CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance

Abstract Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology ope...

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Autores principales:	Sara P. Oliveira, Pedro C. Neto, João Fraga, Diana Montezuma, Ana Monteiro, João Monteiro, Liliana Ribeiro, Sofia Gonçalves, Isabel M. Pinto, Jaime S. Cardoso
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7259c74c95484c5ea21e6474921c24a9
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spelling	oai:doaj.org-article:7259c74c95484c5ea21e6474921c24a92021-12-02T18:30:39ZCAD systems for colorectal cancer from WSI are still not ready for clinical acceptance10.1038/s41598-021-93746-z2045-2322https://doaj.org/article/7259c74c95484c5ea21e6474921c24a92021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93746-zhttps://doaj.org/toc/2045-2322Abstract Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology opened up many research opportunities, allowing the development of more advanced image processing techniques, as well as artificial intelligence (AI) methodologies. Nevertheless, despite colorectal cancer (CRC) being the second deadliest cancer type worldwide, with increasing incidence rates, the application of AI for CRC diagnosis, particularly on whole-slide images (WSI), is still a young field. In this review, we analyse some relevant works published on this particular task and highlight the limitations that hinder the application of these works in clinical practice. We also empirically investigate the feasibility of using weakly annotated datasets to support the development of computer-aided diagnosis systems for CRC from WSI. Our study underscores the need for large datasets in this field and the use of an appropriate learning methodology to gain the most benefit from partially annotated datasets. The CRC WSI dataset used in this study, containing 1,133 colorectal biopsy and polypectomy samples, is available upon reasonable request.Sara P. OliveiraPedro C. NetoJoão FragaDiana MontezumaAna MonteiroJoão MonteiroLiliana RibeiroSofia GonçalvesIsabel M. PintoJaime S. CardosoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Sara P. Oliveira Pedro C. Neto João Fraga Diana Montezuma Ana Monteiro João Monteiro Liliana Ribeiro Sofia Gonçalves Isabel M. Pinto Jaime S. Cardoso CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
description	Abstract Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology opened up many research opportunities, allowing the development of more advanced image processing techniques, as well as artificial intelligence (AI) methodologies. Nevertheless, despite colorectal cancer (CRC) being the second deadliest cancer type worldwide, with increasing incidence rates, the application of AI for CRC diagnosis, particularly on whole-slide images (WSI), is still a young field. In this review, we analyse some relevant works published on this particular task and highlight the limitations that hinder the application of these works in clinical practice. We also empirically investigate the feasibility of using weakly annotated datasets to support the development of computer-aided diagnosis systems for CRC from WSI. Our study underscores the need for large datasets in this field and the use of an appropriate learning methodology to gain the most benefit from partially annotated datasets. The CRC WSI dataset used in this study, containing 1,133 colorectal biopsy and polypectomy samples, is available upon reasonable request.
format	article
author	Sara P. Oliveira Pedro C. Neto João Fraga Diana Montezuma Ana Monteiro João Monteiro Liliana Ribeiro Sofia Gonçalves Isabel M. Pinto Jaime S. Cardoso
author_facet	Sara P. Oliveira Pedro C. Neto João Fraga Diana Montezuma Ana Monteiro João Monteiro Liliana Ribeiro Sofia Gonçalves Isabel M. Pinto Jaime S. Cardoso
author_sort	Sara P. Oliveira
title	CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
title_short	CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
title_full	CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
title_fullStr	CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
title_full_unstemmed	CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
title_sort	cad systems for colorectal cancer from wsi are still not ready for clinical acceptance
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7259c74c95484c5ea21e6474921c24a9
work_keys_str_mv	AT sarapoliveira cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT pedrocneto cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT joaofraga cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT dianamontezuma cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT anamonteiro cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT joaomonteiro cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT lilianaribeiro cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT sofiagoncalves cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT isabelmpinto cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance AT jaimescardoso cadsystemsforcolorectalcancerfromwsiarestillnotreadyforclinicalacceptance
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CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance

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