Evaluating a Text-Prompt AI Assistant for Chest CT Scans (AI-REPORT Study)
An Evaluation Study of a Text-Based Chest CT-Assisted Diagnostic System: A Two-stage, Multicenter, Multireader Multicase (MRMC), Self-Crossover Controlled Trial
Shanghai Zhongshan Hospital
100 participants
Jun 20, 2026
INTERVENTIONAL
Conditions
Summary
This study aims to find out if an artificial intelligence (AI) system can help experienced radiologists write chest CT scan reports more quickly without lowering the quality of the report. Chest CT scans are common, and writing reports for them is a major part of a radiologist's job. In this trial, board-certified radiologists will interpret complex chest CT cases. For some cases, they will start with a complete draft report generated by the AI system, which they can review and edit as needed. For other cases, they will write the report from scratch without any AI help, following their usual routine. The main things we are measuring are: 1) how much time the AI draft saves, and 2) whether the final reports created with AI help are as good as or better than those written without it, as judged by other senior doctors who do not know which report came from which method. The hope is that this AI tool can make radiologists' work more efficient while maintaining high standards for patient care.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
A clinical decision support software generates a preliminary report draft for chest CT examinations. Board-certified radiologists then finalize the AI draft.
Standard chest CT reporting procedure without AI assistance. Board-certified radiologists independently interpret chest CT examinations and generate final reports following standard clinical workflow without preliminary AI-generated drafts.
Locations(2)
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NCT07634861