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 met...

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Autores principales:	Anton A. Plekhanov, Marina A. Sirotkina, Alexander A. Sovetsky, Ekaterina V. Gubarkova, Sergey S. Kuznetsov, Alexander L. Matveyev, Lev A. Matveev, Elena V. Zagaynova, Natalia D. Gladkova, Vladimir Y. Zaitsev
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8a5caa539630417594d1a9c3e5eb66d6
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spelling	oai:doaj.org-article:8a5caa539630417594d1a9c3e5eb66d62021-12-02T15:32:59ZHistological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography10.1038/s41598-020-68631-w2045-2322https://doaj.org/article/8a5caa539630417594d1a9c3e5eb66d62020-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-68631-whttps://doaj.org/toc/2045-2322Abstract 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.Anton A. PlekhanovMarina A. SirotkinaAlexander A. SovetskyEkaterina V. GubarkovaSergey S. KuznetsovAlexander L. MatveyevLev A. MatveevElena V. ZagaynovaNatalia D. GladkovaVladimir Y. ZaitsevNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-16 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Anton A. Plekhanov Marina A. Sirotkina Alexander A. Sovetsky Ekaterina V. Gubarkova Sergey S. Kuznetsov Alexander L. Matveyev Lev A. Matveev Elena V. Zagaynova Natalia D. Gladkova Vladimir Y. Zaitsev Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
description	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.
format	article
author	Anton A. Plekhanov Marina A. Sirotkina Alexander A. Sovetsky Ekaterina V. Gubarkova Sergey S. Kuznetsov Alexander L. Matveyev Lev A. Matveev Elena V. Zagaynova Natalia D. Gladkova Vladimir Y. Zaitsev
author_facet	Anton A. Plekhanov Marina A. Sirotkina Alexander A. Sovetsky Ekaterina V. Gubarkova Sergey S. Kuznetsov Alexander L. Matveyev Lev A. Matveev Elena V. Zagaynova Natalia D. Gladkova Vladimir Y. Zaitsev
author_sort	Anton A. Plekhanov
title	Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
title_short	Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
title_full	Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
title_fullStr	Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
title_full_unstemmed	Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography
title_sort	histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by optical coherence elastography
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/8a5caa539630417594d1a9c3e5eb66d6
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Histological validation of in vivo assessment of cancer tissue inhomogeneity and automated morphological segmentation enabled by Optical Coherence Elastography

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