Quantitative lateral and axial flow imaging with optical coherence microscopy and tomography

Extraction of phase-based optoretinograms (ORG) from serial B-scans acquired over tens of seconds by mouse retinal raster scanning OCT system

Several specialized retinal optical coherence tomography (OCT) acquisition and processing methods have been recently developed to allow in vivo probing of light-evoked photoreceptors function, focusing on measurements in individual photoreceptors (rods and cones). Recent OCT investigations in humans and experimental animals have shown that the outer segments in dark-adapted rods and cones elongate in response to the visible optical stimuli that bleach fractions of their visual photopigment. We have previously successfully contributed to these developments by implementing OCT intensity-based "optoretinograms" (ORG), the paradigm of using near-infrared OCT (NIR OCT) to measure bleaching-induced back-scattering and/or elongation changes of photoreceptors in the eye in vivo. In parallel, several groups have successfully implemented phase-based ORGs, mainly in human studies, exploiting changes in the phases of back-scattered light. This allowed more sensitive observations of tiny alterations of photoreceptors structures. Applications of the phase-based ORG have been implemented primarily in high speed and cellular resolution AO-OCT systems that can visualize photoreceptor mosaic, allowing phase measurements of path length changes in outer segments of individual photoreceptors. The phase-based ORG in standard resolution OCT systems is much more demanding to implement and has not been explored extensively. This manuscript describes our efforts to implement a phase analysis framework to retinal images acquired with a standard resolution and raster scanning OCT system, which offers much lower phase stability than line-field or full-field OCT detection schemes due to the relatively slower acquisition speed. Our initial results showcase the successful extraction of phase-based ORG signal from the B-scans acquired at ∼100 Hz rate and its favorable comparison with intensity-based ORG signal extracted from the same data sets. We implemented the calculation of phase-based ORG signals using Knox-Thompson paths and modified signal recovery by adding decorrelation weights. The phase-sensitive ORG signal analysis developed here for mouse retinal raster scanning OCT systems could be in principle extended to clinical retinal raster scanning OCT systems, potentially opening doors for clinically friendly ORG probing.

Blood flow rate estimation in optic disc capillaries and vessels using Doppler optical coherence tomography with 3D fast phase unwrapping

The retinal volumetric flow rate contains useful information not only for ophthalmology but also for the diagnosis of common civilization diseases such as diabetes, Alzheimer's disease, or cerebrovascular diseases. Non-invasive optical methods for quantitative flow assessment, such as Doppler optical coherence tomography (OCT), have certain limitations. One is the phase wrapping that makes simultaneous calculations of the flow in all human retinal vessels impossible due to a very large span of flow velocities. We demonstrate that three-dimensional Doppler OCT combined with three-dimensional four Fourier transform fast phase unwrapping (3D 4FT FPU) allows for the calculation of the volumetric blood flow rate in real-time by the implementation of the algorithms in a graphics processing unit (GPU). The additive character of the flow at the furcations is proven using a microfluidic device with controlled flow rates as well as in the retinal veins bifurcations imaged in the optic disc area of five healthy volunteers. We show values of blood flow rates calculated for retinal capillaries and vessels with diameters in the range of 12-150 µm. The potential of quantitative measurement of retinal blood flow volume includes noninvasive detection of carotid artery stenosis or occlusion, measuring vascular reactivity and evaluation of vessel wall stiffness.

Optical coherence tomography velocimetry based on decorrelation estimation of phasor pair ratios (DEPPAIR)

Quantitative velocity estimations in optical coherence tomography requires the estimation of the axial and lateral flow components. Optical coherence tomography measures the depth resolved complex field reflected from a sample. While the axial velocity component can be determined from the Doppler shift or phase shift between a pair of consecutive measurements at the same location, the estimation of the lateral component for in vivo applications is still challenging. One approach to determine lateral velocity is multiple simultaneous measurements at different angles. In another approach the lateral component can be retrieved through repeated measurements at (nearly) the same location by an analysis of the decorrelation over time. In this paper we follow the latter approach. We describe a model for the complex field changes between consecutive measurements and use it to predict the uncertainties for amplitude-based, phase-based and complex algorithms. The uncertainty of the flow estimations follows from a statistical analysis and is determined by the number of available measurements and the applied analysis method. The model is verified in phantom measurements and the dynamic range of velocity estimations is investigated. We demonstrate that phase-based and complex (phasor) based lateral flow estimation methods are superior to amplitude-based algorithms.

