Real-Time, AI-Guided Photodynamic Laparoscopy Enhances Detection in a Rabbit Model of Peritoneal Cancer Metastasis

Sep 23, 2026

Accurate diagnosis is essential for effective cancer treatment, especially in peritoneal surface malignancies where missed metastatic lesions can derail therapeutic planning. This study evaluated staging laparoscopy by integrating artificial intelligence–guided photodynamic diagnosis using the Phonozen photosensitizer activated at 405 nm in a rabbit peritoneal cancer metastasis model. VX2 cells created peritoneal carcinomatosis. White light and 405-nm blue excitation fluorescent visualization supported a tripartite workflow, with AI-enhanced PDD achieving markedly higher detection sensitivity.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages10

Reading Time25 min

AccessFree to download

Abstract

Introduction

Methods and experimental design

Diagnostic workflow (white light, blue excitation, AI support)

Results (detection sensitivity)

Funding and access information

Cancer Science ORIGINAL ARTICLE OPEN ACCESS Real-Time, AI-Guided Photodynamic Laparoscopy Enhances Detection in a Rabbit Model of Peritoneal Cancer Metastasis Adriana Rivera-Piza1 | Sung-Ho Lee1 | Hannah HeeJung Lee1,2 | Seungho Lee1,2 | Su-Jin Shin3 | Jaehyuk Kim4 | JongHyun Park1,5 | Jae Eun Yu1 | Sang Won Lee1 | Gyuri Park6 | Brian C. Wilson7,8 | Hyoung-Il Kim1,2,7 1Yonsei-Dongsung Photodynamic Therapy Research Center, Avison Biomedical Research Center, Yonsei University College of Medicine, Seoul, South Korea | 2Department of Surgery, Yonsei University College of Medicine, Seoul, South Korea | 3Department of Pathology, Gangnam Severance Hospital, Seoul, South Korea | 4CAE Group, Health and Medical Equipment Business, Samsung Electronics Co. Ltd. , Seoul, South Korea | 5Department of NanoScience and Technology, Graduate School of Convergence Science and Technology of Seoul National University, Seoul, South Korea | 6Yonsei Biomedical Research Institute, Yonsei University College of Medicine, Seoul, South Korea | 7Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada | 8Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada Correspondence: Hyoung-Il Kim ([cairus@naver.com](cairus@naver.com)) Received: 25 October 2024 | Revised: 16 January 2025 | Accepted: 27 January 2025 Funding: This study was supported by a faculty research grant from Dalim Biotech. The funders were not involved in the study design, data collection/ analysis, or manuscript preparation. Keywords: artificial intelligence | laparoscopy | peritoneal metastasis | photodynamic diagnosis | VX2 sarcoma ABSTRACT Accurate diagnosis is essential for effective cancer treatment, particularly in peritoneal surface malignancies, where failure to detect metastatic lesions can mislead the treatment plan. This study assessed the diagnostic accuracy of staging laparoscopy using the integration of artificial intelligence (AI)-guided photodynamic diagnosis (PDD) with the photosensitizer Phonozen, activated at 405 nm in a rabbit model. To create peritoneal carcinomatosis, VX2 cells were inoculated laparoscopically into the peritoneum of female white New Zealand rabbits. Conventional and PDD-guided laparoscopy utilized a customized light source that emitted broad-spectrum white light or 405-nm blue light, respectively. The surgical procedure comprised a tripartite approach: exploration and labeling of suspected nodules under white-light visualization, identification of additional metastatic tumors under blue-excitation fluorescent light, and confirmatory open laparotomy to locate overlooked nodules by palpation. Our results showed that the initial experimental data from 371 nodules in 14 rabbits, comparing conventional diagnostic laparoscopy and PDD, showed increased detection sensitivity from 67% ± 1.9%(conventional) to 98% ± 0.7%(PDD) in the small-size nodule. In the second experimental data set from 265 nodules in 10 rabbits, the addition of a real-time AI algorithm further increased the sensitivity to 100% ± 0.0% . Combining PDD with AI enhances the detection of peritoneal cancer metastasis in staging laparoscopy. | Abbreviations: PDD, photodynamic diagnosis; PDD-AI, photodynamic diagnosis with Aartificial intelligence; PDT, photodynamic therapy; POM, peritoneal oligometastasis; WL, white light.
Adriana Rivera-Piza and Sung-Ho Lee contributed equally. | | --- | | This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
© 2025 The Author(s). Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. | 966 Cancer Science, 2025; 116:966–975 [https://doi.org/10.1111/cas.70009](https://doi.org/10.1111/cas.70009) 1 | Introductio

FAQs

Why is accurate detection of peritoneal metastasis critical?

Missed metastatic lesions can mislead treatment planning, shifting surgical intent away from curative approaches and affecting prognosis.

How does the study combine AI with photodynamic laparoscopy?

It integrates AI-guided photodynamic diagnosis with a photosensitizer (Phonozen) activated at 405 nm, using white light and blue-excitation fluorescent visualization within a staged exploration-confirmation workflow.

What detection performance improvement was reported?

Compared with conventional diagnostic laparoscopy, AI-guided photodynamic diagnosis increased detection sensitivity substantially, reaching 98% ± 0.7% in one dataset and 100% ± 0.0% after adding the real-time AI algorithm in the second dataset.

Sep 23, 2026

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