Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numerous challenges, including technical and regulatory hurdles in translating research results into clinical diagnostic produ...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Journal of Pathology Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2153353924000269 |
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| author | Norman Zerbe Lars Ole Schwen Christian Geißler Katja Wiesemann Tom Bisson Peter Boor Rita Carvalho Michael Franz Christoph Jansen Tim-Rasmus Kiehl Björn Lindequist Nora Charlotte Pohlan Sarah Schmell Klaus Strohmenger Falk Zakrzewski Markus Plass Michael Takla Tobias Küster André Homeyer Peter Hufnagl |
| author_facet | Norman Zerbe Lars Ole Schwen Christian Geißler Katja Wiesemann Tom Bisson Peter Boor Rita Carvalho Michael Franz Christoph Jansen Tim-Rasmus Kiehl Björn Lindequist Nora Charlotte Pohlan Sarah Schmell Klaus Strohmenger Falk Zakrzewski Markus Plass Michael Takla Tobias Küster André Homeyer Peter Hufnagl |
| author_sort | Norman Zerbe |
| collection | DOAJ |
| description | Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numerous challenges, including technical and regulatory hurdles in translating research results into clinical diagnostic products and the lack of standardized interfaces.The open and vendor-neutral EMPAIA initiative addresses these challenges. Here, we provide an overview of EMPAIA's achievements and lessons learned. EMPAIA integrates various stakeholders of the pathology AI ecosystem, i.e., pathologists, computer scientists, and industry. In close collaboration, we developed technical interoperability standards, recommendations for AI testing and product development, and explainability methods. We implemented the modular and open-source EMPAIA Platform and successfully integrated 14 AI-based image analysis apps from eight different vendors, demonstrating how different apps can use a single standardized interface. We prioritized requirements and evaluated the use of AI in real clinical settings with 14 different pathology laboratories in Europe and Asia. In addition to technical developments, we created a forum for all stakeholders to share information and experiences on digital pathology and AI. Commercial, clinical, and academic stakeholders can now adopt EMPAIA's common open-source interfaces, providing a unique opportunity for large-scale standardization and streamlining of processes.Further efforts are needed to effectively and broadly establish AI assistance in routine laboratory use. To this end, a sustainable infrastructure, the non-profit association EMPAIA International, has been established to continue standardization and support broad implementation and advocacy for an AI-assisted digital pathology future. |
| format | Article |
| id | doaj-art-224c25035ba642a39b737874f9152e0c |
| institution | OA Journals |
| issn | 2153-3539 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Pathology Informatics |
| spelling | doaj-art-224c25035ba642a39b737874f9152e0c2025-08-20T02:35:39ZengElsevierJournal of Pathology Informatics2153-35392024-12-011510038710.1016/j.jpi.2024.100387Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiativeNorman Zerbe0Lars Ole Schwen1Christian Geißler2Katja Wiesemann3Tom Bisson4Peter Boor5Rita Carvalho6Michael Franz7Christoph Jansen8Tim-Rasmus Kiehl9Björn Lindequist10Nora Charlotte Pohlan11Sarah Schmell12Klaus Strohmenger13Falk Zakrzewski14Markus Plass15Michael Takla16Tobias Küster17André Homeyer18Peter Hufnagl19Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyFraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359 Bremen, GermanyTechnische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, GermanyQuIP GmbH, Reinhardtstraße 1, 10117 Berlin, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyInstitute of Pathology, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, Germany; Corresponding author at: Evangelisches Geriatriezentrum Berlin, Haus 10, Reinickendorfer Str. 61, 13347 Berlin, Germany.Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyInstitute of Pathology, Carl Gustav Carus University Hospital Dresden (UKD), TU Dresden (TUD), Fetscherstraße 74, 01307 Dresden, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyInstitute of Pathology, Carl Gustav Carus University Hospital Dresden (UKD), TU Dresden (TUD), Fetscherstraße 74, 01307 Dresden, GermanyMedical University of Graz, Diagnostic and Research Center for Molecular BioMedicine, Diagnostic & Research Institute of Pathology, Neue Stiftingtalstrasse 6, 8010 Graz, AustriaVitasystems GmbH, Gottlieb-Daimler-Straße 8, 68165 Mannheim, GermanyTechnische Universität Berlin, DAI-Labor, Ernst-Reuter-Platz 7, 10587 Berlin, GermanyFraunhofer Institute for Digital Medicine MEVIS, Max-von-Laue-Straße 2, 28359 Bremen, GermanyCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pathology, Charitéplatz 1, 10117 Berlin, GermanyOver the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numerous challenges, including technical and regulatory hurdles in translating research results into clinical diagnostic products and the lack of standardized interfaces.The open and vendor-neutral EMPAIA initiative addresses these challenges. Here, we provide an overview of EMPAIA's achievements and lessons learned. EMPAIA integrates various stakeholders of the pathology AI ecosystem, i.e., pathologists, computer scientists, and industry. In close collaboration, we developed technical interoperability standards, recommendations for AI testing and product development, and explainability methods. We implemented the modular and open-source EMPAIA Platform and successfully integrated 14 AI-based image analysis apps from eight different vendors, demonstrating how different apps can use a single standardized interface. We prioritized requirements and evaluated the use of AI in real clinical settings with 14 different pathology laboratories in Europe and Asia. In addition to technical developments, we created a forum for all stakeholders to share information and experiences on digital pathology and AI. Commercial, clinical, and academic stakeholders can now adopt EMPAIA's common open-source interfaces, providing a unique opportunity for large-scale standardization and streamlining of processes.Further efforts are needed to effectively and broadly establish AI assistance in routine laboratory use. To this end, a sustainable infrastructure, the non-profit association EMPAIA International, has been established to continue standardization and support broad implementation and advocacy for an AI-assisted digital pathology future.http://www.sciencedirect.com/science/article/pii/S2153353924000269Digital pathologyArtificial intelligenceStandardizationInteroperabilityValidation of algorithmsExplainability |
| spellingShingle | Norman Zerbe Lars Ole Schwen Christian Geißler Katja Wiesemann Tom Bisson Peter Boor Rita Carvalho Michael Franz Christoph Jansen Tim-Rasmus Kiehl Björn Lindequist Nora Charlotte Pohlan Sarah Schmell Klaus Strohmenger Falk Zakrzewski Markus Plass Michael Takla Tobias Küster André Homeyer Peter Hufnagl Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative Journal of Pathology Informatics Digital pathology Artificial intelligence Standardization Interoperability Validation of algorithms Explainability |
| title | Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative |
| title_full | Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative |
| title_fullStr | Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative |
| title_full_unstemmed | Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative |
| title_short | Joining forces for pathology diagnostics with AI assistance: The EMPAIA initiative |
| title_sort | joining forces for pathology diagnostics with ai assistance the empaia initiative |
| topic | Digital pathology Artificial intelligence Standardization Interoperability Validation of algorithms Explainability |
| url | http://www.sciencedirect.com/science/article/pii/S2153353924000269 |
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