Precision analysis and optimization in phase decorrelation OCT velocimetry

Quantitative flow velocimetry in Optical Coherence Tomography is used to determine both the axial and lateral flow component at the level of individual voxels. The lateral flow is determined by analyzing the statistical properties of reflected electro-magnetic fields for repeated measurements at (nearly) the same location. The precision or statistical fluctuation of the quantitative velocity estimation depends on the number of repeated measurements and the method to determine quantitative flow velocity. In this paper, both a method to determine quantitative flow velocity and a model for the prediction of the statistical fluctuations of velocity estimations are developed to analyze and optimize the estimation precision for phase-based velocimetry methods. The method and model are validated by phantom measurements in a bulk scattering medium as well as in intralipid solution in a capillary. Based on the model, the number of repeated measurements to achieve a certain velocimetry precision is predicted.

Computationally effective 2D and 3D fast phase unwrapping algorithms and their applications to Doppler optical coherence tomography

We propose a simplification for a robust and easy to implement fast phase unwrapping (FPU) algorithm that is used to solve the phase wrapping problem encountered in various fields of optical imaging and metrology. We show that the number of necessary computations using the algorithm can be reduced compared to its original version. FPU can be easily extended from two to three spatial dimensions. We demonstrate the applicability of the two- and three-dimensional FPU algorithm for Doppler optical coherence tomography (DOCT) in numerical simulations, and in the imaging of a flow phantom and blood flow in the human retina in vivo. We introduce an FPU applicability plot for use as a guide in the selection of the most suitable version of the algorithm depending on the phase noise in the acquired data. This plot uses the circular standard deviation of the wrapped phase distribution as a measure of noise and relates it to the root-mean-square error of the recovered, unwrapped phase.

Wavelet analysis on time-frequency plane of optical coherence tomography: simultaneous signal quality improvement in structural and velocity images

In this Letter, we utilize one-dimensional wavelet analysis to improve the quality of morphology images and velocity profiles of optical coherence tomography simultaneously, by performing analysis on the complex time-frequency plane of raw interferograms, prior to image construction. The results indicate a robust signal improvement that also preserves accuracy for both morphology and velocity information and has been demonstrated on a variety of samples with diverse flow speeds and morphologies.

Extracting Blood Vessels From Full-Field OCT Data of Human Skin by Short-Time RPCA

Recent advances in optical coherence tomography (OCT) lead to the development of OCT angiography to provide additional helpful information for diagnosis of diseases like basal cell carcinoma. In this paper, we investigate how to extract blood vessels of human skin from full-field OCT (FF-OCT) data using the robust principal component analysis (RPCA) technique. Specifically, we propose a short-time RPCA method that divides the FF-OCT data into segments and decomposes each segment into a low-rank structure representing the relatively static tissues of human skin and a sparse matrix representing the blood vessels. The method mitigates the problem associated with the slow-varying background and is free of the detection error that RPCA may have when dealing with FF-OCT data. Both short-time RPCA and RPCA methods can extract blood vessels from FF-OCT data with heavy speckle noise, but the former takes only half the computation time of the latter. We evaluate the performance of the proposed method by comparing the extracted blood vessels with the ground truth vessels labeled by a dermatologist and show that the proposed method works equally well for FF-OCT volumes of different quality. The average F-measure improvements over the correlation-mapping OCT method, the modified amplitude-decorrelation OCT angiography method, and the RPCA method, respectively, are 0.1835, 0.1032, and 0.0458.

Imaging of cortical structures and microvasculature using extended-focus optical coherence tomography at 1.3 μm

Extended-focus optical coherence tomography (xf-OCT) is a variant of optical coherence tomography (OCT) wherein the illumination and/or detection modes are engineered to provide a constant diffractionless lateral resolution over an extended depth of field (typically 3 to 10× the Rayleigh range). xf-OCT systems operating at 800 nm have been devised and used in the past to image brain structures at high-resolution in vivo, but are limited to ∼500  μm in penetration depth due to their short illumination wavelength. Here we present an xf-OCT system optimized to an image deeper within the cortex by using a longer illumination central wavelength of 1310 nm. The system offers a lateral resolution of 3 and 6.5 μm, over a depth of 900 μm and >1.5  mm using a 10× and 5× objective, respectively, in air. We characterize the system's resolution using microbeads embedded in PDMS and demonstrate its capabilities by imaging the cortical structure and microvasculature in anesthetized mice to a depth of ∼0.8  mm. Finally, we illustrate the difference in penetration depths obtainable with the new system and an xf-OCT system operating at 800 nm.

