Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

Journal: The American journal of pathology
Published Date: Sep 8, 2021

Abstract

Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical utility. This study investigates the visualization of deep features (DFs) to characterize two lung cancer subtypes, adenocarcinoma and squamous cell carcinoma. It demonstrates that a subset of DFs, called prominent DFs, can accurately distinguish these two cancer subtypes. Visualization of such individual DFs allows for a better understanding of histopathologic patterns at both the whole-slide and patch levels, and discrimination of these cancer types. These DFs were visualized at the whole slide image level through DF-specific heatmaps and at tissue patch level through the generation of activation maps. In addition, these prominent DFs can distinguish carcinomas of organs other than the lung. This framework may serve as a platform for evaluating the interpretability of any deep network for diagnostic decision making.

Authors

  • Taher Dehkharghanian
  • Shahryar Rahnamayan
  • Abtin Riasatian
    Kimia Laboratory, University of Waterloo, Waterloo, Canada.
  • Azam A Bidgoli
    Nature Inspired Computer Intelligence (NICI) Lab, Ontario Tech University, Oshawa, Ontario, Canada.
  • Shivam Kalra
  • Manit Zaveri
  • Morteza Babaie
  • Mahjabin S Seyed Sajadi
    KIMIA (Laboratory for Knowledge Inference in Medical Image Analysis) Lab, University of Waterloo, Waterloo, Ontario, Canada.
  • Ricardo Gonzalelz
    KIMIA (Laboratory for Knowledge Inference in Medical Image Analysis) Lab, University of Waterloo, Waterloo, Ontario, Canada.
  • Phedias Diamandis
    Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada. p.diamandis@mail.utoronto.ca.
  • Liron Pantanowitz
    Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
  • Tao Huang
    The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Hamid R Tizhoosh
    Kimia Lab, University of Waterloo, Waterloo, ON Canada.

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