Quantitative Imaging Analysis Fluorescence In Situ Hybridization Validation for Clinical HER2 Testing in Breast Cancer
Quantitative imaging is a promising tool that is gaining wide use across several areas of pathology. Although there has been increasing adoption of morphologic and immunohistochemical analysis, the adoption for evaluation of fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embed...
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creator | Wilcock, Diane M Moore, Kristina H Rowe, Leslie Mahlow, Jonathan Jedrzkiewicz, Jolanta Cleary, Allison S Lomo, Lesley Ruano, Ana L Gering, Maarika Bradshaw, Derek Maughan, Meghan Tran, Phuong Burlingame, Jesse Davis, Richard Affolter, Kajsa Albertson, Daniel J Adelhardt, Parisa Kim, Jong Take Coleman, Joshua F Deftereos, Georgios Gulbahce, Evin H Sirohi, Deepika |
description | Quantitative imaging is a promising tool that is gaining wide use across several areas of pathology. Although there has been increasing adoption of morphologic and immunohistochemical analysis, the adoption for evaluation of fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded tissue has been limited because of complexity and lack of practice guidelines.
To perform HER2 FISH validation in breast carcinoma in accordance with the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) 2018 guideline.
Clinical validation of HER2 FISH was performed using the US Food and Drug Administration-approved, dual-probe HER2 IQFISH (Dako, Carpinteria, California) with digital scanning performed on a PathFusion (Applied Spectral Imaging, Carlsbad, California) system. Validation parameters evaluated included: z-stacking, classifier, accuracy, precision, software, and hardware settings. Finally, we evaluated the performance of digital enumeration on clinical samples in a real-world setting.
The accuracy samples showed a final concordance of 95.3% to 100% across HER2 groups 1 to 5. During clinical implementation for HER2 groups 2, 3, and 4, we achieved a final concordance of 76% (95 of 125). Of these, only 8% (10 of 125) of the cases had discordances with clinical impact that can be identified algorithmically and triaged for manual review.
Digital FISH enumeration is a useful tool to improve the efficacy of HER2 FISH enumeration and capture genetic heterogeneity across HER2 signals. Excluding cases with high background or poor image quality and manual review for cases with ASCO/CAP group discordances can further improve the efficiency of digital HER2 FISH enumeration. |
doi_str_mv | 10.5858/arpa.2022-0372-OA |
format | Article |
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To perform HER2 FISH validation in breast carcinoma in accordance with the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) 2018 guideline.
Clinical validation of HER2 FISH was performed using the US Food and Drug Administration-approved, dual-probe HER2 IQFISH (Dako, Carpinteria, California) with digital scanning performed on a PathFusion (Applied Spectral Imaging, Carlsbad, California) system. Validation parameters evaluated included: z-stacking, classifier, accuracy, precision, software, and hardware settings. Finally, we evaluated the performance of digital enumeration on clinical samples in a real-world setting.
The accuracy samples showed a final concordance of 95.3% to 100% across HER2 groups 1 to 5. During clinical implementation for HER2 groups 2, 3, and 4, we achieved a final concordance of 76% (95 of 125). Of these, only 8% (10 of 125) of the cases had discordances with clinical impact that can be identified algorithmically and triaged for manual review.
