Rapid label-free detection of early-stage lung adenocarcinoma and tumor boundary via multiphoton microscopy.

Autor: Xi G; School of Science, Jimei University, Xiamen, China., Huang C; Shengli Clinical College of Fujian Medical University, Department of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, China., Lin J; Shengli Clinical College of Fujian Medical University, Department of Pathology, Fujian Provincial Hospital, Fuzhou, China., Luo T; School of Science, Jimei University, Xiamen, China., Kang B; School of Science, Jimei University, Xiamen, China., Xu M; School of Science, Jimei University, Xiamen, China., Xu H; School of Science, Jimei University, Xiamen, China., Li X; School of Science, Jimei University, Xiamen, China., Chen J; Key Laboratory of OptoElectronic Science and Technology for Medicine of the Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, China., Qiu L; College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou, China., Zhuo S; School of Science, Jimei University, Xiamen, China.
Jazyk: angličtina
Zdroj: Journal of biophotonics [J Biophotonics] 2023 Nov; Vol. 16 (11), pp. e202300172. Date of Electronic Publication: 2023 Aug 30.
DOI: 10.1002/jbio.202300172
Abstrakt: Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related deaths in China. Rapid and precise evaluation of tumor tissue during lung cancer surgery can reduce operative time and improve negative-margin assessment, thus increasing disease-free and overall survival rates. This study aimed to explore the potential of label-free multiphoton microscopy (MPM) for imaging adenocarcinoma tissues, detecting histopathological features, and distinguishing between normal and cancerous lung tissues. We showed that second harmonic generation (SHG) signals exhibit significant specificity for collagen fibers, enabling the quantification of collagen features in lung adenocarcinomas. In addition, we developed a collagen score that could be used to distinguish between normal and tumor areas at the tumor boundary, showing good classification performance. Our findings demonstrate that MPM imaging technology combined with an image-based collagen feature extraction method can rapidly and accurately detect early-stage lung adenocarcinoma tissues.
(© 2023 Wiley-VCH GmbH.)
Databáze: MEDLINE
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