[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100647302":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":10,"centralContacts":19,"locations":29,"responsibleParty":46,"collaborators":10,"id":50,"slug":51,"hasResults":52,"nctId":53,"briefTitle":54,"officialTitle":55,"acronym":56,"eligibilityCriteria":57,"healthyVolunteers":52,"sex":58,"minAge":59,"maxAge":10,"enrollmentInfo":60,"targetDuration":10,"studyType":63,"phases":10,"briefSummary":64,"conditions":65,"keywords":67,"overallStatus":32,"whyStopped":10,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":79,"completionDateStruct":81,"leadSponsor":83,"locationsCount":84},{"fullName":5,"class":6},"First Affiliated Hospital of Wenzhou Medical University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"PSMA PET\u002FCT Report Text Validation Cohort",null,"Patients with prostate cancer or suspected prostate cancer who underwent PSMA PET\u002FCT as part of routine clinical care. De-identified Chinese PSMA PET\u002FCT report texts and necessary baseline information will be used for manual annotation, large language model-assisted imaging cTNM staging annotation, uncertainty recognition, internal validation, external validation, prospective validation, and human-AI comparison. No additional examination, treatment, or follow-up will be assigned for this study.",[13],"Other: Large Language Model-Assisted Report Annotation",[15],{"type":6,"name":16,"description":17,"armGroupLabels":18,"otherNames":10},"Large Language Model-Assisted Report Annotation","A locally or institutionally controlled large language model workflow will analyze de-identified Chinese PSMA PET\u002FCT report texts and generate structured outputs for report-derived imaging cTNM staging annotation, uncertainty recognition, and supporting evidence extraction. This workflow is used only for research evaluation and methodological analysis. It will not assign any examination, treatment, medication, procedure, or follow-up to participants, and it will not guide clinical diagnosis or treatment decisions.",[9],[20,25],{"name":21,"role":22,"phone":23,"phoneExt":10,"email":24},"Qi Lin","CONTACT","+86 15205771010","devillynch@126.com",{"name":26,"role":22,"phone":27,"phoneExt":10,"email":28},"Yikai Chen","+86 13857730804","chenyikai@wzhospital.cn",[30],{"facility":31,"status":32,"city":33,"state":34,"zip":10,"country":35,"countryCode":36,"cosmosGeoPoint":37,"geoPoint":42,"contacts":43},"The First Affiliated Hospital of Wenzhou Medical University","RECRUITING","Wenzhou","Zhejiang","China","CN",{"type":38,"coordinates":39},"Point",[40,41],120.66682,27.99942,{"lat":41,"lon":40},[44,45],{"name":21,"role":22,"phone":23,"phoneExt":10,"email":24},{"name":26,"role":22,"phone":27,"phoneExt":10,"email":28},{"type":47,"investigatorFullName":48,"investigatorTitle":49,"investigatorAffiliation":5,"oldNameTitle":10,"oldOrganization":10},"PRINCIPAL_INVESTIGATOR","Qi Lin, MD","Principal Investigator","100647302","large-language-model-assisted-ctnm-annotation-from-chinese-psma-petct-reports-100647302",false,"NCT07707232","Large Language Model-Assisted cTNM Annotation From Chinese PSMA PET\u002FCT Reports","Large Language Model-Assisted Imaging cTNM Staging Annotation and Uncertainty Recognition for Prostate Cancer Based on Chinese PSMA PET\u002FCT Reports","PSMA-LLM-cTNM","Inclusion Criteria:\n\n1. Male patients aged 18 years or older.\n2. Patients with clinically diagnosed, pathologically diagnosed, or clinically suspected prostate cancer.\n3. Patients who underwent PSMA PET\u002FCT for initial staging, recurrence assessment, treatment response evaluation, metastatic assessment, or other clinical purposes during routine care.\n4. Complete or basically complete Chinese PSMA PET\u002FCT report text is available, including imaging findings and\u002For diagnostic impression.\n5. The report text contains information that can be used to evaluate at least one target field, such as local prostate lesion, regional lymph nodes, non-regional lymph nodes, bone metastasis, visceral metastasis, or uncertainty expressions.\n6. The research data can be de-identified and replaced by a study identification number before analysis.\n\nExclusion Criteria:\n\n1. PSMA PET\u002FCT reports unrelated to prostate cancer, or reports clearly irrelevant to the research task.\n2. Reports with severely missing, unreadable, or unavailable main text, imaging findings, or diagnostic impression.\n3. Reports that cannot be adequately de-identified or contain residual direct personal identifiers that cannot be safely removed.\n4. Duplicate records, repeated exports of the same examination, or records for which the unique report version cannot be confirmed.\n5. Reports judged by the research team to be of insufficient quality for manual annotation, model evaluation, or statistical analysis.","MALE","18 Years",{"count":61,"type":62},4600,"ESTIMATED","OBSERVATIONAL","This observational study will develop and validate a large language model-assisted workflow for imaging cTNM staging annotation and uncertainty recognition in prostate cancer using Chinese PSMA PET\u002FCT report texts generated during routine clinical care. The study will use de-identified report texts and necessary baseline clinical information only. No additional imaging examination, blood test, treatment, or follow-up visit will be assigned for this study.\n\nThe main objective is to evaluate whether a locally or institutionally controlled large language model can identify report-derived imaging cT, cN, and cM categories, extract supporting evidence from the original report, and recognize uncertainty expressions. Model performance will be assessed using an internal independent validation set, external validation reports from two collaborating hospitals, and a prospective validation set of 100 consecutive routine PSMA PET\u002FCT reports. A human-AI comparison will also be performed using physicians from urology and imaging-related specialties with different seniority levels.",[66],"Prostate Cancer",[68,69,70,71,72,73,74],"PSMA PET\u002FCT","Large Language Model","Artificial Intelligence","cTNM Staging","Uncertainty Recognition","Natural Language Processing","Medical Imaging Report","2026-07-20",{"date":77,"type":78},"2026-07-21","ACTUAL",{"date":80,"type":78},"2026-06-17",{"date":82,"type":62},"2027-12-31",{"name":5,"class":6},1]