1
|
Hanna MG, Brogi E. Future Practices of Breast Pathology Using Digital and Computational Pathology. Adv Anat Pathol 2023; 30:421-433. [PMID: 37737690 DOI: 10.1097/pap.0000000000000414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
Pathology clinical practice has evolved by adopting technological advancements initially regarded as potentially disruptive, such as electron microscopy, immunohistochemistry, and genomic sequencing. Breast pathology has a critical role as a medical domain, where the patient's pathology diagnosis has significant implications for prognostication and treatment of diseases. The advent of digital and computational pathology has brought about significant advancements in the field, offering new possibilities for enhancing diagnostic accuracy and improving patient care. Digital slide scanning enables to conversion of glass slides into high-fidelity digital images, supporting the review of cases in a digital workflow. Digitization offers the capability to render specimen diagnoses, digital archival of patient specimens, collaboration, and telepathology. Integration of image analysis and machine learning-based systems layered atop the high-resolution digital images offers novel workflows to assist breast pathologists in their clinical, educational, and research endeavors. Decision support tools may improve the detection and classification of breast lesions and the quantification of immunohistochemical studies. Computational biomarkers may help to contribute to patient management or outcomes. Furthermore, using digital and computational pathology may increase standardization and quality assurance, especially in areas with high interobserver variability. This review explores the current landscape and possible future applications of digital and computational techniques in the field of breast pathology.
Collapse
Affiliation(s)
- Matthew G Hanna
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | | |
Collapse
|
2
|
Sode M, Thagaard J, Eriksen JO, Laenkholm AV. Digital image analysis and assisted reading of the HER2 score display reduced concordance: pitfalls in the categorisation of HER2-low breast cancer. Histopathology 2023; 82:912-924. [PMID: 36737248 DOI: 10.1111/his.14877] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 01/11/2023] [Accepted: 02/01/2023] [Indexed: 02/05/2023]
Abstract
AIMS Digital image analysis (DIA) is used increasingly as an assisting tool to evaluate biomarkers, including human epidermal growth factor receptor 2 (HER2) in invasive breast cancer (BC). DIA can assist pathologists in HER2 evaluation by presenting quantitative information about the HER2 staining in APP assisted reading (AR). Concurrently, the HER2-low category (HER2-1+/2+ without HER2 gene amplification) has gained prominence due to newly developed antibody-drug conjugates. However, major inter- and intraobserver variability have been observed for the entity. The present quality assurance study investigated the concordance between DIA and AR in clinical use, especially concerning the HER2-low category. METHODS AND RESULTS HER2 immunohistochemistry (IHC) in 761 tumours from 727 patients was evaluated in tissue microarray (TMA) cores by DIA (Visiopharm HER2-CONNECT) and AR. Overall concordance between HER2-scores were 73% (n = 552, weighted-κ: 0.66), and 88% (n = 669, weighted-κ: 0.70), when combining HER2-0/1+. A total of 205 scores were discordant by one category, while four were discordant by two categories. A heterogeneous HER2 pattern was relatively common in the discordant cases and a pitfall in the categorisation of HER2-low BC. AR more commonly reassigned a lower HER2 score (from HER2-1+ to HER2-0) within the HER2-low subgroup (n = 624) compared with DIA. CONCLUSION DIA and AR display moderate agreement with heterogeneous and aberrant staining, representing a source of discordance and a pitfall in the evaluation of HER2.
Collapse
Affiliation(s)
- Michael Sode
- Department of Pathology, Zealand University Hospital, Roskilde, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Jens Ole Eriksen
- Department of Pathology, Zealand University Hospital, Roskilde, Denmark
| | - Anne-Vibeke Laenkholm
- Department of Pathology, Zealand University Hospital, Roskilde, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
3
|
Yousif M, Huang Y, Sciallis A, Kleer CG, Pang J, Smola B, Naik K, McClintock DS, Zhao L, Kunju LP, Balis UGJ, Pantanowitz L. Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma. Am J Clin Pathol 2022; 157:899-907. [PMID: 34875014 DOI: 10.1093/ajcp/aqab206] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/08/2021] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES Biomarker expression evaluation for estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) is an essential prognostic and predictive parameter for breast cancer and critical for guiding hormonal and neoadjuvant therapy. This study compared quantitative image analysis (QIA) with pathologists' scoring for ER, PgR, and HER2. METHODS A retrospective analysis was undertaken of 1,367 invasive breast carcinomas, including all histopathology subtypes, for which ER, PgR, and HER2 were analyzed by manual scoring and QIA. The resulting scores were compared, and in a subset of HER2 cases (n = 373, 26%), scores were correlated with available fluorescence in situ hybridization (FISH) results. RESULTS Concordance between QIA and manual scores for ER, PgR, and HER2 was 93%, 96%, and 90%, respectively. Discordant cases had low positive scores (1%-10%) for ER (n = 33), were due to nonrepresentative region selection (eg, ductal carcinoma in situ) or tumor heterogeneity for PgR (n = 43), and were of one-step difference (negative to equivocal, equivocal to positive, or vice versa) for HER2 (n = 90). Among HER2 cases where FISH results were available, only four (1.0%) showed discordant QIA and FISH results. CONCLUSIONS QIA is a computer-aided diagnostic support tool for pathologists. It significantly improves ER, PgR, and HER2 scoring standardization. QIA demonstrated excellent concordance with pathologists' scores. To avoid pitfalls, pathologist oversight of representative region selection is recommended.
