Femtosecond Laser Imaging (FLI): A Rapid and Reliable Alternative for Intraoperative Pathological Assessment in Thoracic Oncology
Presented During:
Monday, May 4, 2026: 9:00AM - 4:00PM
McCormick Place Lakeside Center
Posted Room Name:
Exhibit Hall, Poster Area
Abstract No:
P0132
Submission Type:
Abstract Submission
Authors:
Hao Yin (1), Hao Yin (1), Ming Li (1), Fangyi Liu (1), Wendi Zhu (1), Wenlong Yu (2), Xin Zhu (2), Mingxiang Feng (1), Lijie Tan (1)
Institutions:
(1) Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, Shanghai, (2) Femtosecond Research Center(Guangzhou), Ltd, Guangdong, Guangzhou
Submitting Author:
Hao Yin
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Co-Author(s):
Hao Yin
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Ming Li
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Fangyi Liu
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Wendi Zhu
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Wenlong Yu
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Femtosecond Research Center(Guangzhou), Ltd
Femtosecond Research Center(Guangzhou), Ltd
Xin Zhu
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Femtosecond Research Center(Guangzhou), Ltd
Femtosecond Research Center(Guangzhou), Ltd
Mingxiang Feng
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Lijie Tan
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Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Department of Thoracic Surgery, Zhongshan Hospital, Fudan University
Presenting Author:
Hao Yin
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Zhongshan Hospital, Fudan University
Zhongshan Hospital, Fudan University
Abstract:
Objective
This study aims to evaluate the potential of FLI as a supplementary tool for intraoperative frozen section analysis in lung cancer and as a method for predicting the efficacy of neoadjuvant therapy in esophageal cancer. The goal is to assess how FLI images can enhance intraoperative decision-making in lung cancer and provide insights into treatment responses in esophageal cancer.
Methods
We collected 73 tissue samples from 40 patients undergoing resection for lung and esophageal cancers. The tissue was imaged using the FLI system, which provides high-resolution, label-free, and multi-modal imaging without the need for staining or sectioning. HE-stained sections were prepared for each sample as the gold standard for pathological comparison. The FLI images and HE sections were analyzed for their ability to detect key tissue structures and tumor regions.
Results
We collected tissue samples from 40 patients undergoing resection for lung and esophageal cancers, including both pre- and post-treatment samples from esophageal cancer patients receiving neoadjuvant therapy. A total of 73 samples were imaged using the FLI system, which enables high-resolution, label-free, multi-modal imaging without the need for staining or slicing. H&E-stained sections were prepared for each sample for comparison. FLI images were analyzed for tumor detection, margin evaluation, and therapy-induced tissue changes in esophageal cancer.
Conclusions
FLI technology holds great promise as a real-time, label-free imaging method that could complement intraoperative frozen section analysis. The findings suggest that FLI may offer enhanced precision in tumor detection and surgical margin evaluation. However, further studies with a larger sample size and continued development of machine learning algorithms are needed to fully realize its potential as a reliable adjunct to traditional pathology techniques.
This study aims to evaluate the potential of FLI as a supplementary tool for intraoperative frozen section analysis in lung cancer and as a method for predicting the efficacy of neoadjuvant therapy in esophageal cancer. The goal is to assess how FLI images can enhance intraoperative decision-making in lung cancer and provide insights into treatment responses in esophageal cancer.
Methods
We collected 73 tissue samples from 40 patients undergoing resection for lung and esophageal cancers. The tissue was imaged using the FLI system, which provides high-resolution, label-free, and multi-modal imaging without the need for staining or sectioning. HE-stained sections were prepared for each sample as the gold standard for pathological comparison. The FLI images and HE sections were analyzed for their ability to detect key tissue structures and tumor regions.
Results
We collected tissue samples from 40 patients undergoing resection for lung and esophageal cancers, including both pre- and post-treatment samples from esophageal cancer patients receiving neoadjuvant therapy. A total of 73 samples were imaged using the FLI system, which enables high-resolution, label-free, multi-modal imaging without the need for staining or slicing. H&E-stained sections were prepared for each sample for comparison. FLI images were analyzed for tumor detection, margin evaluation, and therapy-induced tissue changes in esophageal cancer.
Conclusions
FLI technology holds great promise as a real-time, label-free imaging method that could complement intraoperative frozen section analysis. The findings suggest that FLI may offer enhanced precision in tumor detection and surgical margin evaluation. However, further studies with a larger sample size and continued development of machine learning algorithms are needed to fully realize its potential as a reliable adjunct to traditional pathology techniques.
ADULT CARDIAC:
Innovations: New devices or novel approaches, preclinical or clinical
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