Statistical parametric mapping of stimuli evoked changes in total blood flow velocity in the mouse cortex obtained with extended-focus optical coherence microscopy

Functional magnetic resonance (fMRI) imaging is the current gold-standard in neuroimaging. fMRI exploits local changes in blood oxygenation to map neuronal activity over the entire brain. However, its spatial resolution is currently limited to a few hundreds of microns. Here we use extended-focus optical coherence microscopy (xfOCM) to quantitatively measure changes in blood flow velocity during functional hyperaemia at high spatio-temporal resolution in the somatosensory cortex of mice. As optical coherence microscopy acquires hundreds of depth slices simultaneously, blood flow velocity measurements can be performed over several vessels in parallel. We present the proof-of-principle of an optimised statistical parametric mapping framework to analyse quantitative blood flow timetraces acquired with xfOCM using the general linear model. We demonstrate the feasibility of generating maps of cortical hemodynamic reactivity at the capillary level with optical coherence microscopy. To validate our method, we exploited 3 stimulation paradigms, covering different temporal dynamics and stimulated limbs, and demonstrated its repeatability over 2 trials, separated by a week.

Spectrometer calibration for spectroscopic Fourier domain optical coherence tomography

We propose a simple and robust procedure for Fourier domain optical coherence tomography (FdOCT) that allows to linearize the detected FdOCT spectra to wavenumber domain and, at the same time, to determine the wavelength of light for each point of detected spectrum. We show that in this approach it is possible to use any measurable physical quantity that has linear dependency on wavenumber and can be extracted from spectral fringes. The actual values of the measured quantity have no importance for the algorithm and do not need to be known at any stage of the procedure. As example we calibrate a spectral OCT spectrometer using Doppler frequency. The technique of spectral calibration can be in principle adapted to of all kind of Fourier domain OCT devices.

Ultrahigh-speed, phase-sensitive full-field interferometric confocal microscopy for quantitative microscale physiology

We developed ultra-high-speed, phase-sensitive, full-field reflection interferometric confocal microscopy (FFICM) for the quantitative characterization of in vivo microscale biological motions and flows. We demonstrated 2D frame rates in excess of 1 kHz and pixel throughput rates up to 125 MHz. These fast FFICM frame rates were enabled by the use of a low spatial coherence, high-power laser source. Specifically, we used a dense vertical cavity surface emitting laser (VCSEL) array that synthesized low spatial coherence light through a large number of narrowband, mutually-incoherent emitters. Off-axis interferometry enabled single-shot acquisition of the complex-valued interferometric signal. We characterized the system performance (~2 μm lateral resolution, ~8 μm axial gating depth) with a well-known target. We also demonstrated the use of this highly parallelized confocal microscopy platform for visualization and quantification of cilia-driven surface flows and cilia beat frequency in an important animal model (Xenopus embryos) with >1 kHz frame rate. Such frame rates are needed to see large changes in local flow velocity over small distance (high shear flow), in this case, local flow around a single ciliated cell. More generally, our results are an important demonstration of low-spatial coherence, high-power lasers in high-performance, quantitative biomedical imaging.

Label-free fast 3D coherent imaging reveals pancreatic islet micro-vascularization and dynamic blood flow

In diabetes, pancreatic β-cells play a key role. These cells are clustered within structures called islets of Langerhans inside the pancreas and produce insulin, which is directly secreted into the blood stream. The dense vascularization of islets of Langerhans is critical for maintaining a proper regulation of blood glucose homeostasis and is known to be affected from the early stage of diabetes. The deep localization of these islets inside the pancreas in the abdominal cavity renders their in vivo visualization a challenging task. A fast label-free imaging method with high spatial resolution is required to study the vascular network of islets of Langerhans. Based on these requirements, we developed a label-free and three-dimensional imaging method for observing islets of Langerhans using extended-focus Fourier domain Optical Coherence Microscopy (xfOCM). In addition to structural imaging, this system provides three-dimensional vascular network imaging and dynamic blood flow information within islets of Langerhans. We propose our method to deepen the understanding of the interconnection between diabetes and the evolution of the islet vascular network.

Dynamic contrast optical coherence tomography images transit time and quantifies microvascular plasma volume and flow in the retina and choriocapillaris

Despite the prevalence of optical imaging techniques to measure hemodynamics in large retinal vessels, quantitative measurements of retinal capillary and choroidal hemodynamics have traditionally been challenging. Here, a new imaging technique called dynamic contrast optical coherence tomography (DyC-OCT) is applied in the rat eye to study microvascular blood flow in individual retinal and choroidal layers in vivo. DyC-OCT is based on imaging the transit of an intravascular tracer dynamically as it passes through the field-of-view. Hemodynamic parameters can be determined through quantitative analysis of tracer kinetics. In addition to enabling depth-resolved transit time, volume, and flow measurements, the injected tracer also enhances OCT angiograms and enables clear visualization of the choriocapillaris, particularly when combined with a post-processing method for vessel enhancement. DyC-OCT complements conventional OCT angiography through quantification of tracer dynamics, similar to fluorescence angiography, but with the important added benefit of laminar resolution.

