[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"lung-nodule\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:lung-nodule":26},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,6,0,[8,40,69,93,118,141],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":13,"acronym":14,"eligibilityCriteria":15,"healthyVolunteers":16,"sex":17,"minAge":18,"maxAge":4,"enrollmentInfo":19,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":23,"conditions":24,"keywords":4,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":28,"lastUpdatePostDateStruct":29,"startDateStruct":32,"completionDateStruct":34,"leadSponsor":36,"locationsCount":39},"100628346","sparc---screening-for-lung-cancer-with-platelets-via-an-ai-enabled-rna-based-classifier-100628346",false,"NCT07460440","SPARC - Screening for Lung Cancer With Platelets Via an AI-enabled RNA-based Classifier","SPARC","Study Population 1: Treatment-Naïve Patients with a Lung Nodule or Lung Cancer\n\nInclusion Criteria:\n\n* Aged 21 years or older\n* Meeting at least one of the following two criteria:\n* Diagnosed with any stage or type of lung cancer\n* Having at least one lung nodule identified on imaging (e.g., low dose computed tomography \\[LDCT\\] or other diagnostic chest imaging) that was completed within 180 days prior to enrollment, and where there is planned or recommended biopsy, surgical resection, radiation therapy, systemic therapy, or other invasive diagnostic or therapeutic procedure to further evaluate the nodule(s) in the next six months based on the clinical judgment of the patient's provider(s)\n\nExclusion Criteria:\n\n* Other diagnosis of, or treatment for, any cancer within the last 6 months except for non-melanoma skin cancer, carcinoma in situ of the cervix, or low-grade prostate cancer (defined as Gleason score ≤ 6) treated locally\n* A history of lung cancer or metastatic cancer to the lungs from an extrathoracic primary site with definitive treatment (surgical, medical, or radiotherapy) within the past 2 years\n* Currently receiving any systemic therapy (chemotherapy, immunotherapy, and\u002For targeted therapy) or radiation therapy for lung cancer\n* Already undergone surgical resection of the lung cancer in part or in whole\n* Have undergone invasive diagnostic or therapeutic procedures (e.g., biopsy, surgery) related to the lung nodule within the past 3 months\n* Unable to provide blood sample\n\nStudy Population 2: Control Subjects\n\nInclusion Criteria:\n\n* Aged 21 years or older\n\nExclusion Criteria:\n\n* Any active malignancy or diagnosis of cancer within the last 6 months except for non-melanoma skin cancer, carcinoma in situ of the cervix, or low-grade prostate cancer (defined as Gleason score ≤ 6) treated locally\n* Treatment for any cancer within the last 6 months except for non-melanoma skin cancer, carcinoma in situ of the cervix, or low-grade prostate cancer (defined as Gleason score ≤ 6) treated locally\n* Hospitalization or surgery (other than minor surgery such as mole removal) within the last 8 weeks\n* Renal failure (defined as eGFR \\\u003C 60 mL\u002Fmin\u002F1.73m² or on dialysis)\n* Liver failure (defined as having hepatic encephalopathy of any degree, OR moderately severe coagulopathy defined as INR ≥ 1.5, OR known cirrhosis, OR ALT of ≥ 10X ULN, OR total bilirubin of ≥ 3.0 mg\u002FdL, OR diagnosis of liver failure)\n* Decompensated or end-stage heart failure (defined as ACC\u002FAHA Stage C or Stage D heart failure)\n* Venous thrombosis, myocardial infarction, or stroke within the last 8 weeks\n* Currently pregnant or have been pregnant within the last 12 weeks\n* Any blood product transfusion within the last 8 weeks\n* Personal history of lung cancer at any time\n* Unable to provide blood sample",true,"ALL","21 Years",{"count":20,"type":21},240,"ESTIMATED","OBSERVATIONAL","The purpose of this study is to test whether combining a unique analytical approach with changes in platelet RNA expression accurately diagnoses lung cancer. Using retrospective platelet transcriptomic data from 522 patients with non-small cell lung cancer (NSCLC, the most common type of lung cancer), an approach that appears to accurately classify lung cancer has been developed.