Volume 16, Issue 10 e202300153
RESEARCH ARTICLE

Detection of fibrotic changes in the progression of liver diseases by label-free multiphoton imaging

Xingxin Huang

Xingxin Huang

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Yuan-E Lian

Yuan-E Lian

Department of Pathology, The Affiliated Union Hospital of Fujian Medical University, Fuzhou, China

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Lida Qiu

Lida Qiu

College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou, China

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XunBin Yu

XunBin Yu

Department of Pathology, Fujian Provincial Hospital, Fuzhou, China

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Zhenlin Zhan

Zhenlin Zhan

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Zheng Zhang

Zheng Zhang

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Xiong Zhang

Xiong Zhang

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Hongxin Lin

Hongxin Lin

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Shuoyu Xu

Shuoyu Xu

Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China

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Jianxin Chen

Jianxin Chen

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

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Yannan Bai

Corresponding Author

Yannan Bai

Shengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary and Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou, China

Correspondence

Yannan Bai, Department of Hepatobiliopancreatic Surgery, Fujian Provincial Hospital, Fuzhou, 350001, China.

Email: [email protected]

Lianhuang Li, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, 350007, China.

Email: [email protected]

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Lianhuang Li

Corresponding Author

Lianhuang Li

Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China

Correspondence

Yannan Bai, Department of Hepatobiliopancreatic Surgery, Fujian Provincial Hospital, Fuzhou, 350001, China.

Email: [email protected]

Lianhuang Li, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, 350007, China.

Email: [email protected]

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First published: 04 July 2023

Xingxin Huang, Yuan-E Lian and Lida Qiu contributed equally to this work.

Abstract

Collagen fibers play an important role in the progression of liver diseases. The formation and progression of liver fibrosis is a dynamic pathological process accompanied by morphological changes in collagen fibers. In this study, we used multiphoton microscopy for label-free imaging of liver tissues, allowing direct detection of various components including collagen fibers, tumors, blood vessels, and lymphocytes. Then, we developed a deep learning classification model to automatically identify tumor regions, and the accuracy reaches 0.998. We introduced an automated image processing method to extract eight collagen morphological features from various stages of liver diseases. Statistical analysis showed significant differences between them, indicating the potential use of these quantitative features for monitoring fibrotic changes during the progression of liver diseases. Therefore, multiphoton imaging combined with automatic image processing method would hold a promising future in rapid and label-free diagnosis of liver diseases.image

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflict of interest.

DATA AVAILABILITY STATEMENT

The data supporting the findings of this study are available within the article. The data not shown can be available from the corresponding authors upon reasonable requests.

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