Modeling of Cerebral Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network Structure, Blood Flow, and Oxygenation

Oxygen is delivered to brain tissue by a dense network of microvessels, which actively control cerebral blood flow (CBF) through vasodilation and contraction in response to changing levels of neural activity. Understanding these network-level processes is immediately relevant for (1) interpretation of functional Magnetic Resonance Imaging (fMRI) signals, and (2) investigation of neurological diseases in which a deterioration of neurovascular and neuro-metabolic physiology contributes to motor and cognitive decline. Experimental data on the structure, flow and oxygen levels of microvascular networks are needed, together with theoretical methods to integrate this information and predict physiologically relevant properties that are not directly measurable. Recent progress in optical imaging technologies for high-resolution in vivo measurement of the cerebral microvascular architecture, blood flow, and oxygenation enables construction of detailed computational models of cerebral hemodynamics and oxygen transport based on realistic three-dimensional microvascular networks. In this article, we review state-of-the-art optical microscopy technologies for quantitative in vivo imaging of cerebral microvascular structure, blood flow and oxygenation, and theoretical methods that utilize such data to generate spatially resolved models for blood flow and oxygen transport. These “bottom-up” models are essential for the understanding of the processes governing brain oxygenation in normal and disease states and for eventual translation of the lessons learned from animal studies to humans.

High-resolution in vivo optical imaging of stroke injury and repair

Central nervous system (CNS) function and dysfunction are best understood within a framework of interactions between neuronal, glial and vascular compartments comprising the neurovascular unit (NVU), all of which contribute to stroke-induced CNS injury, plasticity, repair, and recovery. Recent advances in in vivo optical microscopy have enabled us to observe and interrogate cells and their processes with high spatial resolution in real time and in their natural environment deep in the brain tissue. Here, we review some of these state-of-the-art imaging techniques with an emphasis on imaging the interactions among the constituents of the NVU during ischemic injury and repair in small animal models. This article is part of a Special Issue entitled SI: Cell Interactions In Stroke.

Combined Optical Coherence and Fluorescence Microscopy to assess dynamics and specificity of pancreatic beta-cell tracers

The identification of a beta-cell tracer is a major quest in diabetes research. However, since MRI, PET and SPECT cannot resolve individual islets, optical techniques are required to assess the specificity of these tracers. We propose to combine Optical Coherence Microscopy (OCM) with fluorescence detection in a single optical platform to facilitate these initial screening steps from cell culture up to living rodents. OCM can image islets and vascularization without any labeling. Thereby, it alleviates the need of both genetically modified mice to detect islets and injection of external dye to reveal vascularization. We characterized Cy5.5-exendin-3, an agonist of glucagon-like peptide 1 receptor (GLP1R), for which other imaging modalities have been used and can serve as a reference. Cultured cells transfected with GLP1R and incubated with Cy5.5-exendin-3 show full tracer internalization. We determined that a dose of 1 μg of Cy5.5-exendin-3 is sufficient to optically detect in vivo the tracer in islets with a high specificity. In a next step, time-lapse OCM imaging was used to monitor the rapid and specific tracer accumulation in murine islets and its persistence over hours. This optical platform represents a versatile toolbox for selecting beta-cell specific markers for diabetes research and future clinical diagnosis.

Dark-field polarization-sensitive optical coherence tomography

Polarization-sensitive optical coherence tomography (PS-OCT) is a functional OCT providing both structural and birefringent information of the sample, and it has been applied to the studies of various organs having polarization properties. Fiber-based PS-OCT is sensitive to specular reflection from the sample surface, because signal saturation due to the strong specular reflection can make the polarization measurement difficult. We developed a dark-field PS-OCT which can avoid the specular reflection problem. Dark-field PS-OCT was implemented by adapting a hybrid method of Bessel-beam illumination and Gaussian-beam detection, and a PS-OCT method based on passive delay unit (PDU). The new system was characterized in comparison with the conventional Gaussian-beam based method in both polarization components and various samples including the human skin. Dark-field PS-OCT performed as good as the conventional PS-OCT without the specular reflection artifact. Dark-field PS-OCT may be useful in practical situations where the specular reflection is unavoidable.

