Skip to main navigation Skip to search Skip to main content

Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis

  • Laura M.G. van Huizen*
  • , Max Blokker
  • , Johannes M.A. Daniels
  • , Teodora Radonic
  • , Jan H. von der Thüsen
  • , Mitko Veta
  • , Jouke T. Annema
  • , Marie Louise Groot
  • *Corresponding author for this work
  • Vrije Universiteit Amsterdam
  • Amsterdam UMC
  • Eindhoven University of Technology

Research output: Contribution to journal › Article › Academic › peer-review

11 Citations (Scopus)
141 Downloads (Pure)

Abstract

Lung cancer is one of the most prevalent and lethal cancers. To improve health outcomes while reducing health care burden, it becomes crucial to move toward early detection and cost-effective workflows. Currently, there is no method for the on-site rapid histologic feedback on biopsies taken in diagnostic, endoscopic, or surgical procedures. Higher harmonic generation (HHG) microscopy is a laser-based technique that provides images of unprocessed tissue. In this study, we report the feasibility of an HHG portable microscope in the clinical workflow in terms of acquisition time, image quality, and diagnostic accuracy in suspected pulmonary and pleural malignancy. One hundred nine biopsies of 47 patients were imaged and a biopsy overview image was provided within a median acquisition time of 6 minutes after excision. The assessment by pathologists and an artificial intelligence algorithm showed that image quality was sufficient for a malignancy or nonmalignancy diagnosis in 97% of the biopsies, and 87% of the HHG images were correctly scored by the pathologists. HHG is therefore an excellent candidate to provide a rapid pathology outcome on biopsy samples, enabling immediate diagnosis and (local) treatment.

Original languageEnglish
Article number100633
JournalModern Pathology
Volume38
Issue number1
DOIs
Publication statusPublished - Jan 2025

Bibliographical note

Publisher Copyright:
© 2024 The Authors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis'. Together they form a unique fingerprint.

Cite this