Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Ashley L Kiemen; Alexander Ioannis Damanakis; Alicia M Braxton; Jin He; Daniel Laheru; Elliot K Fishman; Patrick Chames; Cristina Almagro Pérez; Pei-Hsun Wu; Denis Wirtz; Laura D Wood; Ralph H Hruban

doi:10.1016/j.medj.2022.11.009

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Med. 2023 Feb 10;4(2):75-91. doi: 10.1016/j.medj.2022.11.009. Epub 2023 Jan 24.

Authors

Affiliations

¹ Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Chemical & Biomolecular Engineering, The Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
² Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of General, Visceral, Cancer and Transplant Surgery, University Hospital of Cologne, Cologne, Germany.
³ Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
⁴ Department of Surgery, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
⁵ Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
⁶ Department of Radiology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
⁷ Antibody Therapeutics and Immunotargeting Team, Aix Marseille University, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille, France.
⁸ Department of Chemical & Biomolecular Engineering, The Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
⁹ Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. Electronic address: ldwood@jhmi.edu.
¹⁰ Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Oncology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. Electronic address: rhruban@jhmi.edu.

Abstract

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Keywords: CODA; artificial intelligence; clearing; digital pathology; machine learning; pancreatic cancer; three dimensions.

Publication types

Review
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Animals
Histological Techniques
Humans
Imaging, Three-Dimensional* / methods
Microscopy
Pancreatic Neoplasms* / diagnostic imaging

Abstract

Publication types

MeSH terms

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