Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography

Abstract

We present a non-invasive (albeit contact) method based on optical coherence elastography (oce) enabling the in vivo segmentation of morphological tissue constituents, in particular, monitoring of morphological alterations during both tumor development and its response to therapies. the method uses compressional OCE to reconstruct tissue stiffness map as the first step. Then the OCE-image is divided into regions, for which the Young's modulus (stiffness) falls in specific ranges corresponding to the morphological constituents to be discriminated. These stiffness ranges (characteristic "stiffness spectra") are initially determined by careful comparison of the "gold-standard" histological data and the OCE-based stiffness map for the corresponding tissue regions. After such pre-calibration, the results of morphological segmentation of oce-images demonstrate a striking similarity with the histological results in terms of percentage of the segmented zones. to validate the sensitivity of the oce-method and demonstrate its high correlation with conventional histological segmentation we present results obtained in vivo on a murine model of breast cancer in comparative experimental study of the efficacy of two antitumor chemotherapeutic drugs with different mechanisms of action. The new technique allowed in vivo monitoring and quantitative segmentation of (1) viable, (2) dystrophic, (3) necrotic tumor cells and (4) edema zones very similar to morphological segmentation of histological images. numerous applications in other experimental/clinical areas requiring rapid, nearly real-time, quantitative assessment of tissue structure can be foreseen.

Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study

“…An advanced variant of phase-sensitive compression OCE [37,39,[51][52][53][54][55] was used to visualize inter-frame strains in the tissue and subsequently map the Young modulus. The probe was slightly pressed onto the studied sample surface, and strain distribution in the probe vicinity was reconstructed.…”

“…Attention to the problem of determining tissue stiffness (elastographic mapping) by optical coherence elastography (OCE) methods has been increasing in recent years [34][35][36][37]. Sufficiently high resolution of quantitative stiffness maps enabled by compressional OCE opened the possibility to perform morphological segmentations of tumor tissue constituents very similar to morphological segmentation of conventional histological images [25,38,39]. In these studies of experimental tumor models on animals, this technique allowed in vivo monitoring of morphological variation in tumor tissue during tumor growth and response to therapies.…”

Simulation of multimodal optical coherence tomography for biomedical diagnostics: comprehensive full-wave description based on ballistic scattering of arbitrary-profile beams

“…(c) is a 3D image for a density of scatterers closer to density of biological cells in tissues with an axial flow 10 m in diameter imitating a blood capillary which is initially indistinguishable against the background; (d) the same refocused image, in which the capillary outside the focal depth becomes well visible with the maximal resolution (corresponding to the focus radius) and looks as a dark channel, which is due to flow-related breaking of the constructive interference in the refocused image; particle displacement between the subsequent A-scans is Finally, the next example relates to elastographic imaging of local strains in the simulated region, in which a prescribed strain-induced variation in the positions of scatterers is introduced. Strain mapping is the basic step in realization of compression optical coherence elastography (C-OCE) 23 which in recent years opened a broad range of biomedical applications: elastographic differentiation of tumorous versus normal tissue 32,33,34 , demonstrations of detailed morphological segmentation of heterogeneous tumor tissues using differences in elasticity among various morphological components 35,36 ; studying complex 3D strain fields of thermo-mechanical origin in corneal tissue subjected to laser treatment in the context of refraction correction 37 ; detection of insufficient stability of laser-fabricated cartilaginous implants 38 ; studying deformations of osmotic origin during tissue impregnation by non-isotonic liquids 39,23 . In view of these very different applications, numerical simulations of exactly controllable arbitrarily complex deformations with possibility to flexibly vary OCT-system parameters, signal-to-noise ratios (SNR), etc., opens unprecedented prospects for detailed multi-parameter studies of elastographic processing in OCT.…”

Flexible Computationally Efficient Platform for Simulating Scan Formation in Optical Coherence Tomography with Accounting for Arbitrary Motions of Scatterers

“…In recent years, some other OCT-modalities are emerging in biomedical research and clinical practice and have already proved their high utility for a broad range of various biomedical applications. In particular, one can mention OCT-based angiography [3][4][5][6] (already translated to some clinical applications, e.g., [7,8]), mapping of viscous properties of biological liquids [9,10], visualization of deformations (for elastographic and other applications) [11][12][13][14] including combined application of a few modalities [15,16]. The principles of OCT-based elastography and angiography are essentially based on the analysis of motions of scatterers in acquired sequences of OCT scans.…”