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A Multicenter, Prospective Study on the Diagnostic Efficacy of Femtosecond Laser Label-Free Imaging Combined With Artificial Intelligence-Assisted Diagnosis for Rapid Diagnosis of Lung Cancer Surgical Specimens

A Multicenter, Prospective Study on the Diagnostic Efficacy of Femtosecond Laser Label-Free Imaging Combined With Artificial Intelligence-Assisted Diagnosis for Rapid Diagnosis of Lung Cancer Surgical Specimens

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07794449
Enrollment
335
Registered
2026-08-31
Start date
2026-09-01
Completion date
2028-08-31
Last updated
2026-08-31

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer (Diagnosis)

Keywords

Lung Cancer, FLI

Brief summary

To investigate the diagnostic efficacy of Femtosecond Laser Label-Free Imaging combined with artificial intelligence-assisted diagnosis for rapid diagnosis of lung cancer.

Detailed description

To investigate the diagnostic efficacy of Femtosecond Laser Label-Free Imaging combined with artificial intelligence-assisted diagnosis for rapid diagnosis of lung cancer.

Interventions

DIAGNOSTIC_TESTFemtosecond Laser Label-Free Imaging Combined with Artificial Intelligence

Femtosecond Laser Label-Free Imaging Combined with Artificial Intelligence. The diagnostic results will be blinded to both the physicians (including all clinicians involved in the patient's diagnostic and treatment process, such as surgeons and pathologists) and the patient, and the diagnostic results will NOT affect the original treatment plan.

Sponsors

Shanghai Zhongshan Hospital
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL

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 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.

Design outcomes

Primary

MeasureTime frame
The accuracy of FLI combined with AI-assisted diagnosis in differentiating benign from malignant lung surgical specimens.through study completion, an average of 2 year

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Sep 1, 2026