Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study
The possibility to assess molecular-biological and morphological features of particular breast cancer types can improve the precision of resection margin detection and enable accurate determining of the tumor aggressiveness, which is important for treatment selection. To enable reliable differentiat...
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MDPI AG
2020-11-01
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author | Ekaterina V. Gubarkova Elena B. Kiseleva Marina A. Sirotkina Dmitry A. Vorontsov Ksenia A. Achkasova Sergey S. Kuznetsov Konstantin S. Yashin Aleksander L. Matveyev Aleksander A. Sovetsky Lev A. Matveev Anton A. Plekhanov Alexey Y. Vorontsov Vladimir Y. Zaitsev Natalia D. Gladkova |
author_facet | Ekaterina V. Gubarkova Elena B. Kiseleva Marina A. Sirotkina Dmitry A. Vorontsov Ksenia A. Achkasova Sergey S. Kuznetsov Konstantin S. Yashin Aleksander L. Matveyev Aleksander A. Sovetsky Lev A. Matveev Anton A. Plekhanov Alexey Y. Vorontsov Vladimir Y. Zaitsev Natalia D. Gladkova |
author_sort | Ekaterina V. Gubarkova |
collection | DOAJ |
description | The possibility to assess molecular-biological and morphological features of particular breast cancer types can improve the precision of resection margin detection and enable accurate determining of the tumor aggressiveness, which is important for treatment selection. To enable reliable differentiation of breast-cancer subtypes and evaluation of resection margin, without performing conventional histological procedures, here we apply cross-polarization optical coherence tomography (CP-OCT) and compare it with a novel variant of compressional optical coherence elastography (C-OCE) in terms of the diagnostic accuracy (Ac) with histological verification. The study used 70 excised breast cancer specimens with different morphological structure and molecular status (Luminal A, Luminal B, Her2/Neo+, non-luminal and triple-negative cancer). Our first aim was to formulate convenient criteria of visual assessment of CP-OCT and C-OCE images intended (i) to differentiate tumorous and non-tumorous tissues and (ii) to enable more precise differentiation among different malignant states. We identified such criteria based on the presence of heterogeneities and characteristics of signal attenuation in CP-OCT images, as well as the presence of inclusions/mosaic structures combined with visually feasible assessment of several stiffness grades in C-OCE images. Secondly, we performed a blinded reader study of the Ac of C-OCE versus CP-OCT, for delineation of tumorous versus non-tumorous tissues followed by identification of breast cancer subtypes. For tumor detection, C-OCE showed higher specificity than CP-OCT (97.5% versus 93.3%) and higher Ac (96.0 versus 92.4%). For the first time, the Ac of C-OCE and CP-OCT were evaluated for differentiation between non-invasive and invasive breast cancer (90.4% and 82.5%, respectively). Furthermore, for invasive cancers, the difference between invasive but low-aggressive and highly-aggressive subtypes can be detected. For differentiation between non-tumorous tissue and low-aggressive breast-cancer subtypes, Ac was 95.7% for C-OCE and 88.1% for CP-OCT. For differentiation between non-tumorous tissue and highly-aggressive breast cancers, Ac was found to be 98.3% for C-OCE and 97.2% for CP-OCT. In all cases C-OCE showed better diagnostic parameters independently of the tumor type. These findings confirm the high potential of OCT-based examinations for rapid and accurate diagnostics during breast conservation surgery. |
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spelling | doaj.art-6ac52df4ee384f659f09b5a5d45ae3972023-11-20T22:05:57ZengMDPI AGDiagnostics2075-44182020-11-01101299410.3390/diagnostics10120994Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative StudyEkaterina V. Gubarkova0Elena B. Kiseleva1Marina A. Sirotkina2Dmitry A. Vorontsov3Ksenia A. Achkasova4Sergey S. Kuznetsov5Konstantin S. Yashin6Aleksander L. Matveyev7Aleksander A. Sovetsky8Lev A. Matveev9Anton A. Plekhanov10Alexey Y. Vorontsov11Vladimir Y. Zaitsev12Natalia D. Gladkova13Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaDepartment of Oncology, Nizhny Novgorod Regional Oncologic Hospital, 603126 Nizhny Novgorod, RussiaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaDepartment of Pathology, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaUniversity Clinic, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaLaboratory of Multidimensional Signal Processing, Institute of Applied Physics of the Russian Academy of Sciences, 603950 Nizhny Novgorod, RussiaLaboratory of Wave Methods for Studying