Evaluating a Text-Prompt AI Assistant for Chest CT Scans (AI-REPORT Study)
ConditionThoracic Diseases
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
This trial accepts healthy volunteersQualifiers
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
Design model
Crossover
Treatments tested in this trial
AI-generated report for chest CT
DeviceA clinical decision support software generates a preliminary report draft for chest CT examinations. Board-certified radiologists then finalize the AI draft.
Standard reporting procedure (no AI assistance)
Procedure/SurgeryStandard 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.
Treatment groups
100 Participants
are divided into 2 treatment groupsGroup A: AI-Assisted Reporting ArmExperimental treatment 1 intervention
Group B: Standard ReportingActive comparator 1 intervention
Trial outcomes
Primary outcomes
1
Subjective report quality evaluation based on diagnostic requirements and clinical relevance
Quality is blindly assessed by independent clinicians using pairwise comparisons among three report types: AI-generated raw reports, human-only reports, and human-AI collaborative reports. Superior reports score 1 point, ties score 0.5.
Time frame
CT reports will be distributed for external clinician scoring once all required data are available (typically ≤ 2 weeks post Primary Completion Date); the final aggregated analysis will be completed within 4 weeks post Primary Completion Date.2
Significance of radiologist modifications to AI-generated reports
Using a 5-point ordinal scale, independent external clinicians rate the clinical significance of edits made to AI reports. Level 1 denotes minimal changes; Level 5 indicates critical corrections preventing inappropriate/delayed management. Intermediate levels (2-4) represent minor adjustments, beneficial optimizations, and significant refinements impacting diagnostic clarity or treatment selection.
Time frame
CT reports will be distributed for external clinician scoring once all required data are available (typically ≤ 2 weeks post Primary Completion Date); the final aggregated analysis will be completed within 4 weeks post Primary Completion Date.Sponsors and contacts
Click on the lead sponsor to view all of their trials.
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
Source ClinicalTrials.gov