Cargando…

Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors

The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with...

Descripción completa

Detalles Bibliográficos
Autores principales: Palm, Christiane, Connolly, Catherine E., Masser, Regina, Padberg Sgier, Barbara, Karamitopoulou, Eva, Simon, Quentin, Bode, Beata, Tinguely, Marianne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818571/
https://www.ncbi.nlm.nih.gov/pubmed/36611460
http://dx.doi.org/10.3390/diagnostics13010168
_version_ 1784865018770096128
author Palm, Christiane
Connolly, Catherine E.
Masser, Regina
Padberg Sgier, Barbara
Karamitopoulou, Eva
Simon, Quentin
Bode, Beata
Tinguely, Marianne
author_facet Palm, Christiane
Connolly, Catherine E.
Masser, Regina
Padberg Sgier, Barbara
Karamitopoulou, Eva
Simon, Quentin
Bode, Beata
Tinguely, Marianne
author_sort Palm, Christiane
collection PubMed
description The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen’s κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists’ agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen’s κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations.
format Online
Article
Text
id pubmed-9818571
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-98185712023-01-07 Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors Palm, Christiane Connolly, Catherine E. Masser, Regina Padberg Sgier, Barbara Karamitopoulou, Eva Simon, Quentin Bode, Beata Tinguely, Marianne Diagnostics (Basel) Article The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen’s κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists’ agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen’s κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations. MDPI 2023-01-03 /pmc/articles/PMC9818571/ /pubmed/36611460 http://dx.doi.org/10.3390/diagnostics13010168 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Palm, Christiane
Connolly, Catherine E.
Masser, Regina
Padberg Sgier, Barbara
Karamitopoulou, Eva
Simon, Quentin
Bode, Beata
Tinguely, Marianne
Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title_full Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title_fullStr Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title_full_unstemmed Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title_short Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
title_sort determining her2 status by artificial intelligence: an investigation of primary, metastatic, and her2 low breast tumors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818571/
https://www.ncbi.nlm.nih.gov/pubmed/36611460
http://dx.doi.org/10.3390/diagnostics13010168
work_keys_str_mv AT palmchristiane determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT connollycatherinee determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT masserregina determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT padbergsgierbarbara determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT karamitopouloueva determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT simonquentin determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT bodebeata determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors
AT tinguelymarianne determiningher2statusbyartificialintelligenceaninvestigationofprimarymetastaticandher2lowbreasttumors