Collapse
Affiliation(s)
- Mustafa Yousif
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
- Department of Pathology, Vanderbilt University Medical Center , Nashville, TN ¸ USA
| | - Yiyuan Huang
- Department of Biostatistics, University of Michigan , Ann Arbor, MI ¸ USA
| | - Andrew Sciallis
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Celina G Kleer
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Judy Pang
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Brian Smola
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Kalyani Naik
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - David S McClintock
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Lili Zhao
- Department of Biostatistics, University of Michigan , Ann Arbor, MI ¸ USA
| | - Lakshmi P Kunju
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Ulysses G J Balis
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| | - Liron Pantanowitz
- Department of Pathology, University of Michigan Medical School , Ann Arbor, MI ¸ USA
| |
Collapse
|
4
|
Yousif M, van Diest PJ, Laurinavicius A, Rimm D, van der Laak J, Madabhushi A, Schnitt S, Pantanowitz L. Artificial intelligence applied to breast pathology. Virchows Arch 2021; 480:191-209. [PMID: 34791536 DOI: 10.1007/s00428-021-03213-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/12/2021] [Accepted: 09/27/2021] [Indexed: 12/12/2022]
Abstract
The convergence of digital pathology and computer vision is increasingly enabling computers to perform tasks performed by humans. As a result, artificial intelligence (AI) is having an astoundingly positive effect on the field of pathology, including breast pathology. Research using machine learning and the development of algorithms that learn patterns from labeled digital data based on "deep learning" neural networks and feature-engineered approaches to analyze histology images have recently provided promising results. Thus far, image analysis and more complex AI-based tools have demonstrated excellent success performing tasks such as the quantification of breast biomarkers and Ki67, mitosis detection, lymph node metastasis recognition, tissue segmentation for diagnosing breast carcinoma, prognostication, computational assessment of tumor-infiltrating lymphocytes, and prediction of molecular expression as well as treatment response and benefit of therapy from routine H&E images. This review critically examines the literature regarding these applications of AI in the area of breast pathology.
Collapse
Affiliation(s)
- Mustafa Yousif
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Paul J van Diest
- Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Arvydas Laurinavicius
- Department of Pathology, Pharmacology and Forensic Medicine, Faculty of Medicine, Vilnius University, and National Center of Pathology, Affiliate of Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania
| | - David Rimm
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Jeroen van der Laak
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anant Madabhushi
- Department of Biomedical Engineering, Case Western Reserve University, and Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA
- Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, USA
| | - Stuart Schnitt
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Breast Oncology Program, Dana-Farber/Brigham and Women's Cancer Center, Boston, MA, USA
| | | |
Collapse
|
5
|
El Khoury K, Fockedey M, Brion E, Macq B. Improved 3D U-Net robustness against JPEG 2000 compression for male pelvic organ segmentation in radiotherapy. J Med Imaging (Bellingham) 2021; 8:041207. [PMID: 33842669 PMCID: PMC8020060 DOI: 10.1117/1.jmi.8.4.041207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/12/2021] [Indexed: 11/15/2022] Open
Abstract
Purpose: Automation of organ segmentation, via convolutional neural networks (CNNs), is key to facilitate the work of medical practitioners by ensuring that the adequate radiation dose is delivered to the target area while avoiding harmful exposure of healthy organs. The issue with CNNs is that they require large amounts of data transfer and storage which makes the use of image compression a necessity. Compression will affect image quality which in turn affects the segmentation process. We address the dilemma involved with handling large amounts of data while preserving segmentation accuracy. Approach: We analyze and improve 2D and 3D U-Net robustness against JPEG 2000 compression for male pelvic organ segmentation. We conduct three experiments on 56 cone beam computed tomography (CT) and 74 CT scans targeting bladder and rectum segmentation. The two objectives of the experiments are to compare the compression robustness of 2D versus 3D U-Net and to improve the 3D U-Net compression tolerance via fine-tuning. Results: We show that a 3D U-Net is 50% more robust to compression than a 2D U-Net. Moreover, by fine-tuning the 3D U-Net, we can double its compression tolerance compared to a 2D U-Net. Furthermore, we determine that fine-tuning the network to a compression ratio of 64:1 will ensure its flexibility to be used at compression ratios equal or lower. Conclusions: We reduce the potential risk involved with using image compression on automated organ segmentation. We demonstrate that a 3D U-Net can be fine-tuned to handle high compression ratios while preserving segmentation accuracy.
