Optimal frequency determination for terahertz technology-based detection of colitis-related cancer in mice.

absorption coefficient spectroscopy colitis-associated cancer colorectal cancer in mice terahertz spectroscopy terahertz transmission time-domain spectroscopy

Journal

Journal of biophotonics
ISSN: 1864-0648
Titre abrégé: J Biophotonics
Pays: Germany
ID NLM: 101318567

Informations de publication

Date de publication:
09 Aug 2023
Historique:
revised: 18 07 2023
received: 26 05 2023
accepted: 08 08 2023
pubmed: 9 8 2023
medline: 9 8 2023
entrez: 9 8 2023
Statut: aheadofprint

Résumé

Colorectal cancer is a prevalent malignancy globally, often linked to chronic colitis. Terahertz technology, with its noninvasive and fingerprint spectroscopic properties, holds promise in disease diagnosis. This study aimed to explore terahertz technology's application in colitis-associated cancer using a mouse model. Mouse colorectal tissues were transformed into paraffin-embedded blocks for histopathological analysis using HE staining. Terahertz transmission spectroscopy was performed on the tissue blocks. By comparing terahertz absorption differences, specific frequency bands were identified as optimal for distinguishing cancerous and normal tissues. The study revealed that terahertz spectroscopy effectively differentiates colitis-related cancers from normal tissues. Remarkably, 1.8 THz emerged as a potential optimal frequency for diagnosing colorectal cancer in mice. This suggests the potential for rapid histopathological diagnosis of colorectal cancer using terahertz technology.

Identifiants

pubmed: 37556310
doi: 10.1002/jbio.202300193
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e202300193

Subventions

Organisme : the Quanzhou Science Project of Production, Study, and Investigation
ID : WTTJJH-DJ2021
Organisme : the Fujian Provincial Health Technology Project
ID : 2021CXB008
Organisme : the Platform and Industry-University Collaboration Projects of Quanzhou, Fujian Province
ID : 2020N089s
Organisme : Joint Funds for the Innovation of Science and Technology, Fujian Province
ID : 2020Y9117
Organisme : the Fujian Medical University Education and Teaching Reform Research Project
ID : J200050

Informations de copyright

© 2023 Wiley-VCH GmbH.

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Auteurs

Yong Chen (Y)

Department of Gastroenterology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

Dan Li (D)

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

Yaling Liu (Y)

Department of Gastroenterology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

Liwen Hu (L)

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

Yuanlin Qi (Y)

Department of Biochemistry and Molecular Biology, Fujian Medical University, Fuzhou, China.

Yi Huang (Y)

Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China.

Zhenghao Zhang (Z)

Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China.

Tingyan Chen (T)

Department of Gastroenterology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

ChengDang Wang (C)

Department of Gastroenterology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

Shuncong Zhong (S)

Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing, School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China.

Jian Ding (J)

Department of Gastroenterology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

Classifications MeSH