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Ki67 Quantitative Interpretation: Insights using Image Analysis
BACKGROUND: Proliferation markers, especially Ki67, are increasingly important in diagnosis and prognosis. The best method for calculating Ki67 is still the subject of debate. MATERIALS AND METHODS: We evaluated an image analysis tool for quantitative interpretation of Ki67 in neuroendocrine tumors...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437785/ https://www.ncbi.nlm.nih.gov/pubmed/30984468 http://dx.doi.org/10.4103/jpi.jpi_76_18 |
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author | Volynskaya, Zoya Mete, Ozgur Pakbaz, Sara Al-Ghamdi, Doaa Asa, Sylvia L. |
author_facet | Volynskaya, Zoya Mete, Ozgur Pakbaz, Sara Al-Ghamdi, Doaa Asa, Sylvia L. |
author_sort | Volynskaya, Zoya |
collection | PubMed |
description | BACKGROUND: Proliferation markers, especially Ki67, are increasingly important in diagnosis and prognosis. The best method for calculating Ki67 is still the subject of debate. MATERIALS AND METHODS: We evaluated an image analysis tool for quantitative interpretation of Ki67 in neuroendocrine tumors and compared it to manual counts. We expanded a primary digital pathology platform to include the Leica Biosystems image analysis nuclear algorithm. Slides were digitized using a Leica Aperio AT2 Scanner and accessed through the Cerner CoPath LIS interfaced with Aperio eSlideManager through Aperio ImageScope. Selected regions of interest (ROIs) were manually defined and annotated to include tumor cells only; they were then analyzed with the algorithm and by four pathologists counting on printed images. After validation, the algorithm was used to examine the impact of the size and number of areas selected as ROIs. RESULTS: The algorithm provided reproducible results that were obtained within seconds, compared to up to 55 min of manual counting that varied between users. Benefits of image analysis identified by users included accuracy, time savings, and ease of viewing. Access to the algorithm allowed rapid comparisons of Ki67 counts in ROIs that varied in numbers of cells and selection of fields, the outputs demonstrated that the results vary around defined cutoffs that provide tumor grade depending on the number of cells and ROIs counted. CONCLUSIONS: Digital image analysis provides accurate and reproducible quantitative data faster than manual counts. However, access to this tool allows multiple analyses of a single sample to use variable numbers of cells and selection of variable ROIs that can alter the result in clinically significant ways. This study highlights the potential risk of hard cutoffs of continuous variables and indicates that standardization of number of cells and number of regions selected for analysis should be incorporated into guidelines for Ki67 calculations. |
format | Online Article Text |
id | pubmed-6437785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-64377852019-04-12 Ki67 Quantitative Interpretation: Insights using Image Analysis Volynskaya, Zoya Mete, Ozgur Pakbaz, Sara Al-Ghamdi, Doaa Asa, Sylvia L. J Pathol Inform Research Article BACKGROUND: Proliferation markers, especially Ki67, are increasingly important in diagnosis and prognosis. The best method for calculating Ki67 is still the subject of debate. MATERIALS AND METHODS: We evaluated an image analysis tool for quantitative interpretation of Ki67 in neuroendocrine tumors and compared it to manual counts. We expanded a primary digital pathology platform to include the Leica Biosystems image analysis nuclear algorithm. Slides were digitized using a Leica Aperio AT2 Scanner and accessed through the Cerner CoPath LIS interfaced with Aperio eSlideManager through Aperio ImageScope. Selected regions of interest (ROIs) were manually defined and annotated to include tumor cells only; they were then analyzed with the algorithm and by four pathologists counting on printed images. After validation, the algorithm was used to examine the impact of the size and number of areas selected as ROIs. RESULTS: The algorithm provided reproducible results that were obtained within seconds, compared to up to 55 min of manual counting that varied between users. Benefits of image analysis identified by users included accuracy, time savings, and ease of viewing. Access to the algorithm allowed rapid comparisons of Ki67 counts in ROIs that varied in numbers of cells and selection of fields, the outputs demonstrated that the results vary around defined cutoffs that provide tumor grade depending on the number of cells and ROIs counted. CONCLUSIONS: Digital image analysis provides accurate and reproducible quantitative data faster than manual counts. However, access to this tool allows multiple analyses of a single sample to use variable numbers of cells and selection of variable ROIs that can alter the result in clinically significant ways. This study highlights the potential risk of hard cutoffs of continuous variables and indicates that standardization of number of cells and number of regions selected for analysis should be incorporated into guidelines for Ki67 calculations. Wolters Kluwer - Medknow 2019-03-08 /pmc/articles/PMC6437785/ /pubmed/30984468 http://dx.doi.org/10.4103/jpi.jpi_76_18 Text en Copyright: © 2019 Journal of Pathology Informatics http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Research Article Volynskaya, Zoya Mete, Ozgur Pakbaz, Sara Al-Ghamdi, Doaa Asa, Sylvia L. Ki67 Quantitative Interpretation: Insights using Image Analysis |
title | Ki67 Quantitative Interpretation: Insights using Image Analysis |
title_full | Ki67 Quantitative Interpretation: Insights using Image Analysis |
title_fullStr | Ki67 Quantitative Interpretation: Insights using Image Analysis |
title_full_unstemmed | Ki67 Quantitative Interpretation: Insights using Image Analysis |
title_short | Ki67 Quantitative Interpretation: Insights using Image Analysis |
title_sort | ki67 quantitative interpretation: insights using image analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437785/ https://www.ncbi.nlm.nih.gov/pubmed/30984468 http://dx.doi.org/10.4103/jpi.jpi_76_18 |
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