Collapse
Affiliation(s)
- Karim El Khoury
- Université Catholique de Louvain, Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Louvain-La-Neuve, Belgium
| | - Martin Fockedey
- Université Catholique de Louvain, Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Louvain-La-Neuve, Belgium
| | - Eliott Brion
- Université Catholique de Louvain, Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Louvain-La-Neuve, Belgium
| | - Benoît Macq
- Université Catholique de Louvain, Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Louvain-La-Neuve, Belgium
| |
Collapse
|
6
|
Amgad M, Stovgaard ES, Balslev E, Thagaard J, Chen W, Dudgeon S, Sharma A, Kerner JK, Denkert C, Yuan Y, AbdulJabbar K, Wienert S, Savas P, Voorwerk L, Beck AH, Madabhushi A, Hartman J, Sebastian MM, Horlings HM, Hudeček J, Ciompi F, Moore DA, Singh R, Roblin E, Balancin ML, Mathieu MC, Lennerz JK, Kirtani P, Chen IC, Braybrooke JP, Pruneri G, Demaria S, Adams S, Schnitt SJ, Lakhani SR, Rojo F, Comerma L, Badve SS, Khojasteh M, Symmans WF, Sotiriou C, Gonzalez-Ericsson P, Pogue-Geile KL, Kim RS, Rimm DL, Viale G, Hewitt SM, Bartlett JMS, Penault-Llorca F, Goel S, Lien HC, Loibl S, Kos Z, Loi S, Hanna MG, Michiels S, Kok M, Nielsen TO, Lazar AJ, Bago-Horvath Z, Kooreman LFS, van der Laak JAWM, Saltz J, Gallas BD, Kurkure U, Barnes M, Salgado R, Cooper LAD. Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group. NPJ Breast Cancer 2020; 6:16. [PMID: 32411818 PMCID: PMC7217824 DOI: 10.1038/s41523-020-0154-2] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 02/18/2020] [Indexed: 02/07/2023] Open
Abstract
Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.
Collapse
Affiliation(s)
- Mohamed Amgad
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA USA
| | | | - Eva Balslev
- Department of Pathology, Herlev and Gentofte Hospital, University of Copenhagen, Herlev, Denmark
| | - Jeppe Thagaard
- DTU Compute, Department of Applied Mathematics, Technical University of Denmark, Lyngby, Denmark
- Visiopharm A/S, Hørsholm, Denmark
| | - Weijie Chen
- FDA/CDRH/OSEL/Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD USA
| | - Sarah Dudgeon
- FDA/CDRH/OSEL/Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD USA
| | - Ashish Sharma
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA USA
| | | | - Carsten Denkert
- Institut für Pathologie, Universitätsklinikum Gießen und Marburg GmbH, Standort Marburg, Philipps-Universität Marburg, Marburg, Germany
- Institute of Pathology, Philipps-University Marburg, Marburg, Germany
- German Cancer Consortium (DKTK), Partner Site Charité, Berlin, Germany
| | - Yinyin Yuan
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Khalid AbdulJabbar
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Stephan Wienert
- Institut für Pathologie, Universitätsklinikum Gießen und Marburg GmbH, Standort Marburg, Philipps-Universität Marburg, Marburg, Germany
| | - Peter Savas
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
| | - Leonie Voorwerk
- Department of Tumor Biology & Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Anant Madabhushi
- Case Western Reserve University, Department of Biomedical Engineering, Cleveland, OH USA
- Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH USA
| | - Johan Hartman
- Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Solna, Sweden
| | - Manu M. Sebastian
- Departments of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Hugo M. Horlings
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jan Hudeček
- Department of Research IT, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Francesco Ciompi
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - David A. Moore
- Department of Pathology, UCL Cancer Institute, London, UK
| | - Rajendra Singh
- Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Elvire Roblin
- Université Paris-Saclay, Univ. Paris-Sud, Villejuif, France
| | - Marcelo Luiz Balancin
- Department of Pathology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Marie-Christine Mathieu
- Department of Medical Biology and Pathology, Gustave Roussy Cancer Campus, Villejuif, France
| | - Jochen K. Lennerz
- Department of Pathology, Massachusetts General Hospital, Boston, MA USA
| | - Pawan Kirtani
- Department of Histopathology, Manipal Hospitals Dwarka, New Delhi, India
| | - I-Chun Chen
- Department of Oncology, National Taiwan University Cancer Center, Taipei, Taiwan
| | - Jeremy P. Braybrooke
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Medical Oncology, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Giancarlo Pruneri
