Large Language Model helps annotate cTNM from PSMA PET/CT reports in prostate cancer

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This multicenter observational study develops and validates a local large language model–assisted workflow to annotate cTNM staging and identify uncertainty in Chinese PSMA PET/CT report texts. It uses de-identified routine-care reports and only basic clinical information, with no new procedures or follow-up required. The project includes retrospective annotation of about 4,000 reports, internal and external validation sets, and a prospective validation of 100 consecutive reports to measure diagnostic accuracy against expert reference standards. A human–AI comparison will be conducted to evaluate performance in real-world reporting contexts. The work focuses on improving consistency and transparency in imaging-based staging for prostate cancer without altering patient care.

Why it matters

Who can join: the full rules

Inclusion Criteria:

1. Male patients aged 18 years or older.
2. Patients with clinically diagnosed, pathologically diagnosed, or clinically suspected prostate cancer.
3. Patients who underwent PSMA PET/CT for initial staging, recurrence assessment, treatment response evaluation, metastatic assessment, or other clinical purposes during routine care.
4. Complete or basically complete Chinese PSMA PET/CT report text is available, including imaging findings and/or diagnostic impression.
5. 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.
6. The research data can be de-identified and replaced by a study identification number before analysis.

Exclusion Criteria:

1. PSMA PET/CT reports unrelated to prostate cancer, or reports clearly irrelevant to the research task.
2. Reports with severely missing, unreadable, or unavailable main text, imaging findings, or diagnostic impression.
3. Reports that cannot be adequately de-identified or contain residual direct personal identifiers that cannot be safely removed.
4. Duplicate records, repeated exports of the same examination, or records for which the unique report version cannot be confirmed.
5. Reports judged by the research team to be of insufficient quality for manual annotation, model evaluation, or statistical analysis.

Where it's running

• The First Affiliated Hospital of Wenzhou Medical University
  Wenzhou, Zhejiang, China Recruiting

Study contacts

• Study coordinator: Qi Lin
• Email: devillynch@126.com
• Phone: +86 15205771010

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.