Digital FISH enumeration is a useful tool to improve the efficacy of HER2 FISH enumeration and capture genetic heterogeneity across HER2 signals. Excluding cases with high background or poor image quality and manual review for cases with ASCO/CAP group discordances can further improve the efficiency of digital HER2 FISH enumeration.</description><identifier>ISSN: 0003-9985</identifier><identifier>ISSN: 1543-2165</identifier><identifier>EISSN: 1543-2165</identifier><identifier>DOI: 10.5858/arpa.2022-0372-OA</identifier><identifier>PMID: 36920020</identifier><language>eng</language><publisher>United States: College of American Pathologists</publisher><subject>Accuracy ; Automation ; Breast cancer ; Breast carcinoma ; Classification ; Diagnosis ; Diagnostic immunohistochemistry ; Enumeration ; Epidermal growth factor ; ErbB-2 protein ; FDA approval ; Fluorescence in situ hybridization ; Hybridization ; Image processing ; Immunohistochemistry ; Methods ; Oncology ; Pathology ; Stacking</subject><ispartof>Archives of pathology & laboratory medicine (1976), 2023-12, Vol.147 (12), p.1402-1412</ispartof><rights>2023 College of American Pathologists.</rights><rights>COPYRIGHT 2023 College of American Pathologists</rights><rights>Copyright College of American Pathologists Dec 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c460t-709a4ea047ab731b4385b86fcd6fcad2af377d5aa2b1af2981ec6434e92c76073</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36920020$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wilcock, Diane M</creatorcontrib><creatorcontrib>Moore, Kristina H</creatorcontrib><creatorcontrib>Rowe, Leslie</creatorcontrib><creatorcontrib>Mahlow, Jonathan</creatorcontrib><creatorcontrib>Jedrzkiewicz, Jolanta</creatorcontrib><creatorcontrib>Cleary, Allison S</creatorcontrib><creatorcontrib>Lomo, Lesley</creatorcontrib><creatorcontrib>Ruano, Ana L</creatorcontrib><creatorcontrib>Gering, Maarika</creatorcontrib><creatorcontrib>Bradshaw, Derek</creatorcontrib><creatorcontrib>Maughan, Meghan</creatorcontrib><creatorcontrib>Tran, Phuong</creatorcontrib><creatorcontrib>Burlingame, Jesse</creatorcontrib><creatorcontrib>Davis, Richard</creatorcontrib><creatorcontrib>Affolter, Kajsa</creatorcontrib><creatorcontrib>Albertson, Daniel J</creatorcontrib><creatorcontrib>Adelhardt, Parisa</creatorcontrib><creatorcontrib>Kim, Jong Take</creatorcontrib><creatorcontrib>Coleman, Joshua F</creatorcontrib><creatorcontrib>Deftereos, Georgios</creatorcontrib><creatorcontrib>Gulbahce, Evin H</creatorcontrib><creatorcontrib>Sirohi, Deepika</creatorcontrib><title>Quantitative Imaging Analysis Fluorescence In Situ Hybridization Validation for Clinical HER2 Testing in Breast Cancer</title><title>Archives of pathology & laboratory medicine (1976)</title><addtitle>Arch Pathol Lab Med</addtitle><description>Quantitative imaging is a promising tool that is gaining wide use across several areas of pathology. Although there has been increasing adoption of morphologic and immunohistochemical analysis, the adoption for evaluation of fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded tissue has been limited because of complexity and lack of practice guidelines.
To perform HER2 FISH validation in breast carcinoma in accordance with the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) 2018 guideline.
Clinical validation of HER2 FISH was performed using the US Food and Drug Administration-approved, dual-probe HER2 IQFISH (Dako, Carpinteria, California) with digital scanning performed on a PathFusion (Applied Spectral Imaging, Carlsbad, California) system. Validation parameters evaluated included: z-stacking, classifier, accuracy, precision, software, and hardware settings. Finally, we evaluated the performance of digital enumeration on clinical samples in a real-world setting.
The accuracy samples showed a final concordance of 95.3% to 100% across HER2 groups 1 to 5. During clinical implementation for HER2 groups 2, 3, and 4, we achieved a final concordance of 76% (95 of 125). Of these, only 8% (10 of 125) of the cases had discordances with clinical impact that can be identified algorithmically and triaged for manual review.
