuates at a certain position as an RBC passes through the position. This exemplary determination can confirm that the Mie scattering-based theoretical inference that 1 ˜μm wavelength light scattering is sensitive to scatterers of, e.g., about 0.1˜10 μm in size. For example, the OCT signal that represents how much light is back-scattered from a voxel can fluctuate when an RBC passes the voxel.
Exemplary results described herein here can be obtained using a spectral-domain OCT system, as shown in a schematic diagram of
As shown in
As shown in
Various exemplary embodiments of the present disclosure as provided herein can be associated with, but not limited to, the following examples.
Cross-Sectional Imaging of Exemplary Capillary RBC Flow Properties
In particular, as shown in
For each time course, e.g., the exemplary procedure shown in.
where t0 is the center time point of the window, and a, b, and c are fitting coefficients. Fitting can result in the values of a, b, and c and the coefficient of determination R2 for each time point. Based on these exemplary values, it is possible to detect the RBC passage peaks (procedure 450) by, e.g., thresholding a>50% and R2>0.5, for example.
The exemplary process of
Such exemplary process according to the exemplary embodiment of the present disclosure (which can be performed by the exemplary system shown in
where wRBC, wvoxel, and wkernel the full-width half-maximum of the RBC, OCT voxel, and the Gaussian kernel used in the post processing, respectively.
For example, when an RBC passes a voxel with about 1 mm/s, for instance, the peak width can result from the convolution of the RBC profile with the voxel profile, leading to (wRBC2+wvoxel2)1/2, where all profiles can be assumed to be Gaussian. As the time course can be further convolved with a Gaussian kernel to suppress noise, the final width can become (wRBC2+wvoxel2+wkernel2)1/2. With <b> in millisecond, with the exemplary system and method according to this exemplary embodiment, it is possible to use wRBC=6.5, wvoxel=3.5, and wkernel=2(2ln2)1/2 Δt (a Gaussian kernel with σ=Δt where Δt indicates the temporal sampling of OCT B-scans). It may be preferable but certainly not compulsory to obtain <b> by averaging over hundreds of peaks while excluding, e.g., about 10% outliers in order to suppress potential error due to RBC clumping.
The accuracy of the exemplary measurement of the capillary RBC speed was tested through comparison with traditional stripe pattern-based measurements. True values of the RBC speed were obtained from the stripe pattern (as shown in
This exemplary embodiment assumes that RBCs have equivalently similar sizes. RBCs exhibit different orientations while flowing through capillaries, and thus different effective sizes in such imaging schemes are obtained as obtained using such exemplary embodiment. However, the effect of the different orientations on the exemplary speed estimation is negligible. This can be seen in Supplementary Figure S2 in Kamoun et al., 2010, “Simultaneous measurement of RBC velocity, flux, hematocrit and shear rate in vascular networks”, Nat Meth, 7, 655-660, which describes a residence time line scanning method. The negligible effect is again verified by the exemplary embodiment (as shown in the exemplary graph of
The exemplary procedure used in the exemplary method and system according to such exemplary embodiment of the present disclosure can have limited dynamic ranges of the estimation of RBC flow properties. For example, an RBC passing with about 2 mm/s can result in a peak with a width of (wRBC2+wvoxel2)1/2/v=3.7 ms, which can be too sharp to be accurately characterized using the temporal sampling in such exemplary procedure (Δt=4 ms). The exemplary upper limit in the dynamic range of the speed measurement using the simple definition (wRBC2+wvoxel2)1/2/Δt can be about 1.8 mm/s. The exemplary range of the capillary RBC speed can be about 0.1-2 mm/s. In addition, as the exemplary data process shown in
Exemplary Three-Dimensional Maps of Capillary RBC Flow Properties
The data acquisition and processing procedures, systems and methods according to exemplary embodiments of the present disclosure described herein can be used to obtain 3D maps of capillary RBC flow properties. For example, as one example, the exemplary procedure shown in
While conventional methods measure the capillary RBC flow properties capillary by capillary (see, e.g., Kleinfeld et al., 1998, “Fluctuations and stimulus-induced changes in blood flow observed in individual capillaries in layers 2 through 4 of rat neocortex”, Proc. Natl. Acad. Sci., 95, 15741-15746) or depth by depth (see, e.g., Tomita et al., 2011, “Oscillating neuro-capillary coupling during cortical spreading depression as observed by tracking of FITC-labeled RBCs in single capillaries”, Neuroimage, 56, 1001-1010), with the exemplary procedure, system and method according to such exemplary embodiment of the present disclosure, it is possible to measure such capillary RBC flow properties simultaneously, e.g., over many capillaries located at different depths. Such advantage facilitates a generation of exemplary 3D spatial maps such as those shown in
In addition, exemplary procedures, systems and methods according to exemplary embodiments of the present disclosure can measure the flow properties even when a capillary is tortuous or spans through different depths. Further, the speed estimation that can be obtained, by procedures, systems and methods according to exemplary embodiments of the present disclosure does not depend, e.g., on the direction of RBC flow as long as they use isotropic voxels. Further, procedures, systems and methods according to exemplary embodiments of the present disclosure does not require a use of any exogenous contrast agent so as to be ready for in situ or clinical applications.
