An observational study in Lung Cancers, sponsored by Fuzhou General Hospital. Not yet recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-03-31.
Sponsored by Fuzhou General Hospital · Observational
Although modern medicine has made significant progress in the diagnosis and treatment of lung cancer, most patients are diagnosed at locally advanced stage or with distant metastases, especially in the late stages where the cancer has spread to other organs through hematogenous metastasis. This not only significantly the survival rate of patients but also increases the complexity and difficulty of treatment. Hematogenous metastasis plays an important role in the clinical progression of lung cancer, its complex biological processes pose a huge challenge for clinical management. Early detection of hematogenous metastasis is difficult, and traditional imaging methods have limited sensitivity in detecting small metastatic lesions. The emerging technology of circulating tumor cells (CTCs) has been limited in clinical application due to its high detection costs and technical requirements. Therefore researching and developing high-sensitivity, high-specificity, simple, easy-to-popularize, and low-cost technologies to predict the risk of hematogenous metastasis lung cancer is crucial for early diagnosis and more precise treatment. Raman spectroscopy (RS), a non-invasive and highly specific molecular detection technology, can detect in biomolecules such as proteins, nucleic acids, lipids, and sugars related to tumor metabolism in biological samples at the molecular level. Surface-enhanced R spectroscopy (SERS), developed based on this technology, is one of the feasible methods for high-sensitivity biomolecular analysis. Although SERS technology has shown diagnostic results in numerous preclinical studies of various tumors, it is limited by small sample sizes and lacks external validation. Therefore, clinical studies on the diagnosis of tumors Raman spectroscopy are needed, with the following requirements: 1. Objective, rapid, and practical Raman spectroscopy data processing methods are needed, and and deep learning methods may be the best classification methods; 2. Multicenter, large-sample clinical samples are needed to train deep learning diagnostic models, and real-world performance should be validated through external data from prospective studies. In previous study, the investigators collected serum Raman spectroscopy data from a cohort of 23 patients with lung malignancies and developed an intelligent Raman diagnostic system for hematogenous metastasis in non-small cell lung cancer (NSCLC) based on learning models, with an accuracy rate of 95%. To obtain the highest level of clinical evidence and truly achieve clinical translation, this prospective, multicenter clinical aims to validate the use of this intelligent diagnostic system for early diagnosis of hematogenous metastasis in NSCLC.
This study used a confocal Raman microspectrometer produced by Renishaw, Britain, purchased by the Key Laboratory of the School of Optoelectronics and Engineering of Fujian Normal University. The spectral resolution was 2 cm-1, the excitation wavelength was 785 nm, and a 20x objective Leica microscope was used to collect SERS spectra in the range of 400-1800 cm-1. The excitation irradiation time of each spectrum was 1 s, and the laser power was 30 mW. The measured SERS spectra were collected using the WIRE3.4 (Renishaw) software package. In order to reduce the interference of fluorescence background signals between different spectral lines, the Vancouver Raman Algorithm software (multi-order polynomial fitting algorithm) was used to remove the fluorescence background, remove the baseline and smooth the results. At the same time, in order to avoid changes in peak spectrum intensity caused by instrument performance problems, the spectrum after background subtraction was normalized using NILabVIEW2014 software. Then, the obtained spectral data was analyzed for mean spectrum and charts using Origin, and multivariate statistical analysis was performed.
5,422 studies on the registry are indexed under Lung Neoplasms; 1,346 are open to participants now.
This study's planned enrollment of 200 is close to the median of 200 across 1,434 observational studies indexed under Lung Neoplasms.
Browse Lung Neoplasms studies →Fuzhou General Hospital is the lead sponsor of 40 studies on the registry; 9 are open to participants now.
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The participants were diagnosed with lung malignancy through pathological examination and were able to undergo clinical staging based on TNM.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Chronic obstructive pulmonary disease: long-term lung disease that makes it hard to breathe out, including emphysema and chronic bronchitis.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
COPD
Chronic obstructive pulmonary disease: long-term lung disease that makes it hard to breathe out, including emphysema and chronic bronchitis.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Patients who underwent chest CT scans and were found to have lung nodules and underwent surgical resection
Diagnostic Test: Serum Raman spectroscopy intelligent diagnostic system
1. Screening interested participants should sign the appropriate informed consent (ICF) prior to completion any study procedures. 2. The investigator will review symptoms, risk factors, and other non-invasive inclusion and exclusion criteria. 3. The following is the general sequence of events during the 3 months evaluation period: 4. Completion of baseline procedures Participants were assessed for 3 months and completed all safety monitoring.
Diagnostic accuracy
Determine whether there is hematogenous metastasis in enrolled lung cancer patients through RAMAN intelligent diagnostic system
Time frame: through study completion, an average of 1 year
Time to RAMAN diagnosis
The time to perform RAMAN testing and obtain diagnostic results after obtaining serum
Time frame: up to 30 days
Safety assessment Results
AEs and SAEs through Day 30
Time frame: up to 30 days
Plan to share: Undecided
No publications or documents are linked to this record.
Start is estimated for Apr 2026; primary completion for Jun 2026, 1 month later.
Of 591 non-industry observational studies under Lung Neoplasms, half reached primary completion within 65 months of starting (the median), counting those still running; a quarter within 25 and three quarters within 162. This study's planned 1 month is below that.
Counting every sponsor, half of 681 studies reached it within 57 months; a quarter within 25 and three quarters within 135.
How these figures are worked out, and which studies are left out of them.
This study is not yet recruiting, as verified in Mar 2025. You cannot join it, but the record below documents what was studied.
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Fuzhou General Hospital