Digital FISH enumeration is a useful tool to improve the efficacy of HER2 FISH enumeration and capture genetic heterogeneity across HER2 signals. Excluding cases with high background or poor image quality and manual review for cases with ASCO/CAP group discordances can further improve the efficiency of digital HER2 FISH enumeration.</description><subject>Accuracy</subject><subject>Automation</subject><subject>Breast cancer</subject><subject>Breast carcinoma</subject><subject>Classification</subject><subject>Diagnosis</subject><subject>Diagnostic immunohistochemistry</subject><subject>Enumeration</subject><subject>Epidermal growth factor</subject><subject>ErbB-2 protein</subject><subject>FDA approval</subject><subject>Fluorescence in situ hybridization</subject><subject>Hybridization</subject><subject>Image processing</subject><subject>Immunohistochemistry</subject><subject>Methods</subject><subject>Oncology</subject><subject>Pathology</subject><subject>Stacking</subject><issn>0003-9985</issn><issn>1543-2165</issn><issn>1543-2165</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptkl1rFDEUhoModq3-AG8kIIg3s-ZjZjK5HJfWLRQWtXobzmQy25RssiYzhfXXm2HrR2UJIR_neQ8nJy9CrylZVk3VfIC4hyUjjBWEC1Zs2idoQauSF4zW1VO0IITwQsqmOkMvUrrLR8kYfY7OeC0ZIYws0P3nCfxoRxjtvcFXO9hav8WtB3dINuFLN4VokjZe56jHX-044fWhi7a3P7MmePwdnO2P2yFEvHLWWw0Ory--MHxj0jgntB5_jAbSiFeQU8WX6NkALplXD-s5-nZ5cbNaF9ebT1er9rrQZU3GQhAJpQFSCugEp13Jm6pr6kH3eULPYOBC9BUA6ygMTDbU6LrkpZFMi5oIfo7eH_PuY_gx5WLUzubXOAfehCkpJhrBKK9qltG3_6F3YYq5EZmSJFdSCSH-UltwRlk_hDGCnpOqNscrKUVJMlWcoLbGmwgueDPYfP2IX57g8-jNzuqTgnf_CG4NuPE2BTfN35Aeg_QI6hhSimZQ-2h3EA-KEjWbSM0mUrOJ1GwitWmz5s1DJ6ZuZ_o_it-u4b8AZcDA9g</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Wilcock, 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HER2 Testing in Breast Cancer</title><author>Wilcock, Diane M ; Moore, Kristina H ; Rowe, Leslie ; Mahlow, Jonathan ; Jedrzkiewicz, Jolanta ; Cleary, Allison S ; Lomo, Lesley ; Ruano, Ana L ; Gering, Maarika ; Bradshaw, Derek ; Maughan, Meghan ; Tran, Phuong ; Burlingame, Jesse ; Davis, Richard ; Affolter, Kajsa ; Albertson, Daniel J ; Adelhardt, Parisa ; Kim, Jong Take ; Coleman, Joshua F ; Deftereos, Georgios ; Gulbahce, Evin H ; Sirohi, Deepika</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c460t-709a4ea047ab731b4385b86fcd6fcad2af377d5aa2b1af2981ec6434e92c76073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accuracy</topic><topic>Automation</topic><topic>Breast cancer</topic><topic>Breast carcinoma</topic><topic>Classification</topic><topic>Diagnosis</topic><topic>Diagnostic immunohistochemistry</topic><topic>Enumeration</topic><topic>Epidermal growth factor</topic><topic>ErbB-2 protein</topic><topic>FDA approval</topic><topic>Fluorescence in situ hybridization</topic><topic>Hybridization</topic><topic>Image processing</topic><topic>Immunohistochemistry</topic><topic>Methods</topic><topic>Oncology</topic><topic>Pathology</topic><topic>Stacking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wilcock, Diane M</creatorcontrib><creatorcontrib>Moore, Kristina H</creatorcontrib><creatorcontrib>Rowe, Leslie</creatorcontrib><creatorcontrib>Mahlow, Jonathan</creatorcontrib><creatorcontrib>Jedrzkiewicz, Jolanta</creatorcontrib><creatorcontrib>Cleary, Allison S</creatorcontrib><creatorcontrib>Lomo, Lesley</creatorcontrib><creatorcontrib>Ruano, Ana L</creatorcontrib><creatorcontrib>Gering, Maarika</creatorcontrib><creatorcontrib>Bradshaw, Derek</creatorcontrib><creatorcontrib>Maughan, Meghan</creatorcontrib><creatorcontrib>Tran, Phuong</creatorcontrib><creatorcontrib>Burlingame, 