Privacy risks of whole-slide image sharing in digital pathology.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
04 05 2023
Historique:
received: 25 04 2022
accepted: 11 04 2023
medline: 8 5 2023
pubmed: 5 5 2023
entrez: 4 5 2023
Statut: epublish

Résumé

Access to large volumes of so-called whole-slide images-high-resolution scans of complete pathological slides-has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologists, and research. Nevertheless, a methodology based on risk analysis for evaluating the privacy risks associated with sharing such imaging data and applying the principle "as open as possible and as closed as necessary" is still lacking. In this article, we develop a model for privacy risk analysis for whole-slide images which focuses primarily on identity disclosure attacks, as these are the most important from a regulatory perspective. We introduce a taxonomy of whole-slide images with respect to privacy risks and mathematical model for risk assessment and design . Based on this risk assessment model and the taxonomy, we conduct a series of experiments to demonstrate the risks using real-world imaging data. Finally, we develop guidelines for risk assessment and recommendations for low-risk sharing of whole-slide image data.

Identifiants

pubmed: 37142591
doi: 10.1038/s41467-023-37991-y
pii: 10.1038/s41467-023-37991-y
pmc: PMC10160114
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2577

Informations de copyright

© 2023. The Author(s).

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Auteurs

Petr Holub (P)

BBMRI-ERIC, Graz, Austria. petr.holub@bbmri-eric.eu.
Institute of Computer Science, Masaryk University, Brno, Czech Republic. petr.holub@bbmri-eric.eu.

Heimo Müller (H)

BBMRI.at & Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Graz, A-8010, Austria.

Tomáš Bíl (T)

Institute of Computer Science, Masaryk University, Brno, Czech Republic.

Luca Pireddu (L)

Visual and Data-intensive Computing Group, CRS4, Pula, Italy.

Markus Plass (M)

BBMRI.at & Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Graz, A-8010, Austria.

Fabian Prasser (F)

Berlin Institute of Health @ Charité - Universitätsmedizin Berlin, Berlin, Germany.

Irene Schlünder (I)

TMF eV, Berlin, Germany.

Kurt Zatloukal (K)

BBMRI.at & Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Graz, A-8010, Austria.

Rudolf Nenutil (R)

BBMRI.cz & Masaryk Memorial Cancer Institute, Brno, Czech Republic.

Tomáš Brázdil (T)

Faculty of Informatics, Masaryk University, Brno, Czech Republic.

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