[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"breast-cancer-detection\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:breast-cancer-detection":26},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,5,0,[8,44,82,110,142],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":22,"briefSummary":24,"conditions":25,"keywords":27,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":33,"lastUpdatePostDateStruct":34,"startDateStruct":37,"completionDateStruct":39,"leadSponsor":41,"locationsCount":4},"100633201","phase-2-fap-petct-for-staging-patients-with-breast-cancer-100633201",false,"NCT07523607","FAP PET\u002FCT for Staging Patients With Breast Cancer","[⁶⁸Ga]Ga-FAP-2286 PET\u002FCT for Staging and Restaging Patients With Newly Diagnosed Primary Breast Cancer: a Phase II Study (FAPILOUS)","Inclusion Criteria:\n\n* Male and females ≥ 18 years\n* Biopsy-verified newly diagnosed breast cancer\n* Can read and understand Danish\n* Capable of providing written and informed consent\n* Undergoing a routine \\[¹⁸F\\]FDG PET\u002FCT scan as part of the clinical standard diagnostic workup\n\nExclusion Criteria:\n\n* Pregnant or lactating women\n* Not able to participate in the conduct of the scan due to any reason ( e.g., claustrophobia or inability to lie still for entire imaging time)\n* Ongoing oncological treatment for another cancer\n* History of allergic reactions \u002F hypersensitivity attributed to \\[⁶⁸Ga\\]Ga-FAP-2286.","ALL","18 Years",{"count":19,"type":20},65,"ESTIMATED","INTERVENTIONAL",[23],"PHASE2","This study aims to evaluate the clinical utility of \\[68Ga\\]Ga-FAP-2268 PET\u002FCT for disease staging and assessment in patients with high-risk primary breast cancer. By targeting fibroblast activation protein (FAP), this novel imaging approach may offer improved tumor visualization compared to conventional imaging, which may help improve treatment planning.",[26],"Breast Cancer Detection",[28,29,30,31],"Breast cancer","PET\u002FCT","FAP","FAPI","NOT_YET_RECRUITING","2026-04-08",{"date":35,"type":36},"2026-04-13","ACTUAL",{"date":38,"type":20},"2026-06-01",{"date":40,"type":20},"2029-01",{"name":42,"class":43},"Odense University Hospital","OTHER",{"id":45,"slug":46,"hasResults":11,"nctId":47,"briefTitle":48,"officialTitle":48,"acronym":4,"eligibilityCriteria":49,"healthyVolunteers":50,"sex":51,"minAge":52,"maxAge":53,"enrollmentInfo":54,"targetDuration":4,"studyType":56,"phases":4,"briefSummary":57,"conditions":58,"keywords":66,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":71,"lastUpdatePostDateStruct":72,"startDateStruct":74,"completionDateStruct":76,"leadSponsor":78,"locationsCount":81},"100618429","validation-of-the-oncoliq-test-for-the-early-detection-of-breast-cancer-100618429","NCT07331506","Validation of the Oncoliq Test for the Early Detection of Breast Cancer.","Inclusion Criteria:\n\nGroup 1 - Breast Cancer:\n\nAge between 40 and 70 years Diagnosis of breast cancer at any stage No prior surgical treatment No prior antineoplastic treatment Pathology report available at the time of enrollment Signed informed consent\n\nGroup 2 - No Cancer (Control):\n\nAge between 50 and 70 years No diagnosis or personal history of any type of cancer Digital mammography and breast ultrasound showing no breast pathology (BI-RADS 1 or 2) Signed informed consent\n\nExclusion Criteria:\n\nRefusal to sign the informed consent Communication issues that hinder understanding (hearing loss, blindness, intellectual disability, or dementia) Venipuncture for blood collection impracticable or posing a risk Personal history of previous cancer",true,"FEMALE","40 Years","70 Years",{"count":55,"type":20},300,"OBSERVATIONAL","Cancer continues to be one of the most significant public health issues worldwide. Thanks to early detection, the mortality rate of certain types of cancer has decreased significantly. However, the lack of accessible, low-cost, non-invasive, non-toxic, and easy-to-implement diagnostic methods results in late diagnoses, leading to 1 in every 6 people dying from cancer today.\n\nMicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and are found both inside cells and in bodily fluids such as blood and urine. Several studies have demonstrated their role in human diseases, especially cancer, where tumors release miRNAs into the bloodstream that can be used as biomarkers for early detection.