Benchmarking Pathology Feature Extractors for Whole Slide Image Classification

St Andrews Research Repository (St Andrews Research Repository)

Abstract

Weakly supervised whole slide image classification is a key task in computational pathology, which involves predicting a slide-level label from a set of image patches constituting the slide. Constructing models to solve this task involves multiple design choices, often made without robust empirical or conclusive theoretical justification. To address this, we conduct a comprehensive benchmarking of feature extractors to answer three critical questions: 1) Is stain normalisation still a necessary preprocessing step? 2) Which feature extractors are best for downstream slide-level classification? 3) How does magnification affect downstream performance? Our study constitutes the most comprehensive evaluation of publicly available pathology feature extractors to date, involving more than 10,000 training runs across 14 feature extractors, 9 tasks, 5 datasets, 3 downstream architectures, 2 levels of magnification, and various preprocessing setups. Our findings challenge existing assumptions: 1) We observe empirically, and by analysing the latent space, that skipping stain normalisation and image augmentations does not degrade performance, while significantly reducing memory and computational demands. 2) We develop a novel evaluation metric to compare relative downstream performance, and show that the choice of feature extractor is the most consequential factor for downstream performance. 3) We find that lower-magnification slides are sufficient for accurate slide-level classification. Contrary to previous patch-level benchmarking studies, our approach emphasises clinical relevance by focusing on slide-level biomarker prediction tasks in a weakly supervised setting with external validation cohorts. Our findings stand to streamline digital pathology workflows by minimising preprocessing needs and informing the selection of feature extractors.

Authors 9

1. Georg Wölflein

   University of St Andrews · Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   University of St Andrews, St Andrews, United Kingdom

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

2. Dyke Ferber

   University Hospital Heidelberg · National Center for Tumor Diseases · Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

   Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany

3. Asier Rabasco Meneghetti

   Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

4. Omar S. M. El Nahhas

   Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

5. Daniel Truhn Aachen

   Universitätsklinikum Aachen

   Affiliation as printed

   University Hospital Aachen, Germany

6. Zunamys Itzell Carrero

   Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

7. David James Harrison

   University of St Andrews

   Affiliation as printed

   University of St Andrews, St Andrews, United Kingdom

8. Ognjen Arandjelović

   University of St Andrews

   Affiliation as printed

   University of St Andrews, St Andrews, United Kingdom

9. Jakob Nikolas Kather

   University Hospital Heidelberg · National Center for Tumor Diseases · University Hospital Carl Gustav Carus · Else Kröner Fresenius Center for Digital Health · Technische Universität Dresden

   Affiliation as printed

   Else Kröner Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

   Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany

   Department of Medicine I, University Hospital Dresden, Dresden, Germany