Integration of computer-aided automated analysis algorithms in the development and validation of immunohistochemistry biomarkers in ovarian cancer
© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ..
In an era when immunohistochemistry (IHC) is increasingly depended on for histological subtyping, and IHC-determined biomarker informing rapid treatment choices is on the horizon; reproducible, quantifiable techniques are required. This study aimed to compare automated IHC scoring to quantify 6 DNA damage response protein markers using a tissue microarray of 66 ovarian cancer samples. Accuracy of quantification was compared between manual H-score and computer-aided quantification using Aperio ImageScope with and without a tissue classification algorithm. High levels of interobserver variation was seen with manual scoring. With automated methods, inclusion of the tissue classifier mask resulted in greater accuracy within carcinomatous areas and an overall increase in H-score of a median of 11.5% (0%-18%). Without the classifier, the score was underestimated by a median of 10.5 (5.2-25.6). Automated methods are reliable and superior to manual scoring. Fixed algorithms offer the reproducibility needed for high-throughout clinical applications.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:74 |
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| Enthalten in: |
Journal of clinical pathology - 74(2021), 7 vom: 19. Juli, Seite 469-474 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Gentles, Lucy [VerfasserIn] |
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| Links: |
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| Themen: |
Antibodies |
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| Anmerkungen: |
Date Completed 24.06.2021 Date Revised 24.06.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1136/jclinpath-2020-207081 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM31781298X |
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| 100 | 1 | |a Gentles, Lucy |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Integration of computer-aided automated analysis algorithms in the development and validation of immunohistochemistry biomarkers in ovarian cancer |
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| 500 | |a Date Revised 24.06.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ. | ||
| 520 | |a In an era when immunohistochemistry (IHC) is increasingly depended on for histological subtyping, and IHC-determined biomarker informing rapid treatment choices is on the horizon; reproducible, quantifiable techniques are required. This study aimed to compare automated IHC scoring to quantify 6 DNA damage response protein markers using a tissue microarray of 66 ovarian cancer samples. Accuracy of quantification was compared between manual H-score and computer-aided quantification using Aperio ImageScope with and without a tissue classification algorithm. High levels of interobserver variation was seen with manual scoring. With automated methods, inclusion of the tissue classifier mask resulted in greater accuracy within carcinomatous areas and an overall increase in H-score of a median of 11.5% (0%-18%). Without the classifier, the score was underestimated by a median of 10.5 (5.2-25.6). Automated methods are reliable and superior to manual scoring. Fixed algorithms offer the reproducibility needed for high-throughout clinical applications | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Validation Study | |
| 650 | 4 | |a antibodies | |
| 650 | 4 | |a carcinoma | |
| 650 | 4 | |a cell biology | |
| 650 | 4 | |a immunohistochemistry | |
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| 700 | 1 | |a Howarth, Rachel |e verfasserin |4 aut | |
| 700 | 1 | |a Lee, Won Ji |e verfasserin |4 aut | |
| 700 | 1 | |a Sharma-Saha, Sweta |e verfasserin |4 aut | |
| 700 | 1 | |a Ralte, Angela |e verfasserin |4 aut | |
| 700 | 1 | |a Curtin, Nicola |e verfasserin |4 aut | |
| 700 | 1 | |a Drew, Yvette |e verfasserin |4 aut | |
| 700 | 1 | |a O'Donnell, Rachel Louise |e verfasserin |4 aut | |
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