Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program.


Journal

Laboratory investigation; a journal of technical methods and pathology
ISSN: 1530-0307
Titre abrégé: Lab Invest
Pays: United States
ID NLM: 0376617

Informations de publication

Date de publication:
10 2023
Historique:
received: 07 05 2023
revised: 17 07 2023
accepted: 24 07 2023
medline: 23 10 2023
pubmed: 31 7 2023
entrez: 30 7 2023
Statut: ppublish

Résumé

Nonalcoholic fatty liver disease is rapidly becoming one of the most common causes of chronic liver disease worldwide and is the leading cause of liver-related morbidity and mortality. A quantitative assessment of the degree of steatosis would be more advantageous for diagnostic evaluation and exploring the patterns of disease progression. Here, multiphoton microscopy, based on the second harmonic generation and 2-photon excited fluorescence, was used to label-free image the samples of nonalcoholic fatty liver. Imaging results confirm that multiphoton microscopy is capable of directly visualizing important pathologic features such as normal hepatocytes, hepatic steatosis, Mallory bodies, necrosis, inflammation, collagen deposition, microvessel, and so on and is a reliable auxiliary tool for the diagnosis of nonalcoholic fatty liver disease. Furthermore, we developed an image segmentation algorithm to simultaneously assess hepatic steatosis and fibrotic changes, and quantitative results reveal that there is a correlation between the degree of steatosis and collagen content. We also developed a feature extraction program to precisely display the spatial distribution of hepatocyte steatosis in tissues. These studies may be beneficial for a better clinical understanding of the process of steatosis as well as for exploring possible therapeutic targets.

Identifiants

pubmed: 37517702
pii: S0023-6837(23)00166-6
doi: 10.1016/j.labinv.2023.100223
pii:
doi:

Substances chimiques

Collagen 9007-34-5

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

100223

Informations de copyright

Copyright © 2023 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights reserved.

Auteurs

Xingxin Huang (X)

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.

Yuan-E Lian (YE)

Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China.

Lida Qiu (L)

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

XunBin Yu (X)

Department of Pathology, Fujian Provincial Hospital, Fuzhou, China.

Jikui Miao (J)

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.

Shichao Zhang (S)

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.

Zheng Zhang (Z)

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.

Xiong Zhang (X)

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.

Jianxin Chen (J)

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.

Yannan Bai (Y)

Department of Hepatobiliary and Pancreatic Surgery, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China. Electronic address: 42236640@qq.com.

Lianhuang Li (L)

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. Electronic address: lhli@fjnu.edu.cn.

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Classifications MeSH