Lung Cancer (Diagnosis)NCT07799038
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
An observational study of Lung Cancer (Diagnosis), run by Shanghai Zhongshan Hospital.
Trial summary
To investigate the diagnostic performance of Femtosecond Laser Label-Free Imaging combined with artificial intelligence for predicting high-risk pathological features in lung cancer Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Lung Cancer (Diagnosis)
- What is being tested?
- Femtosecond Laser Label-Free Imaging Combined with Artificial Intelligence.
- How many people
- 333 participants
- Where
- No sites listed yet
- Study dates
- 1 Sep 2026to 31 Aug 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
Study population: Lung cancer patients undergoing pulmonary resection.
Who may be able to join
- 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.
Who cannot join
- 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.
About this study
To investigate the diagnostic performance of Femtosecond Laser Label-Free Imaging combined with artificial intelligence for predicting high-risk pathological features in lung cancer
- Conditions
- Lung Cancer (Diagnosis)
- Being tested
- Femtosecond Laser Label-Free Imaging Combined with Artificial Intelligence.
- Keywords
- Lung cancer, FLI
- Medical subject headings
- Lung Neoplasms, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Femtosecond Laser Label-Free Imaging Combined with Artificial Intelligence.Diagnostic test
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.
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: through study completion, an average of 2 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Sep 2026
- Study start1 Sep 2026 (estimated)
- Primary completion31 Aug 2028 (estimated)
- Study completion31 Aug 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung Cancer (Diagnosis)Studies of the same condition, open and under way.
- More trials run by Shanghai Zhongshan HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 333 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai Zhongshan Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07799038
- Sponsor's protocol ID
- B2026-532
- Status last verified
- Aug 2026
- First submitted
- 24 Aug 2026
- Last updated
- 2 Sep 2026
- Results posted
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 2 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- 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
- ClinicalTrials.gov ID
- NCT07799038
- Acronym / sponsor ID
- B2026-532
- Conditions
- Lung Cancer (Diagnosis)
- Keywords
- Lung cancer, FLI
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 333 participants (estimated)
- Lead sponsor
- Shanghai Zhongshan HospitalUniversity, hospital or other
- Study start
- 1 Sep 2026 (estimated)
- Primary completion
- 31 Aug 2028 (estimated)
- Study completion
- 31 Aug 2028 (estimated)
- First posted
- 2 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- Study population
- Lung cancer patients undergoing pulmonary resection.
Key inclusion criteria (5 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Femtosecond 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. | Diagnostic test | – |
Primary outcome
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
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Sep 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer (Diagnosis), run by Shanghai Zhongshan Hospital.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 2 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Sep 2026; AzTrials last refreshed its copy on 6 Nov 2026.