Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma

In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slides of diffuse large B-cell lymphoma. The H&E-st...

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Autores principales: Swiderska-Chadaj, Zaneta, Hebeda, Konnie M., van den Brand, Michiel, Litjens, Geert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Brief Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448690/
https://www.ncbi.nlm.nih.gov/pubmed/32979109
http://dx.doi.org/10.1007/s00428-020-02931-4
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author Swiderska-Chadaj, Zaneta
Hebeda, Konnie M.
van den Brand, Michiel
Litjens, Geert
author_facet Swiderska-Chadaj, Zaneta
Hebeda, Konnie M.
van den Brand, Michiel
Litjens, Geert
author_sort Swiderska-Chadaj, Zaneta
collection PubMed
description In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slides of diffuse large B-cell lymphoma. The H&E-stained slides of 287 cases from 11 hospitals were used for training and evaluation. The overall sensitivity to detect MYC rearrangement was 0.93 and the specificity 0.52, showing that prediction of MYC translocation based on morphology alone was possible in 93% of MYC-rearranged cases. This would allow a simple and fast prescreening, saving approximately 34% of genetic tests with the current algorithm. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00428-020-02931-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-84486902021-10-01 Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma Swiderska-Chadaj, Zaneta Hebeda, Konnie M. van den Brand, Michiel Litjens, Geert Virchows Arch Brief Report In patients with suspected lymphoma, the tissue biopsy provides lymphoma confirmation, classification, and prognostic factors, including genetic changes. We developed a deep learning algorithm to detect MYC rearrangement in scanned histological slides of diffuse large B-cell lymphoma. The H&E-stained slides of 287 cases from 11 hospitals were used for training and evaluation. The overall sensitivity to detect MYC rearrangement was 0.93 and the specificity 0.52, showing that prediction of MYC translocation based on morphology alone was possible in 93% of MYC-rearranged cases. This would allow a simple and fast prescreening, saving approximately 34% of genetic tests with the current algorithm. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00428-020-02931-4) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2020-09-26 2021 /pmc/articles/PMC8448690/ /pubmed/32979109 http://dx.doi.org/10.1007/s00428-020-02931-4 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Brief Report
Swiderska-Chadaj, Zaneta
Hebeda, Konnie M.
van den Brand, Michiel
Litjens, Geert
Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title_full Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title_fullStr Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title_full_unstemmed Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title_short Artificial intelligence to detect MYC translocation in slides of diffuse large B-cell lymphoma
title_sort artificial intelligence to detect myc translocation in slides of diffuse large b-cell lymphoma
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448690/
https://www.ncbi.nlm.nih.gov/pubmed/32979109
http://dx.doi.org/10.1007/s00428-020-02931-4
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