- Pathology Department, Fondazione IRCCS Istituto Nazionale Tumori and University of Milan, School of Medicine, Milan, Italy
| | | | - Sylvia Adams
- Laura and Isaac Perlmutter Cancer Center, NYU Langone Medical Center, New York, NY USA
| | - Stuart J. Schnitt
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA USA
| | - Sunil R. Lakhani
- The University of Queensland Centre for Clinical Research and Pathology Queensland, Brisbane, Australia
| | - Federico Rojo
- Pathology Department, CIBERONC-Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- GEICAM-Spanish Breast Cancer Research Group, Madrid, Spain
| | - Laura Comerma
- Pathology Department, CIBERONC-Instituto de Investigación Sanitaria Fundación Jiménez Díaz (IIS-FJD), Madrid, Spain
- GEICAM-Spanish Breast Cancer Research Group, Madrid, Spain
| | - Sunil S. Badve
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN USA
| | | | - W. Fraser Symmans
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | - Christos Sotiriou
- Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Brussels, Belgium
- ULB-Cancer Research Center (U-CRC) Université Libre de Bruxelles, Brussels, Belgium
| | - Paula Gonzalez-Ericsson
- Breast Cancer Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN USA
| | | | | | - David L. Rimm
- Department of Pathology, Yale University School of Medicine, New Haven, CT USA
| | - Giuseppe Viale
- Department of Pathology, IEO, European Institute of Oncology IRCCS & State University of Milan, Milan, Italy
| | - Stephen M. Hewitt
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - John M. S. Bartlett
- Ontario Institute for Cancer Research, Toronto, ON Canada
- Edinburgh Cancer Research Centre, Western General Hospital, Edinburgh, UK
| | - Frédérique Penault-Llorca
- Department of Pathology and Molecular Pathology, Centre Jean Perrin, Clermont-Ferrand, France
- UMR INSERM 1240, Universite Clermont Auvergne, Clermont-Ferrand, France
| | - Shom Goel
- Victorian Comprehensive Cancer Centre building, Peter MacCallum Cancer Centre, Melbourne, Victoria Australia
| | - Huang-Chun Lien
- Department of Pathology, National Taiwan University Hospital, Taipei, Taiwan
| | - Sibylle Loibl
- German Breast Group, c/o GBG-Forschungs GmbH, Neu-Isenburg, Germany
| | - Zuzana Kos
- Department of Pathology, BC Cancer, Vancouver, British Columbia Canada
| | - Sherene Loi
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
- Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Matthew G. Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY USA
| | - Stefan Michiels
- Gustave Roussy, Universite Paris-Saclay, Villejuif, France
- Université Paris-Sud, Institut National de la Santé et de la Recherche Médicale, Villejuif, France
| | - Marleen Kok
- Division of Molecular Oncology & Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Alexander J. Lazar
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
- Department of Dermatology, The University of Texas MD Anderson Cancer Center, Houston, TX USA
| | | | - Loes F. S. Kooreman
- GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Pathology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Jeroen A. W. M. van der Laak
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY USA
| | - Brandon D. Gallas
- FDA/CDRH/OSEL/Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, MD USA
| | - Uday Kurkure
- Roche Tissue Diagnostics, Digital Pathology, Santa Clara, CA USA
| | - Michael Barnes
- Roche Diagnostics Information Solutions, Belmont, CA USA
| | - Roberto Salgado
- Division of Research and Cancer Medicine, Peter MacCallum Cancer Centre, University of Melbourne, Victoria, Australia
- Department of Pathology, GZA-ZNA Ziekenhuizen, Antwerp, Belgium
| | - Lee A. D. Cooper
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL USA
| |
Collapse
|
7
|
Bui MM, Riben MW, Allison KH, Chlipala E, Colasacco C, Kahn AG, Lacchetti C, Madabhushi A, Pantanowitz L, Salama ME, Stewart RL, Thomas NE, Tomaszewski JE, Hammond ME. Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists. Arch Pathol Lab Med 2019; 143:1180-1195. [PMID: 30645156 PMCID: PMC6629520 DOI: 10.5858/arpa.2018-0378-cp] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
CONTEXT.— Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing. OBJECTIVE.— To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used. DESIGN.— The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review. RESULTS.— Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants. CONCLUSIONS.— To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA.