\n\nThe research and development team at Oncoliq SAS identified a panel of miRNAs associated with breast cancer, with a detection performance of 82% sensitivity and 83% specificity, validated in exploratory and preliminary confirmatory studies. These results led to the filing of a patent based on liquid biopsy technology.\n\nThe objective of this protocol is to establish a panel of miRNAs for the early detection of breast cancer using samples from breast cancer patients and a cancer-free control group. Validation of the miRNAs will be carried out through RT-qPCR. This stage constitutes the analytical validation of the biomarkers, with the goal of developing an algorithm capable of classifying individuals with and without breast cancer. In future stages, a pilot clinical trial is planned to evaluate test implementation and clinical validation.",[26,59,60,61,62,63,64,65],"Breast Cancer Early Stage Breast Cancer (Stage 1-3)","Breast Cancer Female","Breast Cancer - Ductal Carcinoma in Situ (DCIS)","Breast Cancer - Infiltrating Ductal Carcinoma","Breast Cancer With Low to Intermediate HER2 Expression","Breast Cancer (Early Breast Cancer)","Breast Cancer - Female",[28,67,68,69],"Detection","Liquid biopsy","miRNAs","RECRUITING","2026-01-13",{"date":73,"type":36},"2026-01-15",{"date":75,"type":36},"2025-10-17",{"date":77,"type":20},"2026-02-28",{"name":79,"class":80},"Oncoliq US Inc","INDUSTRY",1,{"id":83,"slug":84,"hasResults":11,"nctId":85,"briefTitle":86,"officialTitle":87,"acronym":4,"eligibilityCriteria":88,"healthyVolunteers":50,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":89,"targetDuration":91,"studyType":56,"phases":4,"briefSummary":92,"conditions":93,"keywords":98,"overallStatus":70,"whyStopped":4,"lastUpdateSubmitDate":101,"lastUpdatePostDateStruct":102,"startDateStruct":104,"completionDateStruct":106,"leadSponsor":108,"locationsCount":81},"100609461","ucf-mammochat-image-repository-100609461","NCT07214883","UCF MammoChat: Image Repository","UCF MammoChat: An AI-Driven Platform for Personalized Breast Cancer Patient Support -Image Repository","Inclusion Criteria:\n\n* Adults, ages 18 and older\n* Had a radiographic breast cancer imaging test, either for screening or diagnosis of breast cancer, with either positive or negative results performed in a US institution.\n* Have an email account with access to a reliable internet connection or smartphone\n* Pregnant women may choose to participate.\n\nExclusion Criteria:\n\n* Minors , ages under 18\n* Prisoners\n* Adults who are unable to provide consent.",{"count":90,"type":20},20000,"1 Year","This study aims to develop AI models to better read diagnostic mammograms for various populations and types of breast cancer, using the images that participants donate and their responses from study questionnaire to improve patient outcomes. This study also aims to provide mammography images to participants.",[94,95,26,96,60,97],"Breast Cancer","Breast Cancer Awareness","Breast Cancer Survivors","Breast Cancer Diagnosis",[94,99,100],"Artificial Intelligence","AI","2025-10-08",{"date":103,"type":36},"2025-10-09",{"date":105,"type":36},"2025-09-03",{"date":107,"type":20},"2026-06-30",{"name":109,"class":43},"University of Central Florida",{"id":111,"slug":112,"hasResults":11,"nctId":113,"briefTitle":114,"officialTitle":115,"acronym":116,"eligibilityCriteria":117,"healthyVolunteers":11,"sex":51,"minAge":118,"maxAge":53,"enrollmentInfo":119,"targetDuration":4,"studyType":21,"phases":121,"briefSummary":123,"conditions":124,"keywords":127,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":133,"lastUpdatePostDateStruct":134,"startDateStruct":136,"completionDateStruct":138,"leadSponsor":140,"locationsCount":4},"100608724","ai-based-self-supervised-learning-model-using-non-contrast-breast-mri-for-early-screening-and-clinical-utility-evaluation-100608724","NCT07205276","AI-Based Self-Supervised Learning Model Using Non-Contrast Breast MRI for Early Screening and Clinical Utility Evaluation","Construction of an Early Breast Cancer Screening Warning Model Based on Self-supervised Learning With Plain MRI Scans and Prospective Clinical Utility Evaluation","B-MRI-AI","* Inclusion Criteria:\n\n  1. Female, age 30-70 years\n  2. Completed breast MRI scan, including at least T2WI, DWI, and ADC sequences\n  3. Multimodal data acquired within the same time window (≤90 days)\n  4. A clear clinical outcome: pathologically confirmed or ≥12-24 months of negative follow-up\n  5. The time window between imaging examination and outcome determination was ≤90 days\n  6. Signed informed consent\n* Exclusion Criteria:\n\n  1. Absolute contraindications to MRI (pacemaker, cochlear implant, ocular metal foreign body, etc.)