\n\nThe study will build upon these retrospective analyses to prospectively recruit patients with newly diagnosed lung cancer, obtain platelet RNA samples from whole blood, and perform validation analyses. This research will also test whether this approach accurately distinguishes benign from malignant lung nodules.",[25,26],"Lung Cancer","Lung Nodule","NOT_YET_RECRUITING","2026-05-12",{"date":30,"type":31},"2026-05-15","ACTUAL",{"date":33,"type":21},"2026-06",{"date":35,"type":21},"2028-06",{"name":37,"class":38},"University of Utah","OTHER",2,{"id":41,"slug":42,"hasResults":11,"nctId":43,"briefTitle":44,"officialTitle":45,"acronym":46,"eligibilityCriteria":47,"healthyVolunteers":11,"sex":17,"minAge":48,"maxAge":4,"enrollmentInfo":49,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":51,"conditions":52,"keywords":53,"overallStatus":58,"whyStopped":4,"lastUpdateSubmitDate":59,"lastUpdatePostDateStruct":60,"startDateStruct":62,"completionDateStruct":64,"leadSponsor":66,"locationsCount":68},"100520306","biobank-for-the-identification-of-biomarkers-in-lung-cancer-bird-biomarkers-in-respiratory-disease-100520306","NCT06054854","Biobank for the Identification of Biomarkers in Lung Cancer (BIRD, Biomarkers in Respiratory Disease)","Biobank for the Identification of Diagnostic, Prognostic or Therapeutic (Response and Resistance) Biomarkers in Lung Cancer (Early and Advanced Stages of Lung Cancer Cohort of the BIRD (Biomarkers in Respiratory Disease) Biobank)","BIRD-NK","Inclusion Criteria:\n\n* Patients with 1 to 3 lung nodules including one \\> 1 cm seen on chest CT\n* OR: patients with suspected lung cancer requiring diagnostic and\u002For therapeutic bronchial endoscopy\n* OR: Patient with histologically confirmed lung cancer, whether early stages prior to surgery, locally advanced or metastatic, included before the start of any anti-cancer treatment.\n* Patient affiliated or beneficiary of a social security scheme\n* Patients who are able to receive and understand information about the study and their participation and who have freely given their signed inform consent before any collection of samples or data necessary for the research (no restriction of rights by the judicial authorities and knowledge of the French language).\n\nExclusion Criteria:\n\n* Patient deprived of liberty on administrative or judicial decision, or patient under guardianship, curators or safeguard of justice\n* Female patients who are pregnant or breastfeeding","18 Years",{"count":50,"type":21},3000,"The BIRD biobank aims at collecting clinical and biological data from patients suffering from a chronic respiratory disease. The lung cancer subpopulation will be divided into two cohorts to identify biomarkers of cancer. One cohort will include patients with supra-centimetric lung nodule(s) whether surveillance, bronchoscopic or radio-guided biopsy or surgery is indicated, patients suspected of lung cancers requiring diagnostic and\u002For therapeutic bronchial endoscopy and patients with a known early stage lung cancer (early-stage cohort). The second cohort will include known advanced stage lung cancers (III-IV).",[26,25],[26,25,54,55,56,57],"Early Stage Lung Cancer","Advanced Lung Cancer","Liquid Biopsy","Biomarkers","RECRUITING","2026-03-16",{"date":61,"type":31},"2026-03-19",{"date":63,"type":31},"2024-06-13",{"date":65,"type":21},"2033-10-01",{"name":67,"class":38},"University