Lev A. Matveev

Elastographic mapping in optical coherence tomography using an unconventional approach based on correlation stability

Abstract. An approach to elastographic mapping in optical coherence tomography (OCT) using comparison of correlation stability of sequentially obtained intensity OCT images of the studied strained tissue is discussed. The basic idea is that for stiffer regions, the OCT image is distorted to a smaller degree. Consequently, cross-correlation maps obtained with compensation of trivial translational motion of the image parts using a sliding correlation window can represent the spatial distribution of the relative tissue stiffness. An important advantage of the proposed approach is that it allows one to avoid the stage of local-strain reconstruction via error-sensitive numerical differentiation of experimentally determined displacements. Another advantage is that the correlation stability (CS) approach intrinsically implies that for deformed softer tissue regions, cross-correlation should already be strongly decreased in contrast to the approaches based on initial reconstruction of displacements. This feature determines a much wider strain range of operability than the proposed approach and is favorable for its free-hand implementation using the OCT probe itself to deform the tissue. The CS approach can be implemented using either the image elements reflecting morphological structure of the tissue or performing the speckle-level cross-correlation. Examples of numerical simulations and experimental demonstrations using both phantom samples and in vivo obtained OCT images are presented.

A model for simulating speckle-pattern evolution based on close to reality procedures used in spectral-domain OCT

A robust model for simulating speckle pattern evolution in optical coherence tomography (OCT) depending on the OCT system parameters and tissue deformation is reported. The model is based on application of close to reality procedures used in spectral-domain OCT scanners. It naturally generates images reproducing properties of real images in spectral-domain OCT, including the pixelized structure and finite depth of unambiguous imaging, influence of the optical spectrum shape, dependence on the optical wave frequency and coherence length, influence of the tissue straining, etc. Good agreement with generally accepted speckle features and properties of real OCT images is demonstrated.

Novel methods for elasticity characterization using optical coherence tomography: Brief review and future prospects

Abstract In this paper, a brief overview of several recently proposed approaches to elastographic characterization of biological tissues using optical coherence tomography is presented. A common feature of these “unconventional” approaches is that unlike most others, they do not rely on a two-step process of first reconstructing the particle displacements and then performing its error-prone differentiation in order to determine the local strains. Further, several variants of these new approaches were proposed and demonstrated essentially independently and are based on significantly different principles. Despite the seeming differences, these techniques open up interesting prospects not only for independent usage, but also for combined implementation to provide a multifunctional investigation of elasticity of biological tissues and their rheological properties in a wider sense.

Correlation stability elastography in OCT: algorithm and in vivo demonstrations

We discuss an elastography method based on comparison of correlation stability for different parts of sequentially obtained OCT images of the studied strained tissue. The basic idea is that in stiffer regions of a deformed tissue the OCT image is distorted to a smaller degree. Thus, cross-correlation maps obtained using a sliding correlation window for compensation of trivial translational motion of the image parts can reflect the spatial inhomogeneity of the tissue stiffness distribution. An important advantage of the proposed approach is that it allows one to avoid the stage of local strain reconstruction via error-sensitive procedures of numerical differentiation of experimentally determined displacements. Another advantage is that the correlation-stability approach requires that for deformed softer tissue regions, cross-correlation should already be strongly decreased, which intrinsically implies much wider strain range of the method operability compared to other approaches and is favorable for its free-hand implementation. Generally speaking, the approach can be implemented using the cross-correlation both image features reflecting morphological structure of the tissue and speckle-level cross-correlation. Examples of numerical simulations and experimental demonstrations using both phantom samples and in vivo obtained OCT images are presented.

