Optical coherence photoacoustic microscopy for 3D cancer model imaging with AI-assisted organoid analysis

Abigail J. Deloria; Agnes Csiszar; Shiyu Deng; Mohammad Ali Sabbaghi; Francesco Branciforti; Lukasz Bugyi; Giulia Rotunno; Richard Haindl; Rainer Leitgeb; Massimo Salvi; Manojit Pramanik; Yi Yuan; Leopold Schmetterer; Gergely Szakacs; Wolfgang Drexler; Kristen M. Meiburger; Mengyang Liu

doi:10.1038/s41377-025-02177-2

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Optical coherence photoacoustic microscopy for 3D cancer model imaging with AI-assisted organoid analysis

Original Articles

- Optical coherence photoacoustic microscopy for 3D cancer model imaging with AI-assisted organoid analysis
- Light: Science & Applications Vol. 15, Issue 4, Pages: 1215-1229(2026)
- Affiliations：
  
  1.Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
  2.Center for Cancer Research, Medical University of Vienna, Vienna, Austria
  3.PolitoBIOMed Lab, Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy
  4.Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA
  5.School of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei, China
  6.Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
  7.Singapore Eye Research Institute, Singapore, Singapore
  8.SERI-NTU Advanced Ocular Engineering (STANCE) Laboratory, Singapore, Singapore
  9.Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
  10.Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
  11.School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore, Singapore
  12.Fondation Ophthalmologique Adolphe De Rothschild, Paris, France
- Author bio：
  
  Mengyang Liu (mengyang.liu@meduniwien.ac.at)
- Funds：
- DOI：10.1038/s41377-025-02177-2
  CLC：
- Received：11 April 2025，
  
  Revised：2025-12-04，
  
  Accepted：20 December 2025，
  
  Online First：05 February 2026，
  
  Published：30 April 2026
- Accepted：
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Deloria, A. J. et al. Optical coherence photoacoustic microscopy for 3D cancer model imaging with AI-assisted organoid analysis. Light: Science & Applications, 15, 1215-1229 (2026).
DOI：

Deloria, A. J. et al. Optical coherence photoacoustic microscopy for 3D cancer model imaging with AI-assisted organoid analysis. Light: Science & Applications, 15, 1215-1229 (2026). DOI： 10.1038/s41377-025-02177-2.

摘要

Abstract

Cancer organoids and cancer spheroids are 3D cell culture models with distinct yet overlapping purposes in cancer research. Various commercially available optical imaging techniques have been employed to study these cell cultures

but these methods suffer from various limitations such as the requirement of fluorescence labeling

complicated sample handling

and limited image volume size. In this work

we demonstrate a multimodal optical coherence photoacoustic microscopy (OC-PAM) system for the study of these models

overcoming these limitations. We first performed a longitudinal study using optical coherence microscopy (OCM) for breast cancer organoids. Using the OCM imaging results

artificial intelligence (AI)-based algorithms were developed to automatically segment individual organoids and classify their viability over time using a radiomics texture feature approach

enabling robust

quantitative tracking and classification at the single-organoid level. To supplement OCM's contrast

we then performed OC-PAM imaging of spheroid models with both melanin positive and melanin negative cells. In the second study

the OC-PAM images clearly mapped the distribution of melanin positive cells hidden amongst melanin negative cells. These results suggest that OC-PAM coupled with AI techniques can be a powerful tool to study cancer organoids and cancer spheroids.

关键词

Keywords

references

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