Collapse
Affiliation(s)
- Marilyn M Bui
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Michael W Riben
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Kimberly H Allison
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Elizabeth Chlipala
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Carol Colasacco
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Andrea G Kahn
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Christina Lacchetti
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Anant Madabhushi
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Liron Pantanowitz
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Mohamed E Salama
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Rachel L Stewart
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - Nicole E Thomas
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - John E Tomaszewski
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| | - M Elizabeth Hammond
- From the Department of Anatomic Pathology, H. Lee Moffitt Cancer Center, Tampa, Florida (Dr Bui); the Department of Pathology, University of Texas MD Anderson Cancer Center, Houston (Dr Riben); the Department of Pathology, Stanford University Medical Center, Stanford, California (Dr Allison); Premier Laboratory, Longmont, Colorado (Ms Chlipala); Surveys (Mses Colasacco and Thomas), College of American Pathologists, Northfield, Illinois; the Department of Pathology, University of South Alabama, Mobile (Dr Kahn); Policy and Advocacy, American Society of Clinical Oncology, Alexandria, Virginia (Ms Lacchetti); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (Dr Madabhushi); the Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Pantanowitz); the Department of Pathology, University of Utah/ARUP Laboratories Inc, Salt Lake City (Dr Salama); the Department of Pathology, University of Kentucky, Lexington (Dr Stewart); the Department of Pathology and Anatomical Sciences, University at Buffalo, State University of New York, Buffalo (Dr Tomaszewski); and the Department of Pathology, University of Utah School of Medicine and Intermountain Healthcare, Salt Lake City (Dr Hammond)
| |
Collapse
|
8
|
Ghazvinian Zanjani F, Zinger S, Piepers B, Mahmoudpour S, Schelkens P, de With PHN. Impact of JPEG 2000 compression on deep convolutional neural networks for metastatic cancer detection in histopathological images. J Med Imaging (Bellingham) 2019; 6:027501. [PMID: 31037247 DOI: 10.1117/1.jmi.6.2.027501] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2018] [Accepted: 04/01/2019] [Indexed: 11/14/2022] Open
Abstract
The availability of massive amounts of data in histopathological whole-slide images (WSIs) has enabled the application of deep learning models and especially convolutional neural networks (CNNs), which have shown a high potential for improvement in cancer diagnosis. However, storage and transmission of large amounts of data such as gigapixel histopathological WSIs are challenging. Exploiting lossy compression algorithms for medical images is controversial but, as long as the clinical diagnosis is not affected, is acceptable. We study the impact of JPEG 2000 compression on our proposed CNN-based algorithm, which has produced performance comparable to that of pathologists and which was ranked second place in the CAMELYON17 challenge. Detecting tumor metastases in hematoxylin and eosin-stained tissue sections of breast lymph nodes is evaluated and compared with the pathologists' diagnoses in three different experimental setups. Our experiments show that the CNN model is robust against compression ratios up to 24:1 when it is trained on uncompressed high-quality images. We demonstrate that a model trained on lower quality images-i.e., lossy compressed images-depicts a classification performance that is significantly improved for the corresponding compression ratio. Moreover, it is also observed that the model performs equally well on all higher-quality images. These properties will help to design cloud-based computer-aided diagnosis (CAD) systems, e.g., telemedicine that employ deep CNN models that are more robust to image quality variations due to compression required to address data storage and transmission constraints. However, the results presented are specific to the CAD system and application described, and further work is needed to examine whether they generalize to other systems and applications.
Collapse
Affiliation(s)
| | - Svitlana Zinger
- Eindhoven University of Technology, SPS-VCA, Eindhoven, The Netherlands
| | | | - Saeed Mahmoudpour
- Vrije Universiteit Brussel, Department of Electronics and Informatics, Brussels, Belgium.,IMEC, Leuven, Belgium
| | - Peter Schelkens
- Vrije Universiteit Brussel, Department of Electronics and Informatics, Brussels, Belgium.,IMEC, Leuven, Belgium
| | - Peter H N de With
- Eindhoven University of Technology, SPS-VCA, Eindhoven, The Netherlands
| |
Collapse
|