Xi Gangqin, Huang Chen, Lin Jie, Luo Tianyi, Kang Bingzi, Xu Mingyu, Xu Huizhen, Li Xiaolu, Chen Jianxin, Qiu Lida, Zhuo Shuangmu
School of Science, Jimei University, Xiamen, China.
Shengli Clinical College of Fujian Medical University, Department of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, China.
J Biophotonics. 2023 Nov;16(11):e202300172. doi: 10.1002/jbio.202300172. Epub 2023 Aug 30.
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.
肺癌是中国最常被诊断出的癌症，也是癌症相关死亡的主要原因。在肺癌手术期间对肿瘤组织进行快速而精确的评估可以减少手术时间并改善切缘阴性评估，从而提高无病生存率和总生存率。本研究旨在探索无标记多光子显微镜（MPM）对腺癌组织成像、检测组织病理学特征以及区分正常和癌性肺组织的潜力。我们发现二次谐波产生（SHG）信号对胶原纤维具有显著特异性，能够对肺腺癌中的胶原特征进行定量。此外，我们开发了一种胶原评分，可用于区分肿瘤边界处的正常和肿瘤区域，显示出良好的分类性能。我们的研究结果表明，MPM成像技术与基于图像的胶原特征提取方法相结合，可以快速准确地检测早期肺腺癌组织。
