[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100655219":3},{"organization":4,"outcomesModule":7,"designInfo":37,"detailedDescription":43,"studyPopulation":11,"armGroups":44,"interventions":51,"overallOfficials":57,"centralContacts":61,"locations":11,"responsibleParty":67,"collaborators":11,"id":69,"slug":70,"hasResults":71,"nctId":72,"briefTitle":73,"officialTitle":74,"acronym":11,"eligibilityCriteria":75,"healthyVolunteers":76,"sex":77,"minAge":78,"maxAge":79,"enrollmentInfo":80,"targetDuration":11,"studyType":83,"phases":84,"briefSummary":85,"conditions":86,"keywords":88,"overallStatus":95,"whyStopped":11,"lastUpdateSubmitDate":96,"lastUpdatePostDateStruct":97,"startDateStruct":100,"completionDateStruct":102,"leadSponsor":104,"locationsCount":11},{"fullName":5,"class":6},"The First Affiliated Hospital with Nanjing Medical University","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":18,"otherOutcomes":11},[9,13,16],{"measure":10,"description":11,"timeFrame":12},"Incremental Breast Cancer Detection Rate of CT-AI",null,"Within 3 months after the index health examination",{"measure":14,"description":11,"timeFrame":15},"Sensitivity of CT-AI for Breast Cancer Detection in the Retrospective Cohort","Up to 12 months of retrospective outcome ascertainment",{"measure":17,"description":11,"timeFrame":12},"Overall Breast Cancer Detection Rate of Combined CT-AI and Breast Ultrasound Screening",[19,23,26,28,31,34],{"measure":20,"description":21,"timeFrame":22},"Specificity of CT-AI","Specificity of the fixed CT-AI model for breast cancer detection, using final breast cancer status based on pathology and\u002For clinical follow-up as the reference standard. Unit of measure: percentage (%).","Up to 24 months after the index health examination",{"measure":24,"description":25,"timeFrame":12},"Positive Predictive Value of CT-AI-Assisted Recall","Proportion of participants recalled following CT-AI-assisted physician review who are subsequently confirmed to have breast cancer. Unit of measure: percentage (%).",{"measure":27,"description":11,"timeFrame":12},"Proportion of Early-Stage Breast Cancers Detected",{"measure":29,"description":30,"timeFrame":12},"Physician Recall Rate","Proportion of participants for whom the reviewing physician recommends additional breast evaluation after CT-AI-assisted review. Unit of measure: percentage (%).",{"measure":32,"description":33,"timeFrame":12},"Breast Biopsy Rate","Proportion of participants who undergo breast biopsy following the index screening episode. Unit of measure: percentage (%).",{"measure":35,"description":36,"timeFrame":22},"24-Month Interval Breast Cancer Rate","Number of breast cancers diagnosed during follow-up after the index screening episode among participants without breast cancer detected at the initial screening assessment, reported per 1,000 participants.",{"allocation":38,"interventionModel":39,"interventionModelDescription":11,"primaryPurpose":40,"observationalModel":11,"timePerspective":11,"maskingInfo":41},"NA","SINGLE_GROUP","SCREENING",{"masking":42,"maskingDescription":11,"whoMasked":11},"NONE","Retrospective phase: Historical health examination data will be used for offline validation of the locked CT-AI model.\n\nProspective phase: Eligible women undergoing routine health examination will be consecutively enrolled. Participants receive routine chest CT and breast ultrasound. After routine reports are completed and locked, AI analysis is performed. Cases exceeding predefined thresholds are reviewed by clinicians who determine recall decisions. The study evaluates incremental detection value, recall workflow, safety and feasibility.",[45],{"label":46,"type":47,"description":48,"interventionNames":49},"AI-Assisted Screening Group","EXPERIMENTAL","Participants undergo routine health examination, including breast ultrasound and non-contrast chest CT when clinically scheduled. No additional chest CT is performed for study purposes. After routine breast ultrasound and chest CT reports are completed and locked, a fixed CT-AI model analyzes the existing chest CT images. Participants meeting predefined AI criteria are reviewed by trained physicians, who make the final decision regarding whether additional breast evaluation is recommended. Further