Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.

Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed, infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete entities, distinct from lymphocytes. TLS are associated with improved cancer prognosis but there is no standardis...

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Autores principales:	Panagiotis Barmpoutis, Matthew Di Capite, Hamzeh Kayhanian, William Waddingham, Daniel C Alexander, Marnix Jansen, Francois Ng Kee Kwong
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/729f08bcca37483ba72053fba1452226
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spelling	oai:doaj.org-article:729f08bcca37483ba72053fba14522262021-12-02T20:14:15ZTertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.1932-620310.1371/journal.pone.0256907https://doaj.org/article/729f08bcca37483ba72053fba14522262021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256907https://doaj.org/toc/1932-6203Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed, infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete entities, distinct from lymphocytes. TLS are associated with improved cancer prognosis but there is no standardised method available to quantify their presence. Previous studies have used immunohistochemistry to determine the presence of specific cells as a marker of the TLS. This has now been proven to be an underestimate of the true number of TLS. Thus, we propose a methodology for the automated identification and quantification of TLS, based on H&E slides. We subsequently determined the mathematical criteria defining a TLS. TLS regions were identified through a deep convolutional neural network and segmentation of lymphocytes was performed through an ellipsoidal model. This methodology had a 92.87% specificity at 95% sensitivity, 88.79% specificity at 98% sensitivity and 84.32% specificity at 99% sensitivity level based on 144 TLS annotated H&E slides implying that the automated approach was able to reproduce the histopathologists' assessment with great accuracy. We showed that the minimum number of lymphocytes within TLS is 45 and the minimum TLS area is 6,245μm2. Furthermore, we have shown that the density of the lymphocytes is more than 3 times those outside of the TLS. The mean density and standard deviation of lymphocytes within a TLS area are 0.0128/μm2 and 0.0026/μm2 respectively compared to 0.004/μm2 and 0.001/μm2 in non-TLS regions. The proposed methodology shows great potential for automated identification and quantification of the TLS density on digital H&E slides.Panagiotis BarmpoutisMatthew Di CapiteHamzeh KayhanianWilliam WaddinghamDaniel C AlexanderMarnix JansenFrancois Ng Kee KwongPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0256907 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Panagiotis Barmpoutis Matthew Di Capite Hamzeh Kayhanian William Waddingham Daniel C Alexander Marnix Jansen Francois Ng Kee Kwong Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
description	Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed, infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete entities, distinct from lymphocytes. TLS are associated with improved cancer prognosis but there is no standardised method available to quantify their presence. Previous studies have used immunohistochemistry to determine the presence of specific cells as a marker of the TLS. This has now been proven to be an underestimate of the true number of TLS. Thus, we propose a methodology for the automated identification and quantification of TLS, based on H&E slides. We subsequently determined the mathematical criteria defining a TLS. TLS regions were identified through a deep convolutional neural network and segmentation of lymphocytes was performed through an ellipsoidal model. This methodology had a 92.87% specificity at 95% sensitivity, 88.79% specificity at 98% sensitivity and 84.32% specificity at 99% sensitivity level based on 144 TLS annotated H&E slides implying that the automated approach was able to reproduce the histopathologists' assessment with great accuracy. We showed that the minimum number of lymphocytes within TLS is 45 and the minimum TLS area is 6,245μm2. Furthermore, we have shown that the density of the lymphocytes is more than 3 times those outside of the TLS. The mean density and standard deviation of lymphocytes within a TLS area are 0.0128/μm2 and 0.0026/μm2 respectively compared to 0.004/μm2 and 0.001/μm2 in non-TLS regions. The proposed methodology shows great potential for automated identification and quantification of the TLS density on digital H&E slides.
format	article
author	Panagiotis Barmpoutis Matthew Di Capite Hamzeh Kayhanian William Waddingham Daniel C Alexander Marnix Jansen Francois Ng Kee Kwong
author_facet	Panagiotis Barmpoutis Matthew Di Capite Hamzeh Kayhanian William Waddingham Daniel C Alexander Marnix Jansen Francois Ng Kee Kwong
author_sort	Panagiotis Barmpoutis
title	Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
title_short	Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
title_full	Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
title_fullStr	Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
title_full_unstemmed	Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.
title_sort	tertiary lymphoid structures (tls) identification and density assessment on h&e-stained digital slides of lung cancer.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/729f08bcca37483ba72053fba1452226
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Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer.

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