Evaluating a Text-Prompt AI Assistant for Chest CT Scans (AI-REPORT Study)

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorShanghai Zhongshan Hospital

About this trial

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 criteria

Qualifiers

Active board certification and ongoing routine clinical practice as an attending radiologist

Independent institutional authority for chest CT image interpretation and final official diagnostic report issuance

A minimum of three years of post-certification clinical experience in specialized thoracic imaging

Legal and cognitive competence for study participation, with voluntary provision of written informed consent after full understanding of study purpose, procedures, risks and benefits

Disqualifiers

Direct participation in the development, training or validation of the trial's evaluated AI system

Ongoing participation in concurrent studies with potential risks of interpretation bias, cognitive fatigue or study procedure interference (investigator-assessed)

Any actual or perceived conflict of interest related to the evaluated AI system or its developers that may compromise objectivity in image interpretation and diagnostic reporting

Trial design

Treatments tested in this trial

  • AI-generated report for chest CT
  • Standard reporting procedure (no AI assistance)

Treatment groups

100 Participants
are divided into 2 treatment groups

Sponsors and collaborators

Shanghai Zhongshan Hospital

Lead sponsor

Shanghai Geriatric Medical Center

Collaborator

Yangzhou No.1 People's Hospital

Collaborator

The Affiliated Hospital of Xuzhou Medical University

Collaborator

Affiliated Hospital of Jiangsu University

Collaborator

Dushu Lake Hospital Affiliated to Soochow University

Collaborator

China-Japan Union Hospital, Jilin University

Collaborator

Xiangya Hospital of Central South University

Collaborator

Lanzhou University Second Hospital

Collaborator

First Affiliated Hospital of Xinjiang Medical University

Collaborator

Peking University Cancer Hospital & Institute

Collaborator

Zhongshan Hospital (Xiamen), Fudan University

Collaborator

First People's Hospital of Kunming

Collaborator

Shanghai Minhang Central Hospital

Collaborator

Shanghai United Imaging Intelligence Ltd.

Collaborator