Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy
Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typical...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037024000722 |
| _version_ | 1797235600447766528 |
|---|---|
| author | Vittorio Bianco Marika Valentino Daniele Pirone Lisa Miccio Pasquale Memmolo Valentina Brancato Luigi Coppola Giovanni Smaldone Massimiliano D’Aiuto Gennaro Mossetti Marco Salvatore Pietro Ferraro |
| author_facet | Vittorio Bianco Marika Valentino Daniele Pirone Lisa Miccio Pasquale Memmolo Valentina Brancato Luigi Coppola Giovanni Smaldone Massimiliano D’Aiuto Gennaro Mossetti Marco Salvatore Pietro Ferraro |
| author_sort | Vittorio Bianco |
| collection | DOAJ |
| description | Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm2) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient’s slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist. |
| first_indexed | 2024-04-24T16:50:32Z |
| format | Article |
| id | doaj.art-4fe15282481c46b49e9e0ce03609c987 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-04-24T16:50:32Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-4fe15282481c46b49e9e0ce03609c9872024-03-29T05:49:49ZengElsevierComputational and Structural Biotechnology Journal2001-03702024-12-0124225236Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic MicroscopyVittorio Bianco0Marika Valentino1Daniele Pirone2Lisa Miccio3Pasquale Memmolo4Valentina Brancato5Luigi Coppola6Giovanni Smaldone7Massimiliano D’Aiuto8Gennaro Mossetti9Marco Salvatore10Pietro Ferraro11CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, ItalyCNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy; DIETI, Department of Electrical Engineering and Information Technologies, University of Naples “Federico II”, via Claudio 21, 80125 Napoli, ItalyCNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, Italy; Corresponding author.CNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, ItalyCNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, ItalyIRCCS SYNLAB SDN, Via E. Gianturco 113, Napoli 80143, ItalyIRCCS SYNLAB SDN, Via E. Gianturco 113, Napoli 80143, ItalyIRCCS SYNLAB SDN, Via E. Gianturco 113, Napoli 80143, ItalyClinica Villa Fiorita, Via Filippo Saporito 24, 81031 Aversa, Caserta, ItalyPathological Anatomy Service, Casa di Cura Maria Rosaria, Via Colle San Bartolomeo 50, 80045 Pompei, Napoli, ItalyIRCCS SYNLAB SDN, Via E. Gianturco 113, Napoli 80143, ItalyCNR-ISASI, Institute of Applied Sciences and Intelligent Systems “E. Caianiello”, Via Campi Flegrei 34, 80078 Pozzuoli, Napoli, ItalyBreast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm2) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient’s slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist.http://www.sciencedirect.com/science/article/pii/S2001037024000722Quantitative Phase ImagingFourier Ptychographic MicroscopyStain-free tissue analysisComputational pathologyFractal geometryMachine learning |
| spellingShingle | Vittorio Bianco Marika Valentino Daniele Pirone Lisa Miccio Pasquale Memmolo Valentina Brancato Luigi Coppola Giovanni Smaldone Massimiliano D’Aiuto Gennaro Mossetti Marco Salvatore Pietro Ferraro Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy Computational and Structural Biotechnology Journal Quantitative Phase Imaging Fourier Ptychographic Microscopy Stain-free tissue analysis Computational pathology Fractal geometry Machine learning |
| title | Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy |
| title_full | Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy |
| title_fullStr | Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy |
| title_full_unstemmed | Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy |
| title_short | Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy |
| title_sort | classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain free slides by fractal biomarkers in fourier ptychographic microscopy |
| topic | Quantitative Phase Imaging Fourier Ptychographic Microscopy Stain-free tissue analysis Computational pathology Fractal geometry Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2001037024000722 |
| work_keys_str_mv | AT vittoriobianco classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT marikavalentino classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT danielepirone classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT lisamiccio classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT pasqualememmolo classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT valentinabrancato classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT luigicoppola classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT giovannismaldone classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT massimilianodaiuto classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT gennaromossetti classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT marcosalvatore classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy AT pietroferraro classifyingbreastcancerandfibroadenomatissuebiopsiesfromparaffinedstainfreeslidesbyfractalbiomarkersinfourierptychographicmicroscopy |