Publikationsdatenbank

Developing a qualification and verification strategy for digital tissue image analysis in toxicological pathology (2021)

Art

Zeitschriftenartikel / wissenschaftlicher Beitrag

Autoren

Zuraw, Aleksandra

Staup, Michael

Klopfleisch, Robert (WE 12)

Aeffner, Famke

Brown, Danielle

Westerling-Bui, Thomas

Rudmann, Daniel

Quelle

Toxicologic pathology

Bandzählung: 49

Heftzählung: 4

Seiten: 773 – 783

ISSN: 0192-6233

Sprache

Englisch

Verweise

URL (Volltext): https://journals.sagepub.com/doi/10.1177/0192623320980310

DOI: 10.1177/0192623320980310

Pubmed: 33371797

Kontakt

Institut für Tierpathologie

Robert-von-Ostertag-Str. 15
14163 Berlin
+49 30 838 62450
pathologie@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Digital tissue image analysis is a computational method for analyzing whole-slide images and extracting large, complex, and quantitative data sets. However, as with any analysis method, the quality of generated results is dependent on a well-designed quality control system for the entire digital pathology workflow. Such system requires clear procedural controls, appropriate user training, and involvement of specialists to oversee key steps of the workflow. The toxicologic pathologist is responsible for reporting data obtained by digital image analysis and therefore needs to ensure that it is correct. To accomplish that, they must understand the main parameters of the quality control system and should play an integral part in its conception and implementation. This manuscript describes the most common digital tissue image analysis end points and potential sources of analysis errors. In addition, it outlines recommended approaches for ensuring quality and correctness of results for both classical and machine-learning based image analysis solutions, as adapted from a recently proposed Food and Drug Administration regulatory framework for modifications to artificial intelligence/machine learning-based software as a medical device. These approaches are beneficial for any type of toxicopathologic study which uses the described end points and can be adjusted based on the intended use of the image analysis solution.