Large Language Model-Assisted cTNM Annotation From Chinese PSMA PET/CT Reports

Recruiting now

Conditions studied: Prostate Cancer

In brief

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.

Key facts

Study ID
NCT07707232
Run by
First Affiliated Hospital of Wenzhou Medical University
People needed
4600
Starts
2026-06-17
Expected to finish
2027-12-31
Last updated by the study team
2026-07-21

Who can join

Age: 18 and older. Sex: male. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.