Hospital, Toulouse",1,{"id":70,"slug":71,"hasResults":11,"nctId":72,"briefTitle":73,"officialTitle":74,"acronym":4,"eligibilityCriteria":75,"healthyVolunteers":11,"sex":17,"minAge":48,"maxAge":76,"enrollmentInfo":77,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":79,"conditions":80,"keywords":81,"overallStatus":58,"whyStopped":4,"lastUpdateSubmitDate":84,"lastUpdatePostDateStruct":85,"startDateStruct":87,"completionDateStruct":89,"leadSponsor":91,"locationsCount":68},"100562038","evaluating-the-real-world-performance-of-an-ai-based-lung-nodule-detection-tool-100562038","NCT06597968","Evaluating the Real World Performance of an AI Based Lung Nodule Detection Tool","Performance Estimation of Triaging Artificial Intelligence Based Computer-Aided Detection Algorithm in Routine Chest Radiography","Inclusion Criteria:\n\n* Chest X-ray images of patients aged 18 - 89 years.\n* Modality: CR\u002FDR\u002FDX.\n* PA\u002Fview\n* Lung nodules measuring 6 mm -30 mm (for chest X-ray images where presence of nodules is required).\n\nExclusion Criteria:\n\n* Incomplete view of the chest.\n* Lateral view\n* Known lung cancer at the time of Chest x-ray images.","89 Years",{"count":78,"type":21},45991,"chest x-rays will be analyzed by AI software for a secondary read of lung nodules. Chest x-rays will either be sent to the AI tool to be read or to radiologists to read. If the image is sent to the AI tool, the AI software will generate a report on if it detects a lung nodule or not. The image will then be sent to a radiologist to determine if there is agreement or disagreement with the AI tool.",[26],[82,83],"chest x-ray","CAD software","2026-01-27",{"date":86,"type":31},"2026-01-29",{"date":88,"type":31},"2025-06-24",{"date":90,"type":21},"2026-04-30",{"name":92,"class":38},"University Hospitals Cleveland Medical Center",{"id":94,"slug":95,"hasResults":11,"nctId":96,"briefTitle":97,"officialTitle":98,"acronym":4,"eligibilityCriteria":99,"healthyVolunteers":11,"sex":17,"minAge":100,"maxAge":4,"enrollmentInfo":101,"targetDuration":103,"studyType":22,"phases":4,"briefSummary":104,"conditions":105,"keywords":106,"overallStatus":58,"whyStopped":4,"lastUpdateSubmitDate":109,"lastUpdatePostDateStruct":110,"startDateStruct":112,"completionDateStruct":114,"leadSponsor":116,"locationsCount":68},"100580554","epigenetic-nucleosomes-in-plasma-for-pulmonary-nodule-differentiation-100580554","NCT06838806","Epigenetic Nucleosomes in Plasma for Pulmonary Nodule Differentiation","Differentiating Benign and Malignant Pulmonary Nodules Using Epigenetically Modified Nucleosomes in Plasma","Inclusion Criteria:\n\n* Aged 20 or older\n* Underwent a low-dose chest CT scan or a standard chest CT scan, showing lung nodules ≥ 6mm\n* Individuals understand the content of the consent form and are willing to participate in this study.\n* The lung nodule is assessed by a physician as high-risk, requiring thoracic surgery or biopsy for diagnosis\n\nExclusion Criteria:\n\n* Pregnant women\n* Individuals without capacity for consent, unable to understand the content of the consent form, or unwilling to participate in this study\n* Assessed by a physician as unsuitable for thoracic surgery or biopsy for diagnosis","20 Years",{"count":102,"type":21},500,"6 Months","Investigators aim to evaluate the diagnostic accuracy of the Nu.Q blood test for lung cancer in the Taiwanese population and compare its diagnostic performance with low-dose computed tomography (LDCT) or computed tomography (CT). Additionally, investigators will investigate the potential role of Nu.Q in lung cancer prevention and its impact on survival outcomes.