\n  2. Pregnant or lactating women\n  3. Recent history of breast surgery\u002Fradiotherapy (≤6 months) or imaging after neoadjuvant therapy\n  4. Substandard image quality (severe motion artifact, signal-to-noise ratio below threshold)\n  5. Incomplete clinical data or time window exceeded\n  6. Known breast cancer metastasis or recurrence","30 Years",{"count":120,"type":20},30000,[122],"NA","Breast cancer is the most common malignant disease among women worldwide, with rising incidence and younger age at onset in China. Early detection is critical for improving survival, yet current screening methods such as mammography and ultrasound show limited sensitivity in Chinese women, particularly those with dense breast tissue. Contrast-enhanced MRI offers higher diagnostic performance but its use is limited by high costs, safety concerns with gadolinium-based contrast agents, and limited accessibility.\n\nThis investigator-initiated trial aims to evaluate the clinical application of non-contrast multiparametric MRI, combined with advanced artificial intelligence algorithms, for the early detection and diagnosis of breast cancer. The study will collect MRI imaging data from multiple centers and integrate radiomic features across T2-weighted imaging, diffusion-weighted imaging, and apparent diffusion coefficient maps. A deep learning-based model will be developed and validated to improve lesion detection, differential diagnosis, and risk stratification.\n\nThe ultimate goal of this project is to establish a safe, accurate, and scalable breast cancer screening pathway suitable for Chinese women. By reducing dependence on invasive procedures and contrast agents, and by leveraging AI for standardization and efficiency, this approach may significantly improve early detection rates and contribute to better patient outcomes.",[26,125,126],"Early Detection of Cancer","AI (Artificial Intelligence)",[128,129,130,131,132],"Breast MRI","Non-contrast MRI","Radiomics","Deep Learning","Breast Cancer Screening","2025-09-25",{"date":135,"type":36},"2025-10-03",{"date":137,"type":20},"2025-10-01",{"date":139,"type":20},"2027-12-01",{"name":141,"class":43},"Second Affiliated Hospital, School of Medicine, Zhejiang University",{"id":143,"slug":144,"hasResults":11,"nctId":145,"briefTitle":146,"officialTitle":147,"acronym":148,"eligibilityCriteria":149,"healthyVolunteers":11,"sex":51,"minAge":150,"maxAge":4,"enrollmentInfo":151,"targetDuration":4,"studyType":21,"phases":153,"briefSummary":154,"conditions":155,"keywords":160,"overallStatus":32,"whyStopped":4,"lastUpdateSubmitDate":170,"lastUpdatePostDateStruct":171,"startDateStruct":173,"completionDateStruct":175,"leadSponsor":177,"locationsCount":81},"100601760","molecular-breast-imaging-mbi-guided-biopsy-100601760","NCT07114679","Molecular Breast Imaging (MBI)-Guided Biopsy","Molecular Breast Imaging (MBI)-Guided Biopsy Pilot SBIR","MBI-GB-Pilot","Inclusion Criteria:\n\n* dense breasts (BI-RADS C or D) on screening DBT\n\nExclusion Criteria:\n\n* pregnancy","21 Years",{"count":152,"type":20},250,[122],"The goal of this pilot clinical trial is to demonstrate supplemental screening MBI (molecular breast imaging) in women with dense breasts. The main questions it aims to answer are:\n\n* Does screening MBI find more cancer than screening DBT (3D mammography, digital breast tomosynthesis?\n* Does screening MBI result in more call-backs for biopsy than DBT?\n* How well does MBI-guided biopsy conform with pathology reports?\n\nResearchers will compare screening MBI to screening DBT to see if MBI is more sensitive to detecting cancer in women with dense breasts.\n\nParticipants will\n\n* Receive both screening DBT and screening MBI\n* Receive either DBT-guided or MBI-guided biopsy (randomly assigned), if required by the screening images",[26,156,157,158,159],"Breast Neoplasm","Molecular Imaging","Biopsy","Dense Breasts",[161,162,163,164,165,166,167,168,169],"screening","crossover","single-group","pilot","biopsy","randomized assignment","dense breasts","MBI","molecular imaging","2025-08-03",{"date":172,"type":36},"2025-08-11",{"date":174,"type":20},"2027-06",{"date":176,"type":20},"2028-06",{"name":178,"class":80},"Smart Breast Corp."]