Practical obstacles and their mitigation strategies in compressional optical coherence elastography of biological tissues

In this paper, we point out some practical obstacles arising in realization of compressional optical coherence elastography (OCE) that have not attracted sufficient attention previously. Specifically, we discuss (i) complications in quantification of the Young modulus of tissues related to partial adhesion between the OCE probe and soft intervening reference layer sensor, (ii) distorting influence of tissue surface curvature/corrugation on the subsurface strain distribution mapping, (iii) ways of signal-to-noise ratio (SNR) enhancement in OCE strain mapping when periodic averaging is not realized, and (iv) potentially significant influence of tissue elastic nonlinearity on quantification of its stiffness. Potential practical approaches to mitigate the effects of these complications are also described.

To the problem of stiffness-contrast quantification in the correlation-stability approach to OCT elastography

In the initial variant, the recently proposed correlation-stability approach to elasticity mapping in optical coherence tomography (OCT) of tissues was intended for qualitative visualization of the relative stiffness of different regions in tissue. Further development of this approach is aimed at obtaining the stiffness ratio between different tissue regions. In the proposed modified variant, the correlation-stability approach has much in common with the speckle variance approach which is used for visualizing blood microcirculation in OCT. We present preliminary demonstrations of implementation of the modified correlation-stability approach to quantify the relative stiffness using processing of the speckle-structure variability of OCT images of deformed tissues.

Combining the correlation-stability approach to OCT elastography with the speckle-variance evaluation for quantifying the stiffness differences

We discuss an advanced variant of the correlation-stability (CS) approach to OCT elastography that is capable of quantifying the stiffness differences. The modified variant is based on natural combination of CS approach with the speckle-variance (SV) approach. It allows one to determine the strain dependence of the normalized speckle intensity variance function for two compared subsets taken from the OCT images corresponding to the initial and deformed states of the tissue. In previous studies we considered the basic dependence of the normalized speckle intensity variance function on the tissue strain under the assumption that the influence of translational displacements can be excluded, so that the residual speckle-intensity variations should be produced only by speckle blinking determined by local strains. In the present report we discuss the corresponding algorithms allowing one to exclude the above-mentioned influence of translational displacements. We demonstrate numerically the efficiency of such processing that allows for quantification of stiffness differences in the elastographic mapping based on the CS approach.

Scan-pattern and signal processing for microvasculature visualization with complex SD-OCT: tissue-motion artifacts robustness and decorrelation time - blood vessel characteristics

We propose a modification of OCT scanning pattern and corresponding signal processing for 3D visualizing blood microcirculation from complex-signal B-scans. We describe the scanning pattern modifications that increase the methods’ robustness to bulk tissue motion artifacts, with speed up to several cm/s. Based on these modifications, OCT-based angiography becomes more realistic under practical measurement conditions. For these scan patterns, we apply novel signal processing to separate the blood vessels with different decorrelation times, by varying of effective temporal diversity of processed signals.

Multimodal optical coherence tomography for in vivo imaging of brain tissue structure and microvascular network at glioblastoma

In the case of infiltrative brain tumors the surgeon faces difficulties in determining their boundaries to achieve total resection. The aim of the investigation was to evaluate the performance of multimodal OCT (MM OCT) for differential diagnostics of normal brain tissue and glioma using an experimental model of glioblastoma. The spectral domain OCT device that was used for the study provides simultaneously two modes: cross-polarization and microangiographic OCT. The comparative analysis of the both OCT modalities images from tumorous and normal brain tissue areas concurrently with histologic correlation shows certain difference between when accordingly to morphological and microvascular tissue features.

An approach to OCT-based microvascular imaging using reference-free processing of complex valued B-scans

We describe a modification of a recently proposed unconventional OCT approach to 3D microvasculature imaging based on high-pass filtering of B-scans in the lateral direction. The B-scans are acquired in M-mode-like regime with highly overlapped A-scans. The goal of the described modification is to suppress non-fluid artifacts in the resultant microcirculation images. The modification is based on the amplitude normalization procedure of complex-valued OCT signal before subsequent processing. This allows one to efficiently suppress imaging degradation due to the influence of very bright spots/lines (e.g. from hairs on the surface) and retain images of real flows inside the tissue without any artificial cut-off of the surface signal, or application of pixel-intensity thresholds, or signal classification approaches.