A Multicenter Prospective Study Evaluating the Diagnostic Performance of Femtosecond Laser Label-Free Imaging Combined With Artificial Intelligence for Predicting High-Risk Pathological Features in Lung Cancer

To investigate the diagnostic performance of Femtosecond Laser Label-Free Imaging combined with artificial intelligence for predicting high-risk pathological features in lung cancer

Inclusion Criteria: 1. Pulmonary nodules detected by clinical imaging with an indication for surgical resection. 2. Patient agrees to and is planned for pulmonary (partial) resection. 3. Resected specimens are suitable for FLI imaging. 4. Written informed consent obtained from the patient or legal representative. 5. Patients undergoing pulmonary (partial) resection at our hospital during this study. Exclusion Criteria: 1. Insufficient sample. 2. Specimen with crushing, contamination, or improper preservation, precluding valid imaging as judged by the investigator. 3. Inability to obtain matched pathology results corresponding to FLI images. 4. Inability to obtain final pathological diagnosis. 5. Other conditions deemed by the investigator as unsuitable for study participation.