imaging, biopsy, or treatment is determined according to routine clinical practice and participant preference.",[50],"Device: CT-AI-assisted breast cancer screening",[52],{"type":53,"name":54,"description":55,"armGroupLabels":56,"otherNames":11},"DEVICE","CT-AI-assisted breast cancer screening","A fixed artificial intelligence model is applied to existing non-contrast chest CT images obtained during routine health examinations to identify and localize suspicious breast lesions and generate a breast cancer risk score and risk category. No additional CT examination is performed for study purposes. Participants meeting predefined AI review criteria are evaluated by trained physicians, who review the original CT images together with the AI output and make the final decision regarding whether additional breast evaluation is recommended. The AI system does not independently diagnose breast cancer or automatically recall participants. Subsequent imaging, biopsy, or treatment is determined according to routine clinical practice and participant preference.",[46],[58],{"name":59,"affiliation":5,"role":60},"Qiang Ding","PRINCIPAL_INVESTIGATOR",[62],{"name":63,"role":64,"phone":65,"phoneExt":11,"email":66},"Ge Ma, doctor","CONTACT","+8618262632870","ntmage@sina.com",{"type":68,"investigatorFullName":11,"investigatorTitle":11,"investigatorAffiliation":11,"oldNameTitle":11,"oldOrganization":11},"SPONSOR","100655219","ct-ai-breast-cancer-opportunistic-screening-health-examination-study-100655219",false,"NCT07809698","CT-AI Breast Cancer Opportunistic Screening Health Examination Study","AI-Assisted Opportunistic Breast Cancer Screening Using Non-contrast Chest CT in Women Undergoing Health Examination: A Retrospective Validation and Prospective Single-Arm Interventional Study","Inclusion Criteria:\n\n* Female participants aged 18 to 80 years.\n* Undergoing routine health examination.\n* For the prospective phase, no clear ongoing breast-related symptoms at baseline.\n* Availability of complete non-contrast chest CT images. In the prospective phase, chest CT must have been scheduled as part of the routine health examination or for another established clinical purpose and must not be performed solely for this study.\n* Availability of a contemporaneous routine breast ultrasound report and relevant clinical information.\n* Chest CT image quality adequate for AI analysis.\n* Availability of an appropriate follow-up pathway through hospital records, pathology systems, cancer registry data, or approved follow-up methods.\n* For the prospective phase, study information has been provided through an ethics-approved process and the participant has not actively opted out.\n\nExclusion Criteria:\n\n* Previous diagnosis of breast cancer, prior treatment for breast malignancy, or breast malignancy already confirmed before baseline.\n* Pregnancy or breastfeeding.\n* Incomplete breast coverage on chest CT, severe image artifacts, missing images, or other conditions that prevent valid AI analysis.\n* Critical baseline or outcome data are substantially incomplete and cannot reasonably be recovered.\n* No effective follow-up pathway can be established.\n* For the prospective phase, the participant actively opts out before AI analysis or explicitly declines use of imaging and clinical data for this study.",true,"FEMALE","18 Years","80 Years",{"count":81,"type":82},30000,"ESTIMATED","INTERVENTIONAL",[38],"This study evaluates the clinical utility of a locked chest CT artificial intelligence model for opportunistic breast cancer screening among women undergoing health examinations. The study includes a retrospective validation phase and a prospective single-arm implementation phase. AI analyzes existing non-contrast chest CT images without additional CT examinations. Clinical physicians make further evaluation decisions based on AI outputs, imaging findings, ultrasound results and clinical information.",[87],"Breast Neoplasms",[89,90,91,92,93,94],"Artificial Intelligence","Breast Cancer Screening","Opportunistic Screening","Non-contrast Chest CT","Breast Ultrasound","Health Examination","NOT_YET_RECRUITING","2026-09-02",{"date":98,"type":99},"2026-09-09","ACTUAL",{"date":101,"type":82},"2026-09-01",{"date":103,"type":82},"2030-02-28",{"name":5,"class":6}]