Relation of joint spectral and time domain optical coherence tomography (jSTdOCT) and phase-resolved Doppler OCT

A variety of promising approaches for quantitative flow velocity measurement in OCT have been proposed in recent years. The question is: Which method gets the most precise flow velocity out of the interference signals detected. We have compared the promising joint spectral and time domain optical coherence tomography (jSTdOCT) and the commonly used phase-resolved Doppler OCT (DOCT) and describe the link between these two proven methods for OCT in the Fourier domain (FD OCT). First, we show that jSTdOCT can be significantly improved by calculating the center of gravity via an unbiased complex algorithm instead of detecting the maximum intensity signal of the broadened Doppler frequency spectrum. Secondly, we introduce a unified mathematical description for DOCT and jSTdOCT that differs only in one exponent and call it enhjSTdOCT. Third, we present that enhjSTdOCT has the potential to significantly reduce the noise of the velocity measurement by choosing an exponent depending on the transverse sample velocity component and the signal-to-noise ratio. EnhjSTdOCT is verified numerically and experimentally to find the optimal parameters for maximal velocity noise reduction.

Optical coherence Doppler tomography for quantitative cerebral blood flow imaging

Optical coherence Doppler tomography (ODT) is a promising neurotechnique that permits 3D imaging of the cerebral blood flow (CBF) network; however, quantitative CBF velocity (CBFv) imaging remains challenging. Here we present a simple phase summation method to enhance slow capillary flow detection sensitivity without sacrificing dynamic range for fast flow and vessel tracking to improve angle correction for absolute CBFv quantification. Flow phantom validation indicated that the CBFv quantification accuracy increased from 15% to 91% and the coefficient of variation (CV) decreased 9.3-fold; in vivo mouse brain validation showed that CV decreased 4.4-/10.8- fold for venular/arteriolar flows. ODT was able to identify cocaine-elicited microischemia and quantify CBFv disruption in branch vessels and capillaries that otherwise would have not been possible.

Photoacoustic microscopy and computed tomography: from bench to bedside

Photoacoustic imaging (PAI) of biological tissue has seen immense growth in the past decade, providing unprecedented spatial resolution and functional information at depths in the optical diffusive regime. PAI uniquely combines the advantages of optical excitation and those of acoustic detection. The hybrid imaging modality features high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth. Here we first summarize the fundamental principles underpinning the technology, then highlight its practical implementation, and finally discuss recent advances toward clinical translation.

Maximum likelihood Doppler frequency estimation under decorrelation noise for quantifying flow in optical coherence tomography

Recent hardware advances in optical coherence tomography (OCT) have led to ever higher A-scan rates. However, the estimation of blood flow axial velocities is limited by the presence and type of noise. Higher acquisition rates alone do not necessarily enable precise quantification of Doppler velocities, particularly if the estimator is suboptimal. In previous work, we have shown that the Kasai autocorrelation estimator is statistically suboptimal under conditions of additive white Gaussian noise. In addition, for practical OCT measurements of flow, decorrelation noise affects Doppler frequency estimation by broadening the signal spectrum. Here, we derive a general maximum likelihood estimator (MLE) for Doppler frequency estimation that takes into account additive white noise as well as signal decorrelation. We compare the decorrelation MLE with existing techniques using simulated and flow phantom data and find that it has better performance, achieving the Cramer-Rao lower bound. By making an approximation, we also provide an interpretation of this method in the Fourier domain. We anticipate that this estimator will be particularly suited for estimating blood flow in in vivo scenarios.

Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux

We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation.

Quantitative cerebral blood flow imaging with extended-focus optical coherence microscopy

Quantitative three-dimensional blood flow imaging is a valuable technique to investigate the physiology of the brain. Two-photon microscopy (2PM) allows quantification of the local blood flow velocity with micrometric resolution by performing repeated line scans, but prohibitively long measurement times would be required to apply this technique to full three-dimensional volumes. By multiplexing the image acquisition over depth, Fourier domain optical coherence tomography (FDOCT) enables quantification of blood flow velocities with a high volume acquisition rate, albeit at a relatively low spatial resolution. Extended-focus optical coherence microscopy (xfOCM) increases the lateral resolution without sacrificing depth of field and therefore combines the high volume acquisition rate of FDOCT with a resolution comparable to 2PM. Here, we demonstrate high-resolution quantitative imaging of the blood flow velocity vector's magnitude in the adult murine brain with xfOCM.