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Diane M</au><au>Moore, Kristina H</au><au>Rowe, Leslie</au><au>Mahlow, Jonathan</au><au>Jedrzkiewicz, Jolanta</au><au>Cleary, Allison S</au><au>Lomo, Lesley</au><au>Ruano, Ana L</au><au>Gering, Maarika</au><au>Bradshaw, Derek</au><au>Maughan, Meghan</au><au>Tran, Phuong</au><au>Burlingame, Jesse</au><au>Davis, Richard</au><au>Affolter, Kajsa</au><au>Albertson, Daniel J</au><au>Adelhardt, Parisa</au><au>Kim, Jong Take</au><au>Coleman, Joshua F</au><au>Deftereos, Georgios</au><au>Gulbahce, Evin H</au><au>Sirohi, Deepika</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative Imaging Analysis Fluorescence In Situ Hybridization Validation for Clinical HER2 Testing in Breast Cancer</atitle><jtitle>Archives of pathology & laboratory medicine (1976)</jtitle><addtitle>Arch Pathol Lab Med</addtitle><date>2023-12-01</date><risdate>2023</risdate><volume>147</volume><issue>12</issue><spage>1402</spage><epage>1412</epage><pages>1402-1412</pages><issn>0003-9985</issn><issn>1543-2165</issn><eissn>1543-2165</eissn><abstract>Quantitative imaging is a promising tool that is gaining wide use across several areas of pathology. Although there has been increasing adoption of morphologic and immunohistochemical analysis, the adoption for evaluation of fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded tissue has been limited because of complexity and lack of practice guidelines.
To perform HER2 FISH validation in breast carcinoma in accordance with the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) 2018 guideline.
Clinical validation of HER2 FISH was performed using the US Food and Drug Administration-approved, dual-probe HER2 IQFISH (Dako, Carpinteria, California) with digital scanning performed on a PathFusion (Applied Spectral Imaging, Carlsbad, California) system. Validation parameters evaluated included: z-stacking, classifier, accuracy, precision, software, and hardware settings. Finally, we evaluated the performance of digital enumeration on clinical samples in a real-world setting.
The accuracy samples showed a final concordance of 95.3% to 100% across HER2 groups 1 to 5. During clinical implementation for HER2 groups 2, 3, and 4, we achieved a final concordance of 76% (95 of 125). Of these, only 8% (10 of 125) of the cases had discordances with clinical impact that can be identified algorithmically and triaged for manual review.
Digital FISH enumeration is a useful tool to improve the efficacy of HER2 FISH enumeration and capture genetic heterogeneity across HER2 signals. Excluding cases with high background or poor image quality and manual review for cases with ASCO/CAP group discordances can further improve the efficiency of digital HER2 FISH enumeration.</abstract><cop>United States</cop><pub>College of American Pathologists</pub><pmid>36920020</pmid><doi>10.5858/arpa.2022-0372-OA</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Automation Breast cancer Breast carcinoma Classification Diagnosis Diagnostic immunohistochemistry Enumeration Epidermal growth factor ErbB-2 protein FDA approval Fluorescence in situ hybridization Hybridization Image processing Immunohistochemistry Methods Oncology Pathology Stacking |
title | Quantitative Imaging Analysis Fluorescence In Situ Hybridization Validation for Clinical HER2 Testing in Breast Cancer |
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