Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer
Breast cancer (BC) diagnosis is made by a pathologist who analyzes a portion of the breast tissue under the microscope and performs a histological evaluation. This evaluation aims to determine the grade of cellular differentiation and the aggressiveness of the tumor by the Nottingham Grade Classific...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/15/5649 |
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| author | Hayde Peregrina-Barreto Valeria Y. Ramirez-Guatemala Gabriela C. Lopez-Armas Jose A. Cruz-Ramos |
| author_facet | Hayde Peregrina-Barreto Valeria Y. Ramirez-Guatemala Gabriela C. Lopez-Armas Jose A. Cruz-Ramos |
| author_sort | Hayde Peregrina-Barreto |
| collection | DOAJ |
| description | Breast cancer (BC) diagnosis is made by a pathologist who analyzes a portion of the breast tissue under the microscope and performs a histological evaluation. This evaluation aims to determine the grade of cellular differentiation and the aggressiveness of the tumor by the Nottingham Grade Classification System (NGS). Nowadays, digital pathology is an innovative tool for pathologists in diagnosis and acquiring new learning. However, a recurring problem in health services is the excessive workload in all medical services. For this reason, it is required to develop computational tools that assist histological evaluation. This work proposes a methodology for the quantitative analysis of BC tissue that follows NGS. The proposed methodology is based on digital image processing techniques through which the BC tissue can be characterized automatically. Moreover, the proposed nuclei characterization was helpful for grade differentiation in carcinoma images of the BC tissue reaching an 0.84 accuracy. In addition, a metric was proposed to assess the likelihood of a structure in the tissue corresponding to a tubule by considering spatial and geometrical characteristics between lumina and its surrounding nuclei, reaching an accuracy of 0.83. Tests were performed from different databases and under various magnification and staining contrast conditions, showing that the methodology is reliable for histological breast tissue analysis. |
| first_indexed | 2024-03-09T12:11:58Z |
| format | Article |
| id | doaj.art-9ca5f0f69b13466bac24bb4130b5959a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:11:58Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9ca5f0f69b13466bac24bb4130b5959a2023-11-30T22:51:03ZengMDPI AGSensors1424-82202022-07-012215564910.3390/s22155649Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast CancerHayde Peregrina-Barreto0Valeria Y. Ramirez-Guatemala1Gabriela C. Lopez-Armas2Jose A. Cruz-Ramos3Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro 1, Santa Maria Tonantzintla, San Andres Cholula 72840, Puebla, MexicoInstituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro 1, Santa Maria Tonantzintla, San Andres Cholula 72840, Puebla, MexicoCentro de Enseñanza Técnica Industrial, C. Nueva Escocia 1885, Guadalajara 44638, Jalisco, MexicoInstituto Jalisciense de Cancerología, Coronel Calderón 715, Guadalajara 44280, Jalisco, MexicoBreast cancer (BC) diagnosis is made by a pathologist who analyzes a portion of the breast tissue under the microscope and performs a histological evaluation. This evaluation aims to determine the grade of cellular differentiation and the aggressiveness of the tumor by the Nottingham Grade Classification System (NGS). Nowadays, digital pathology is an innovative tool for pathologists in diagnosis and acquiring new learning. However, a recurring problem in health services is the excessive workload in all medical services. For this reason, it is required to develop computational tools that assist histological evaluation. This work proposes a methodology for the quantitative analysis of BC tissue that follows NGS. The proposed methodology is based on digital image processing techniques through which the BC tissue can be characterized automatically. Moreover, the proposed nuclei characterization was helpful for grade differentiation in carcinoma images of the BC tissue reaching an 0.84 accuracy. In addition, a metric was proposed to assess the likelihood of a structure in the tissue corresponding to a tubule by considering spatial and geometrical characteristics between lumina and its surrounding nuclei, reaching an accuracy of 0.83. Tests were performed from different databases and under various magnification and staining contrast conditions, showing that the methodology is reliable for histological breast tissue analysis.https://www.mdpi.com/1424-8220/22/15/5649automatic classificationbreast cancer diagnosisdigital image processinghistological differentiation grade |
| spellingShingle | Hayde Peregrina-Barreto Valeria Y. Ramirez-Guatemala Gabriela C. Lopez-Armas Jose A. Cruz-Ramos Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer Sensors automatic classification breast cancer diagnosis digital image processing histological differentiation grade |
| title | Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer |
| title_full | Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer |
| title_fullStr | Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer |
| title_full_unstemmed | Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer |
| title_short | Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer |
| title_sort | characterization of nuclear pleomorphism and tubules in histopathological images of breast cancer |
| topic | automatic classification breast cancer diagnosis digital image processing histological differentiation grade |
| url | https://www.mdpi.com/1424-8220/22/15/5649 |
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