\n\nStudy Method:\n\nInvestigators plan to collect 20 mL of blood samples from individuals undergoing chest LDCT\u002FCT, isolate plasma for Nu.Q™ analysis, and compare the results with corresponding lung cancer pathology findings. The estimated sample size is 500 participants.",[26],[107,108],"liquid biopsy","epigenetic","2025-11-16",{"date":111,"type":31},"2025-11-19",{"date":113,"type":31},"2025-03-11",{"date":115,"type":21},"2026-03-31",{"name":117,"class":38},"National Taiwan University Hospital",{"id":119,"slug":120,"hasResults":11,"nctId":121,"briefTitle":122,"officialTitle":122,"acronym":4,"eligibilityCriteria":123,"healthyVolunteers":11,"sex":17,"minAge":100,"maxAge":124,"enrollmentInfo":125,"targetDuration":4,"studyType":22,"phases":4,"briefSummary":127,"conditions":128,"keywords":4,"overallStatus":58,"whyStopped":4,"lastUpdateSubmitDate":130,"lastUpdatePostDateStruct":131,"startDateStruct":133,"completionDateStruct":135,"leadSponsor":137,"locationsCount":140},"100600545","artificial-intelligence-for-pathology-diagnosis-and-prognosis-prediction-of-lung-nodule-using-smartphone-photos-100600545","NCT07098884","Artificial Intelligence for Pathology Diagnosis and Prognosis Prediction of Lung Nodule Using Smartphone Photos","Inclusion Criteria: (1) Participants scheduled for surgery for radiological finding of pulmonary lesions from the preoperative thin-section CT scans; (2) Age ranging from 20-75 years.\n\nExclusion Criteria: (1) Participants with incomplete clinical information; (2) Participants who have received anti-tumor therapy.","75 Years",{"count":126,"type":21},600,"The current study aims to develop and validate a deep learning signature for diagnosing pathology and predicting prognosis of lung nodule using smartphone photos of resected tumor specimens.",[129,26],"Artificial Intelligence","2025-07-30",{"date":132,"type":31},"2025-08-01",{"date":134,"type":31},"2025-06-01",{"date":136,"type":21},"2025-10-30",{"name":138,"class":139},"Anhui Provincial Hospital","OTHER_GOV",3,{"id":142,"slug":143,"hasResults":11,"nctId":144,"briefTitle":145,"officialTitle":146,"acronym":4,"eligibilityCriteria":147,"healthyVolunteers":11,"sex":17,"minAge":48,"maxAge":148,"enrollmentInfo":149,"targetDuration":4,"studyType":151,"phases":152,"briefSummary":154,"conditions":155,"keywords":156,"overallStatus":27,"whyStopped":4,"lastUpdateSubmitDate":160,"lastUpdatePostDateStruct":161,"startDateStruct":163,"completionDateStruct":165,"leadSponsor":167,"locationsCount":140},"100580001","ai-based-low-dose-cbct-reconstruction-for-clinical-application-100580001","NCT06831617","AI-based Low Dose CBCT Reconstruction for Clinical Application","AI-based Low Dose CBCT Reconstruction for Lung Puncture Guidance: A Multicenter Randomized Controlled Study","Inclusion Criteria:\n\n* Participants who require CBCT-guided precutaneous lung puncture (PLP) and meet the clinical indications for the procedure.\n* Participants whose physical condition is suitable for PLP.\n* Participants are willing to sign informed consent.\n\nExclusion Criteria:\n\n* Participants have metallic implants in the body, which severely affects the image quality.\n* Participants are pregnant or breastfeeding.\n* Participants are unwilling or unable to sign informed consent.","80 Years",{"count":150,"type":21},400,"INTERVENTIONAL",[153],"NA","The goal of this clinical trial is to learn if AI-based low dose CBCT reconstructed images can guide lung puncture effectively. The main questions it aims to answer are:\n\n1. Does the AI-based low dose CBCT reconstruction model reconstruct high quality images?\n2. Is it possible that low-dose CBCT reconstructed images can guide lung puncture procedures without compromising the efficiency of the procedure? Researchers will compare AI-based low dose CBCT reconstructed images to a placebo (conventional CBCT images) to see if AI-based low dose CBCT reconstructed image can guide lung puncture procedures without compromising the efficiency of the procedure.\n\nParticipants will:\n\n1. Undergo lung puncture under AI-based low dose CBCT reconstructed images guidance or under conventional CBCT images\n2. Be followed up for 1 week postoperative to obtain patient complications",[26],[129,26,157,158,159],"Cone Beam CT","Lung Puncture","Images Reconstruction","2025-02-12",{"date":162,"type":31},"2025-02-18",{"date":164,"type":21},"2025-03-01",{"date":166,"type":21},"2025-11-30",{"name":168,"class":38},"Union Hospital, Tongji Medical College, Huazhong University of Science and Technology"]