Towards a national strategy for digital pathology in Switzerland

Andrew Janowczyk; Daniel Baumhoer; Stefan Dirnhofer; Rainer Grobholz; Anja Kipar; Laurence de Leval; Doron Merkler; Olivier Michielin; Holger Moch; Aurel Perren; Sven Rottenberg; Laura Rubbia-Brandt; Mark A Rubin; Christine Sempoux; Markus Tolnay; Inti Zlobec; Viktor Hendrik Koelzer; Swiss Digital Pathology Consortium (SDiPath)

doi:10.1007/s00428-022-03345-0

Towards a national strategy for digital pathology in Switzerland

Virchows Arch. 2022 Oct;481(4):647-652. doi: 10.1007/s00428-022-03345-0. Epub 2022 May 27.

Authors

Andrew Janowczyk^{1

2}, Daniel Baumhoer³, Stefan Dirnhofer³, Rainer Grobholz^{4

5}, Anja Kipar⁶, Laurence de Leval⁷, Doron Merkler^{8

9}, Olivier Michielin^{1

10

11}, Holger Moch^{12

13}, Aurel Perren¹⁴, Sven Rottenberg^{15

16}, Laura Rubbia-Brandt^{8

9}, Mark A Rubin^{16

17}, Christine Sempoux⁷, Markus Tolnay³, Inti Zlobec¹⁸, Viktor Hendrik Koelzer^{19

20}; Swiss Digital Pathology Consortium (SDiPath)

Affiliations

¹ Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland.
² Biomedical Engineering Department, Case Western Reserve University, Cleveland, OH, USA.
³ Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland.
⁴ Medical Faculty, University of Zurich, Zurich, Switzerland.
⁵ Institute of Pathology, Kantonsspital Aarau, Aarau, Switzerland.
⁶ Institute of Veterinary Pathology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
⁷ Institute of Pathology, Department of Laboratory Medicine and Pathology, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland.
⁸ Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland.
⁹ Division of Clinical Pathology, Diagnostic Departement Geneva University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.
¹⁰ Precision Oncology Center, Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland.
¹¹ Molecular Modelling Group, Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
¹² Department of Pathology and Molecular Pathology, University of Zurich and University Hospital Zurich, Raemistrasse 100, CH-8091, Zurich, Switzerland.
¹³ Comprehensive Cancer Center Zurich, Zurich, Switzerland.
¹⁴ Institute of Pathology, University of Bern, Murtenstrasse 31, CH-3008, Bern, Switzerland.
¹⁵ Institute of Animal Pathology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
¹⁶ Bern Center for Precision Medicine, University of Bern, Bern, Switzerland.
¹⁷ Department for BioMedical Research, Precision Oncology Laboratory, University of Bern, Bern, Switzerland.
¹⁸ Institute of Pathology, University of Bern, Murtenstrasse 31, CH-3008, Bern, Switzerland. inti.zlobec@pathology.unibe.ch.
¹⁹ Medical Faculty, University of Zurich, Zurich, Switzerland. viktor.koelzer@usz.ch.
²⁰ Department of Pathology and Molecular Pathology, University of Zurich and University Hospital Zurich, Raemistrasse 100, CH-8091, Zurich, Switzerland. viktor.koelzer@usz.ch.

Abstract

Precision medicine is entering a new era of digital diagnostics; the availability of integrated digital pathology (DP) and structured clinical datasets has the potential to become a key catalyst for biomedical research, education and business development. In Europe, national programs for sharing of this data will be crucial for the development, testing, and validation of machine learning-enabled tools supporting clinical decision-making. Here, the Swiss Digital Pathology Consortium (SDiPath) discusses the creation of a Swiss Digital Pathology Infrastructure (SDPI), which aims to develop a unified national DP network bringing together the Swiss Personalized Health Network (SPHN) with Swiss university hospitals and subsequent inclusion of cantonal and private institutions. This effort builds on existing developments for the national implementation of structured pathology reporting. Opening this national infrastructure and data to international researchers in a sequential rollout phase can enable the large-scale integration of health data and pooling of resources for research purposes and clinical trials. Therefore, the concept of a SDPI directly synergizes with the priorities of the European Commission communication on the digital transformation of healthcare on an international level, and with the aims of the Swiss State Secretariat for Economic Affairs (SECO) for advancing research and innovation in the digitalization domain. SDPI directly addresses the needs of existing national and international research programs in neoplastic and non-neoplastic diseases by providing unprecedented access to well-curated clinicopathological datasets for the development and implementation of novel integrative methods for analysis of clinical outcomes and treatment response. In conclusion, a SDPI would facilitate and strengthen inter-institutional collaboration in technology, clinical development, business and research at a national and international scale, promoting improved patient care via precision medicine.

Keywords: Artificial intelligence; Biomedical research; Image analysis; Pathology; Precision medicine.

MeSH terms

Biomedical Research*
Europe
Humans
Machine Learning
Precision Medicine
Switzerland