Comparison of Kasai autocorrelation and maximum likelihood estimators for Doppler optical coherence tomography

Size correction and deep image optimization in optical coherence tomography angiography with structural image-assisted common parts extraction method

Tail artifact elimination is essential in optical coherence tomography angiography (OCTA) for the artifacts will prevent the reconstruction of the 3D vessel image. The tail artifacts of superficial vessels obscure the deep vascular signals and cause the signals at different depths to mix with each other. Most tail artifact elimination methods can shorten the tails but have difficulty in determining the lower boundary of the vessels. In this letter, we introduce a technique to extract vascular signals with more accurate vascular boundaries. With the help of structural image, our method can reconstruct the 3D image of the vascular network more precisely and perform better in deep areas. The images of vessels of palm are used to compare our new technique with previous common parts extraction method experimentally. The results show that our method removes the tail artifacts more thoroughly and has a significant advantage in imaging deep vessels.

Analysis of sensitivity in quantitative micro-elastography

Quantitative micro-elastography (QME), a variant of compression optical coherence elastography (OCE), is a technique to image tissue elasticity on the microscale. QME has been proposed for a range of applications, most notably tumor margin assessment in breast-conserving surgery. However, QME sensitivity, a key imaging metric, has yet to be systematically analyzed. Consequently, it is difficult to optimize imaging performance and to assess the potential of QME in new application areas. To address this, we present a framework for analyzing sensitivity that incorporates the three main steps in QME image formation: mechanical deformation, its detection using optical coherence tomography (OCT), and signal processing used to estimate elasticity. Firstly, we present an analytical model of QME sensitivity, validated by experimental data, and demonstrate that sub-kPa elasticity sensitivity can be achieved in QME. Using silicone phantoms, we demonstrate that sensitivity is dependent on friction, OCT focus depth, and averaging methods in signal processing. For the first time, we show that whilst lubrication of layer improves accuracy by reducing surface friction, it reduces sensitivity due to the time-dependent effect of lubricant exudation from the layer boundaries resulting in increased friction. Furthermore, we demonstrate how signal processing in QME provides a trade-off between sensitivity and resolution that can be used to optimize imaging performance. We believe that our framework to analyze sensitivity can help to sustain the development of QME and, also, that it can be readily adapted to other OCE techniques.

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.

Clinical feasibility of optical coherence micro-elastography for imaging tumor margins in breast-conserving surgery

It has been demonstrated that optical coherence micro-elastography (OCME) provides additional contrast of tumor compared to optical coherence tomography (OCT) alone. Previous studies, however, have predominantly been performed on mastectomy specimens. Such specimens typically differ substantially in composition and geometry from the more clinically relevant wide-local excision (WLE) specimens excised during breast-conserving surgery. As a result, it remains unclear if the mechanical contrast observed is maintained in WLE specimens. In this manuscript, we begin to address this issue by performing a feasibility study of OCME on 17 freshly excised, intact WLE specimens. In addition, we present two developments required to sustain the progression of OCME towards intraoperative deployment. First, to enable the rapid visualization of en face images required for intraoperative assessment, we describe an automated segmentation algorithm to fuse en face micro-elastograms with OCT images to provide dual contrast images. Secondly, to validate contrast in micro-elastograms, we present a method that enables co-registration of en face images with histology of WLE specimens, sectioned in the orthogonal plane, without any modification to the standard clinical workflow. We present a summary of the observations across the 17 specimens imaged in addition to representative micro-elastograms and OCT images demonstrating contrast in a number of tumor margins, including those involved by invasive ductal carcinoma, mucinous carcinoma, and solid-papillary carcinoma. The results presented here demonstrate the potential of OCME for imaging tumor margins.

Doppler OCT clutter rejection using variance minimization and offset extrapolation

Doppler optical coherence tomography (OCT) is widely used for high-resolution mapping of flow velocities and is based on analysis of temporal changes in the phase of an OCT signal (i.e., how fast the OCT signal rotates in the complex plane). Determination of the rate of phase change or rotation speed critically depends on the center of rotation. Here, we demonstrate the bias in high-pass filtering, the current widely used method to determine the center of rotation, and propose two advanced methods for Doppler OCT clutter rejection. The bias in the high-pass filtering method becomes increasingly significant with lower velocities or larger signal noise. Two novel methods based on variance minimization and offset extrapolation can potentially reduce this bias and thereby improve the accuracy of Doppler OCT measurements of flow velocities, even for low-velocity and/or high-noise signals. The two novel methods and the current standard method (high-pass filtering) have been tested in combination with several currently used velocity measurement algorithms: Kasai, autocorrelation function fitting, and maximum likelihood estimation. The newly proposed methods are shown to improve the accuracy in both the center of rotation and resultant velocity by up to 60 percentage points and reduce the flow conservation error by 30% when applied to in vivo cerebral blood flow imaging of the rodent brain cortex.

