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Author Spotlight: 3D Scanning and Augmented Reality for Enhanced Cancer Surgery Communication
Published on: December 15, 2023
Harnessing non-destructive 3D pathology
Jonathan T C Liu1,2,3, Adam K Glaser4, Kaustav Bera5
1Department of Mechanical Engineering, University of Washington, Seattle, WA, USA. jonliu@uw.edu.
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High-throughput methods for slide-free three-dimensional (3D) pathological analyses of whole biopsies and surgical specimens offer the promise of modernizing traditional histology workflows and delivering improvements in diagnostic performance. Advanced optical methods now enable the interrogation of orders of magnitude more tissue than previously possible, where volumetric imaging allows for enhanced quantitative analyses of cell distributions and tissue structures that are prognostic and predictive. Non-destructive imaging processes can simplify laboratory workflows, potentially reducing costs, and can ensure that samples are available for subsequent molecular assays. However, the large size of the feature-rich datasets that they generate poses challenges for data management and computer-aided analysis. In this Perspective, we provide an overview of the imaging technologies that enable 3D pathology, and the computational tools-machine learning, in particular-for image processing and interpretation. We also discuss the integration of various other diagnostic modalities with 3D pathology, along with the challenges and opportunities for clinical adoption and regulatory approval.

