Using a language model to read PSMA PET/CT scan reports in prostate cancer
Tests a language model that reads scan reports to stage prostate cancer.
Plain-language title generated from the registry record
Registry title: Large Language Model-Assisted cTNM Annotation From Chinese PSMA PET/CT Reports
Key facts
- Where
- Wenzhou, ChinaSee the site
Where in China
- The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou, ChinaTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- First Affiliated Hospital of Wenzhou Medical University
- Trial code
- NCT07707232
- Record updated
- 21 July 2026
- Original description
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/CT 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.Read full original descriptionShow less
Large Language Model-Assisted Imaging cTNM Staging Annotation and Uncertainty Recognition for Prostate Cancer Based on Chinese PSMA PET/CT Reports
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/CT 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.
The 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/CT reports. A human-AI comparison will also be performed using physicians from urology and imaging-related specialties with different seniority levels.
Inclusion: Male patients aged 18 years or older; Patients with clinically diagnosed, pathologically diagnosed, or clinically suspected prostate cancer; Patients who underwent PSMA PET/CT for initial staging, recurrence assessment, treatment response evaluation, metastatic assessment, or other clinical purposes during routine care; Complete or basically complete Chinese PSMA PET/CT report text is available, including imaging findings and/or diagnostic impression; 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; The research data can be de-identified and replaced by a study identification number before analysis.
Exclusion: PSMA PET/CT reports unrelated to prostate cancer, or reports clearly irrelevant to the research task; Reports with severely missing, unreadable, or unavailable main text, imaging findings, or diagnostic impression; Reports that cannot be adequately de-identified or contain residual direct personal identifiers that cannot be safely removed; Duplicate records, repeated exports of the same examination, or records for which the unique report version cannot be confirmed; Reports judged by the research team to be of insufficient quality for manual annotation, model evaluation, or statistical analysis.