Wide-field quantitative micro-elastography of human breast tissue

Currently, 20-30% of patients undergoing breast-conserving surgery require a second surgery due to insufficient surgical margins in the initial procedure. We have developed a wide-field quantitative micro-elastography system for the assessment of tumor margins. In this technique, we map tissue elasticity over a field-of-view of ~46 × 46 mm. We performed wide-field quantitative micro-elastography on thirteen specimens of freshly excised tissue acquired from patients undergoing a mastectomy. We present wide-field optical coherence tomography (OCT) images, qualitative (strain) micro-elastograms and quantitative (elasticity) micro-elastograms, acquired in 10 minutes. We demonstrate that wide-field quantitative micro-elastography can extend the range of tumors visible using OCT-based elastography by providing contrast not present in either OCT or qualitative micro-elastography and, in addition, can reduce imaging artifacts caused by a lack of contact between tissue and the imaging window. Also, we describe how the combined evaluation of OCT, qualitative micro-elastograms and quantitative micro-elastograms can improve the visualization of tumor.

Temporal artifact minimization in sonoelastography through optimal selection of imaging parameters

Sonoelastography is an ultrasonic technique that uses Kasai's autocorrelation algorithms to generate qualitative images of tissue elasticity using external mechanical vibrations. In the absence of synchronization between the mechanical vibration device and the ultrasound system, the random initial phase and finite ensemble length of the data packets result in temporal artifacts in the sonoelastography frames and, consequently, in degraded image quality. In this work, the analytic derivation of an optimal selection of acquisition parameters (i.e., pulse repetition frequency, vibration frequency, and ensemble length) is developed in order to minimize these artifacts, thereby eliminating the need for complex device synchronization. The proposed rule was verified through experiments with heterogeneous phantoms, where the use of optimally selected parameters increased the average contrast-to-noise ratio (CNR) by more than 200% and reduced the CNR standard deviation by 400% when compared to the use of arbitrarily selected imaging parameters. Therefore, the results suggest that the rule for specific selection of acquisition parameters becomes an important tool for producing high quality sonoelastography images.

Comparison of amplitude-decorrelation, speckle-variance and phase-variance OCT angiography methods for imaging the human retina and choroid

We compared the performance of three OCT angiography (OCTA) methods: speckle variance, amplitude decorrelation and phase variance for imaging of the human retina and choroid. Two averaging methods, split spectrum and volume averaging, were compared to assess the quality of the OCTA vascular images. All data were acquired using a swept-source OCT system at 1040 nm central wavelength, operating at 100,000 A-scans/s. We performed a quantitative comparison using a contrast-to-noise (CNR) metric to assess the capability of the three methods to visualize the choriocapillaris layer. For evaluation of the static tissue noise suppression in OCTA images we proposed to calculate CNR between the photoreceptor/RPE complex and the choriocapillaris layer. Finally, we demonstrated that implementation of intensity-based OCT imaging and OCT angiography methods allows for visualization of retinal and choroidal vascular layers known from anatomic studies in retinal preparations. OCT projection imaging of data flattened to selected retinal layers was implemented to visualize retinal and choroidal vasculature. User guided vessel tracing was applied to segment the retinal vasculature. The results were visualized in a form of a skeletonized 3D model.

Effects of data acquisition parameters on the quality of sonoelastographic imaging

Sonoelastography is an ultrasonic technique that provides qualitative and quantitative images of tissue elasticity. Even though the Kasai variance estimator is a key part of the sonoelastographic image formation, there are no studies that demonstrate that its performance using discrete time signals and finite sized ensemble lengths is optimal. In this work, the influence of the selection of acquisition parameters (pulse repetition frequency or PRF, vibration frequency, and ensemble length) on the quality of the elastograms is studied. Simulations are carried out to define the optimal PRF and ensemble length given a vibration frequency in order to avoid artifacts which can severely degrade image quality. This empirical criterion is supported by sonoelastography experiments performed using two commercial scanners, where the variability increased from 4% to 42% at the worst selection of acquisition parameters. Although a further mathematical proof of the empirical findings is required, these results suggest that careful selection of PRF, vibration frequency and ensemble lengths is required to ensure unbiased sonoelastograms.

Simultaneous estimation of bidirectional particle flow and relative flux using MUSIC-OCT: phantom studies

In an optical coherence tomography (OCT) scan from a living tissue, red blood cells (RBCs) are the major source of backscattering signal from moving particles within microcirculatory system. Measuring the concentration and velocity of RBC particles allows assessment of RBC flux and flow, respectively, to assess tissue perfusion and oxygen/nutrition exchange rates within micro-structures. In this paper, we propose utilizing spectral estimation techniques to simultaneously quantify bi-directional particle flow and relative flux by spectral estimation of the received OCT signal from moving particles within capillary tubes embedded in tissue mimicking phantoms. The proposed method can be directly utilized for in vivo quantification of capillaries and microvessels. Compared to the existing methods in the literature that can either quantify flow direction or power, our proposed method allows simultaneous flow (velocity) direction and relative flux (power) estimation.

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.

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.