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Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control
BACKGROUND: Digital image analysis (DIA) enables better reproducibility of immunohistochemistry (IHC) studies. Nevertheless, accuracy of the DIA methods needs to be ensured, demanding production of reference data sets. We have reported on methodology to calibrate DIA for Ki67 IHC in breast cancer ti...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4305978/ https://www.ncbi.nlm.nih.gov/pubmed/25565221 http://dx.doi.org/10.1186/1746-1596-9-S1-S8 |
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author | Plancoulaine, Benoît Laurinaviciene, Aida Meskauskas, Raimundas Baltrusaityte, Indra Besusparis, Justinas Herlin, Paulette Laurinavicius, Arvydas |
author_facet | Plancoulaine, Benoît Laurinaviciene, Aida Meskauskas, Raimundas Baltrusaityte, Indra Besusparis, Justinas Herlin, Paulette Laurinavicius, Arvydas |
author_sort | Plancoulaine, Benoît |
collection | PubMed |
description | BACKGROUND: Digital image analysis (DIA) enables better reproducibility of immunohistochemistry (IHC) studies. Nevertheless, accuracy of the DIA methods needs to be ensured, demanding production of reference data sets. We have reported on methodology to calibrate DIA for Ki67 IHC in breast cancer tissue based on reference data obtained by stereology grid count. To produce the reference data more efficiently, we propose digital IHC wizard generating initial cell marks to be verified by experts. METHODS: Digital images of proliferation marker Ki67 IHC from 158 patients (one tissue microarray spot per patient) with an invasive ductal carcinoma of the breast were used. Manual data (mD) were obtained by marking Ki67-positive and negative tumour cells, using a stereological method for 2D object enumeration. DIA was used as an initial step in stereology grid count to generate the digital data (dD) marks by Aperio Genie and Nuclear algorithms. The dD were collected into XML files from the DIA markup images and overlaid on the original spots along with the stereology grid. The expert correction of the dD marks resulted in corrected data (cD). The percentages of Ki67 positive tumour cells per spot in the mD, dD, and cD sets were compared by single linear regression analysis. Efficiency of cD production was estimated based on manual editing effort. RESULTS: The percentage of Ki67-positive tumor cells was in very good agreement in the mD, dD, and cD sets: regression of cD from dD (R(2)=0.92) reflects the impact of the expert editing the dD as well as accuracy of the DIA used; regression of the cD from the mD (R(2)=0.94) represents the consistency of the DIA-assisted ground truth (cD) with the manual procedure. Nevertheless, the accuracy of detection of individual tumour cells was much lower: in average, 18 and 219 marks per spot were edited due to the Genie and Nuclear algorithm errors, respectively. The DIA-assisted cD production in our experiment saved approximately 2/3 of manual marking. CONCLUSIONS: Digital IHC wizard enabled DIA-assisted stereology to produce reference data in a consistent and efficient way. It can provide quality control measure for appraising accuracy of the DIA steps. |
format | Online Article Text |
id | pubmed-4305978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43059782015-02-12 Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control Plancoulaine, Benoît Laurinaviciene, Aida Meskauskas, Raimundas Baltrusaityte, Indra Besusparis, Justinas Herlin, Paulette Laurinavicius, Arvydas Diagn Pathol Proceedings BACKGROUND: Digital image analysis (DIA) enables better reproducibility of immunohistochemistry (IHC) studies. Nevertheless, accuracy of the DIA methods needs to be ensured, demanding production of reference data sets. We have reported on methodology to calibrate DIA for Ki67 IHC in breast cancer tissue based on reference data obtained by stereology grid count. To produce the reference data more efficiently, we propose digital IHC wizard generating initial cell marks to be verified by experts. METHODS: Digital images of proliferation marker Ki67 IHC from 158 patients (one tissue microarray spot per patient) with an invasive ductal carcinoma of the breast were used. Manual data (mD) were obtained by marking Ki67-positive and negative tumour cells, using a stereological method for 2D object enumeration. DIA was used as an initial step in stereology grid count to generate the digital data (dD) marks by Aperio Genie and Nuclear algorithms. The dD were collected into XML files from the DIA markup images and overlaid on the original spots along with the stereology grid. The expert correction of the dD marks resulted in corrected data (cD). The percentages of Ki67 positive tumour cells per spot in the mD, dD, and cD sets were compared by single linear regression analysis. Efficiency of cD production was estimated based on manual editing effort. RESULTS: The percentage of Ki67-positive tumor cells was in very good agreement in the mD, dD, and cD sets: regression of cD from dD (R(2)=0.92) reflects the impact of the expert editing the dD as well as accuracy of the DIA used; regression of the cD from the mD (R(2)=0.94) represents the consistency of the DIA-assisted ground truth (cD) with the manual procedure. Nevertheless, the accuracy of detection of individual tumour cells was much lower: in average, 18 and 219 marks per spot were edited due to the Genie and Nuclear algorithm errors, respectively. The DIA-assisted cD production in our experiment saved approximately 2/3 of manual marking. CONCLUSIONS: Digital IHC wizard enabled DIA-assisted stereology to produce reference data in a consistent and efficient way. It can provide quality control measure for appraising accuracy of the DIA steps. BioMed Central 2014-12-19 /pmc/articles/PMC4305978/ /pubmed/25565221 http://dx.doi.org/10.1186/1746-1596-9-S1-S8 Text en Copyright © 2014 Plancoulaine et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Proceedings Plancoulaine, Benoît Laurinaviciene, Aida Meskauskas, Raimundas Baltrusaityte, Indra Besusparis, Justinas Herlin, Paulette Laurinavicius, Arvydas Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title | Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title_full | Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title_fullStr | Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title_full_unstemmed | Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title_short | Digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
title_sort | digital immunohistochemistry wizard: image analysis-assisted stereology tool to produce reference data set for calibration and quality control |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4305978/ https://www.ncbi.nlm.nih.gov/pubmed/25565221 http://dx.doi.org/10.1186/1746-1596-9-S1-S8 |
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