Rapid Volumetric Imaging of Exemplary Capillary Network RBC Flux
With exemplary procedures, systems and methods according to further exemplary embodiments of the present disclosure, it is possible to facilitate a more rapid volumetric imaging of capillary RBC flow properties. Such exemplary procedures, systems and methods can be used to obtain and effectuate the exemplary measurement of capillary RBC flux using the exemplary metric of SIV.
In particular, as depicted in
First, e.g., the 3D angiogram and/or the SIV data can be used to identity and vectorize individual capillaries, and thus to provide a mask for gathering and analyzing the SIV values along each capillary path (see procedure 830 of
Then, using the exemplary information of the above vectorized vessel segments (see procedure 840) and the SIV volume data (see procedure 850), it is possible to obtain exemplary SIV values for each capillary segment (see procedure 860). Then, the obtained set of SIV values for each capillary segment, {SIV}, can be analyzed to estimate the RBC flow properties. In such exemplary manner, the exemplary process, system and procedures according to the further exemplary embodiment of the present disclosure can be used to estimate the RBC flux,
According to yet another exemplary embodiment of the present disclosure, it is also possible to estimate the other flow properties from {SIV}. For example, as the intensity variation is zero in principle at the moment when no RBC passes (see, e.g., an exemplary illustration of
Exemplary Functional Imaging of Capillary Network Flow Responses to Brain Activation
One example of possible applications of such exemplary process, system and procedures according to this exemplary embodiment of the present disclosure can be its possible use for studying how the cerebral cortex's capillary network flux pattern varies in response to functional somatosensory activation. In particular, with such exemplary process, system and procedures, it is possible to achieve a sufficiently high temporal resolution for tracing fast hemodynamic responses to functional activation. The time constant of the responses is typically ˜1 s. For example, SIV imaging was repeated so that 3D capillary network flux maps were obtained every 1.3 s during functional activation (see FIGS, 11A-11C).
In particular,
This exemplary experiment facilitated a tracing of relative changes in the RBC flux over hundreds of capillaries, as shown in
Exemplary Multiple-Time-Gap SIV Imaging
The quantitative relation between the mean SIV and the RBC flux (as shown in, e.g.,
It is further possible to implement, e.g., three or more time gaps with three or more B-scans. The above exemplary scanning protocol according to an exemplary embodiment of the present disclosure consecutively repeats three B-scans for each Y position so that the scanned Y position sequence can be 1 1 1 2 2 2 3 3 3, and so on. However, a further exemplary protocol can be provided with moving the scanning plane back and forth along the y-axis such that, for example, the scanned Y position sequence becomes 1 1 2 2 1 3 2 4 3 3 4 4 and so on. This exemplary protocol can be used to scan, e.g., three or more times for each Y position, and can result in three or more SIV volume data with three or more different time gaps of δt, 3δt, and 4δt. Other exemplary smart scanning protocols also can be provided within the scope of the exemplary embodiments of the present disclosure.
The exemplary multiple-time-gap SIV imaging procedure, system and method according to various exemplary embodiments of the present disclosure can improve the accuracy, as well as the dynamic range of the flow property measurement. The dynamic ranges of measurable RBC flux and speed with single-time-gap SIV information are functions of the time gap. Therefore, a larger dynamic range can be achieved by, e.g., combining the exemplary SIV information with more than one time gaps.
