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

August 28, 2026 updated by: Shanghai Zhongshan Hospital

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

Study Overview

Status

Not yet recruiting

Conditions

Lung Cancer (Diagnosis)

Intervention / Treatment

Diagnostic test: Femtosecond Laser Label-Free Imaging Combined with Artificial Intelligence.

Study Type

Observational

Enrollment (Estimated)

333

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

Child
Adult
Older Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Non-Probability Sample

Study Population

Lung cancer patients undergoing pulmonary resection.

Description

Inclusion Criteria:

Pulmonary nodules detected by clinical imaging with an indication for surgical resection.
Patient agrees to and is planned for pulmonary (partial) resection.
Resected specimens are suitable for FLI imaging.
Written informed consent obtained from the patient or legal representative.
Patients undergoing pulmonary (partial) resection at our hospital during this study.

Exclusion Criteria:

Insufficient sample.
Specimen with crushing, contamination, or improper preservation, precluding valid imaging as judged by the investigator.
Inability to obtain matched pathology results corresponding to FLI images.
Inability to obtain final pathological diagnosis.
Other conditions deemed by the investigator as unsuitable for study participation.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
The primary endpoint is the accuracy of the FLI combined with the AI model in predicting regional lymph node metastasis status in lung cancer, evaluated using postoperative pathology results as the reference standard. Time Frame: through study completion, an average of 2 year	through study completion, an average of 2 year

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shanghai Zhongshan Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

September 1, 2026

Primary Completion (Estimated)

August 31, 2028

Study Completion (Estimated)

August 31, 2028

Study Registration Dates

First Submitted

August 24, 2026

First Submitted That Met QC Criteria

August 28, 2026

First Posted (Actual)

September 2, 2026

Study Record Updates

Last Update Posted (Actual)