Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues
Aims Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to its recognised importance as a predictive and prognostic marker in clinica...
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| Format: | Article |
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Wiley
2018
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| Online Access: | https://eprints.nottingham.ac.uk/46432/ |
| _version_ | 1848797325751746560 |
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| author | Qaiser, Talha Mukherjee, Abhik Reddy Pb, Chaitanya Munugoti, Sai Dileep Tallam, Vamsi Pitkäaho, Tomi Lehtimäki, Taina Naughton, Thomas Berseth, Matt Pedraza, Aníbal Mukundan, Ramakrishnan Smith, Matthew Bhalerao, Abhir Rodner, Erik Simon, Marcel Denzler, Joachim Huang, Chao-Hui Bueno, Gloria Snead, David Ellis, Ian O Ilyas, Mohammad Rajpoot, Nasir |
| author_facet | Qaiser, Talha Mukherjee, Abhik Reddy Pb, Chaitanya Munugoti, Sai Dileep Tallam, Vamsi Pitkäaho, Tomi Lehtimäki, Taina Naughton, Thomas Berseth, Matt Pedraza, Aníbal Mukundan, Ramakrishnan Smith, Matthew Bhalerao, Abhir Rodner, Erik Simon, Marcel Denzler, Joachim Huang, Chao-Hui Bueno, Gloria Snead, David Ellis, Ian O Ilyas, Mohammad Rajpoot, Nasir |
| author_sort | Qaiser, Talha |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Aims
Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to its recognised importance as a predictive and prognostic marker in clinical practice. However, visual scoring of Her2 is subjective and consequently prone to inter-observer variability. Given the prognostic and therapeutic implications of Her2 scoring, a more objective method is required. In this paper, we report on a recent automated Her2 scoring contest, held in conjunction with the annual PathSoc meeting held in Nottingham in June 2016, aimed at systematically comparing and advancing the state-of-the-art Artificial Intelligence (AI) based automated methods for Her2 scoring.
Methods and Results
The contest dataset comprised of digitised whole slide images (WSI) of sections from 86 cases of invasive breast carcinoma stained with both Haematoxylin & Eosin (H&E) and IHC for Her2. The contesting algorithms automatically predicted scores of the IHC slides for an unseen subset of the dataset and the predicted scores were compared with the “ground truth” (a consensus score from at least two experts). We also report on a simple Man vs Machine contest for the scoring of Her2 and show that the automated methods could beat the pathology experts on this contest dataset.
Conclusions
This paper presents a benchmark for comparing the performance of automated algorithms for scoring of Her2. It also demonstrates the enormous potential of automated algorithms in assisting the pathologist with objective IHC scoring. |
| first_indexed | 2025-11-14T20:02:05Z |
| format | Article |
| id | nottingham-46432 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:02:05Z |
| publishDate | 2018 |
| publisher | Wiley |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-464322020-05-04T19:53:15Z https://eprints.nottingham.ac.uk/46432/ Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues Qaiser, Talha Mukherjee, Abhik Reddy Pb, Chaitanya Munugoti, Sai Dileep Tallam, Vamsi Pitkäaho, Tomi Lehtimäki, Taina Naughton, Thomas Berseth, Matt Pedraza, Aníbal Mukundan, Ramakrishnan Smith, Matthew Bhalerao, Abhir Rodner, Erik Simon, Marcel Denzler, Joachim Huang, Chao-Hui Bueno, Gloria Snead, David Ellis, Ian O Ilyas, Mohammad Rajpoot, Nasir Aims Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to its recognised importance as a predictive and prognostic marker in clinical practice. However, visual scoring of Her2 is subjective and consequently prone to inter-observer variability. Given the prognostic and therapeutic implications of Her2 scoring, a more objective method is required. In this paper, we report on a recent automated Her2 scoring contest, held in conjunction with the annual PathSoc meeting held in Nottingham in June 2016, aimed at systematically comparing and advancing the state-of-the-art Artificial Intelligence (AI) based automated methods for Her2 scoring. Methods and Results The contest dataset comprised of digitised whole slide images (WSI) of sections from 86 cases of invasive breast carcinoma stained with both Haematoxylin & Eosin (H&E) and IHC for Her2. The contesting algorithms automatically predicted scores of the IHC slides for an unseen subset of the dataset and the predicted scores were compared with the “ground truth” (a consensus score from at least two experts). We also report on a simple Man vs Machine contest for the scoring of Her2 and show that the automated methods could beat the pathology experts on this contest dataset. Conclusions This paper presents a benchmark for comparing the performance of automated algorithms for scoring of Her2. It also demonstrates the enormous potential of automated algorithms in assisting the pathologist with objective IHC scoring. Wiley 2018-01 Article PeerReviewed Qaiser, Talha, Mukherjee, Abhik, Reddy Pb, Chaitanya, Munugoti, Sai Dileep, Tallam, Vamsi, Pitkäaho, Tomi, Lehtimäki, Taina, Naughton, Thomas, Berseth, Matt, Pedraza, Aníbal, Mukundan, Ramakrishnan, Smith, Matthew, Bhalerao, Abhir, Rodner, Erik, Simon, Marcel, Denzler, Joachim, Huang, Chao-Hui, Bueno, Gloria, Snead, David, Ellis, Ian O, Ilyas, Mohammad and Rajpoot, Nasir (2018) Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues. Histopathology, 72 (2). pp. 227-238. ISSN 1365-2559 Digital Pathology; Automated Her2 Scoring; Biomarker Quantification; Quantitative Immunohistochemistry; Breast Cancer http://onlinelibrary.wiley.com/doi/10.1111/his.13333/abstract doi:10.1111/his.13333 doi:10.1111/his.13333 |
| spellingShingle | Digital Pathology; Automated Her2 Scoring; Biomarker Quantification; Quantitative Immunohistochemistry; Breast Cancer Qaiser, Talha Mukherjee, Abhik Reddy Pb, Chaitanya Munugoti, Sai Dileep Tallam, Vamsi Pitkäaho, Tomi Lehtimäki, Taina Naughton, Thomas Berseth, Matt Pedraza, Aníbal Mukundan, Ramakrishnan Smith, Matthew Bhalerao, Abhir Rodner, Erik Simon, Marcel Denzler, Joachim Huang, Chao-Hui Bueno, Gloria Snead, David Ellis, Ian O Ilyas, Mohammad Rajpoot, Nasir Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title | Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title_full | Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title_fullStr | Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title_full_unstemmed | Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title_short | Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| title_sort | her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues |
| topic | Digital Pathology; Automated Her2 Scoring; Biomarker Quantification; Quantitative Immunohistochemistry; Breast Cancer |
| url | https://eprints.nottingham.ac.uk/46432/ https://eprints.nottingham.ac.uk/46432/ https://eprints.nottingham.ac.uk/46432/ |