Label-free Femtosecond Laser Imaging Combined With the Fast Lung Artificial Intelligence Model for Rapid Intraoperative Diagnosis of Lung Surgical Specimens: A Multicentre, Prospective, Parallel-workflow, Non-inferiority Study.
This study aims to evaluate whether femtosecond laser imaging combined with FastLung AI model can provide intraoperative diagnostic performance that is non-inferior to standard frozen section diagnosis for pulmonary nodules or suspected pulmonary tumor lesions. Patients scheduled for lung surgery and requiring intraoperative pathological assessment will be prospectively enrolled. After tumor excision, the fresh tumor specimen will be bisected through the central plane. One half will be used for standard frozen section diagnosis, and the mirrored counterpart will be used for femtosecond laser imaging. Both diagnostic results will be compared with the final paraffin-embedded pathological diagnosis as the reference standard. The results of femtosecond laser imaging will not guide intraoperative clinical decision-making.
• Preoperative imaging suggests a pulmonary nodule, pulmonary space-occupying lesion, or suspected pulmonary tumor lesion.
• The participant is scheduled to undergo pulmonary wedge resection, segmentectomy, lobectomy, or other pulmonary surgery.
• Fresh lung tissue specimens can be obtained intraoperatively for femtosecond laser imaging.
• Intraoperative frozen section diagnosis is planned to assess the nature of the tumor lesion.
• Corresponding postoperative paraffin-embedded pathological diagnosis can be obtained.
• The participant or the participant's legally authorized representative has signed the written informed consent form.
• Patients had not received any antitumor treatment prior to enrollment or specimen collection, including chemotherapy, radiotherapy, targeted therapy, immunotherapy, or other systemic anticancer treatments.