Exemplary Ophthalmic Imaging of Capillary Network Flow Dynamics
Since the exemplary systems, methods, apparatus and procedures according to exemplary embodiments of the present disclosure does not need to rely on an exogenous contrast agent, it can be also be used for in situ or clinical diagnosis. For example, such exemplary systems, methods, apparatus and procedures can be utilized and/or embodied for human ophthalmology diagnosis, and can be beneficial for diagnosis of diabetic retinopathy if the retinal capillary flow and its response to functional activation can be imaged quantitatively and in a capillary network level. Exemplary Doppler OCT procedures, systems and methods can measure the axial velocity of blood flow, but it can be difficult to quantify the RBC flux as well as the speed in capillaries, especially in those lying in the lateral direction. Further, exemplary Doppler OCT procedures, systems and methods can require at least several consecutive scans per position for gathering sequential phase information. In contrast, the exemplary systems, apparatus, method and procedures according to certain exemplary embodiments of the present disclosure utilized with the metric of SIV can require, e.g., only two B-scans so that a higher volumetric imaging speed can be obtained with therewith (e.g., the exemplary OCT method, system, modality, procedure, etc.). Such exemplary embodiments can also be used to estimate other flow properties than the speed as it is based on the determination that the OCT intensity varies with individual RBC passage. Further, the exemplary systems, apparatus, method and procedures according to various exemplary embodiments of the present disclosure can quantify RBC flow in regardless of the flow direction as long as they use isotropic voxels. Thus, the exemplary systems, apparatus, method and procedures according to the exemplary embodiments of the present disclosure can be used for ophthalmic imaging of blood flow dynamics, e.g., by only implementing software or by modifying only a small portion of hardware when needed.
The foregoing merely illustrates the principles of the disclosure. Various modifications and alterations to the described embodiments will be apparent to those skilled in the art in view of the teachings herein. Indeed, the arrangements, systems and methods according to the exemplary embodiments of the present disclosure can be used with and/or implement any OCT system, OFDI system, SD-OCT system or other imaging systems, and for example with those described in International Patent Application PCT/US2004/029148, filed Sep. 8, 2004 which published as International Patent Publication No. WO 2005/047813 on May 26, 2005, U.S. patent application Ser. No. 11/266,779, filed Nov. 2, 2005 which published as U.S. Patent Publication No. 2006/0093276 on May 4, 2006, and U.S. patent application Ser. No. 10/501,276, filed Jul. 9, 2004 which published as U.S. Patent Publication No. 2005/0018201 on Jan. 27, 2005, and U.S. Patent Publication No. 2002/0122246, published on May 9, 2002, the disclosures of which are incorporated by reference herein in their entireties. It will thus be appreciated that those skilled in the art will be able to devise numerous systems, arrangements, and procedures which, although not explicitly shown or described herein, embody the principles of the disclosure and can be thus within the spirit and scope of the disclosure. In addition, all publications and references referred to above can be incorporated, herein by reference in their entireties. It should be understood that the exemplary procedures described herein can be stored on any computer accessible medium, including a hard drive, RAM, ROM, removable disks, CD-ROM, memory sticks, etc., and executed by a processing arrangement and/or computing arrangement which can be and/or include a hardware processors, microprocessor, mini, macro, mainframe, etc., including a plurality and/or combination, thereof. In addition, certain terms used in the present disclosure. Including the specification, drawings and claims thereof, can be used synonymously in certain instances, including, but not limited to, e.g., data and information. It should be understood that, while these words, and/or other words that can be synonymous to one another, can be used synonymously herein, that there can be instances when such words can be intended to not be used synonymously. Further, to the extent that the prior art knowledge has not been explicitly incorporated by reference herein above, it can be explicitly being incorporated herein in its entirety. All publications referenced above can be incorporated herein by reference.
This application relates to and claims priority from U.S. Patent Application Ser. No. 61/743,815 filed on Sep. 12, 2012, the entire disclosure of which is incorporated herein by reference.
This invention was made with the U.S. Government support under grant numbers NIB K99-EB014879 and R01-EB000790 awarded by the National Institute of Health. Thus, the U.S. Government has certain rights therein.
Number | Date | Country | |
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61743815 | Sep 2012 | US |