Structurally Inhomogeneous Media, Institute of Applied Physics of the Russian Academy of Sciences, 603950 Nizhny Novgorod, RussiaLaboratory of Wave Methods for Studying Structurally Inhomogeneous Media, Institute of Applied Physics of the Russian Academy of Sciences, 603950 Nizhny Novgorod, RussiaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaDepartment of Oncology, Nizhny Novgorod Regional Oncologic Hospital, 603126 Nizhny Novgorod, RussiaLaboratory of Wave Methods for Studying Structurally Inhomogeneous Media, Institute of Applied Physics of the Russian Academy of Sciences, 603950 Nizhny Novgorod, RussiaInstitute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, 603950 Nizhny Novgorod, RussiaThe possibility to assess molecular-biological and morphological features of particular breast cancer types can improve the precision of resection margin detection and enable accurate determining of the tumor aggressiveness, which is important for treatment selection. To enable reliable differentiation of breast-cancer subtypes and evaluation of resection margin, without performing conventional histological procedures, here we apply cross-polarization optical coherence tomography (CP-OCT) and compare it with a novel variant of compressional optical coherence elastography (C-OCE) in terms of the diagnostic accuracy (Ac) with histological verification. The study used 70 excised breast cancer specimens with different morphological structure and molecular status (Luminal A, Luminal B, Her2/Neo+, non-luminal and triple-negative cancer). Our first aim was to formulate convenient criteria of visual assessment of CP-OCT and C-OCE images intended (i) to differentiate tumorous and non-tumorous tissues and (ii) to enable more precise differentiation among different malignant states. We identified such criteria based on the presence of heterogeneities and characteristics of signal attenuation in CP-OCT images, as well as the presence of inclusions/mosaic structures combined with visually feasible assessment of several stiffness grades in C-OCE images. Secondly, we performed a blinded reader study of the Ac of C-OCE versus CP-OCT, for delineation of tumorous versus non-tumorous tissues followed by identification of breast cancer subtypes. For tumor detection, C-OCE showed higher specificity than CP-OCT (97.5% versus 93.3%) and higher Ac (96.0 versus 92.4%). For the first time, the Ac of C-OCE and CP-OCT were evaluated for differentiation between non-invasive and invasive breast cancer (90.4% and 82.5%, respectively). Furthermore, for invasive cancers, the difference between invasive but low-aggressive and highly-aggressive subtypes can be detected. For differentiation between non-tumorous tissue and low-aggressive breast-cancer subtypes, Ac was 95.7% for C-OCE and 88.1% for CP-OCT. For differentiation between non-tumorous tissue and highly-aggressive breast cancers, Ac was found to be 98.3% for C-OCE and 97.2% for CP-OCT. In all cases C-OCE showed better diagnostic parameters independently of the tumor type. These findings confirm the high potential of OCT-based examinations for rapid and accurate diagnostics during breast conservation surgery.https://www.mdpi.com/2075-4418/10/12/994breast cancercross-polarization optical coherence tomography (CP-OCT)compressional optical coherence elastography (C-OCE)image assessment |
spellingShingle | Ekaterina V. Gubarkova Elena B. Kiseleva Marina A. Sirotkina Dmitry A. Vorontsov Ksenia A. Achkasova Sergey S. Kuznetsov Konstantin S. Yashin Aleksander L. Matveyev Aleksander A. Sovetsky Lev A. Matveev Anton A. Plekhanov Alexey Y. Vorontsov Vladimir Y. Zaitsev Natalia D. Gladkova Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study Diagnostics breast cancer cross-polarization optical coherence tomography (CP-OCT) compressional optical coherence elastography (C-OCE) image assessment |
title | Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study |
title_full | Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study |
title_fullStr | Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study |
title_full_unstemmed | Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study |
title_short | Diagnostic Accuracy of Cross-Polarization OCT and OCT-Elastography for Differentiation of Breast Cancer Subtypes: Comparative Study |
title_sort | diagnostic accuracy of cross polarization oct and oct elastography for differentiation of breast cancer subtypes comparative study |
topic | breast cancer cross-polarization optical coherence tomography (CP-OCT) compressional optical coherence elastography (C-OCE) image assessment |
url | https://www.mdpi.com/2075-4418/10/12/994 |
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