AI boosts radiologist speed in reading chest scans
NCT ID NCT07640906
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looks at whether an AI tool can help radiologists (doctors who read chest CT scans) write their reports faster without sacrificing quality. About 75 radiologists from several hospitals will use the AI as part of their normal work. Researchers will compare report time and quality before and after the AI tool is introduced.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
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About 75 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
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Jun 2026
An estimate. Start dates often move.
- Expected to finish
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Dec 2026
An estimate. End dates often move.
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
The study population is defined as follows: 1. Radiologists: Attending radiologists who routinely interpret chest CT scans as part of their clinical duties at the participating medical centers. 2. Chest CT Scans: Clinically indicated, non-contrast chest CT examinations acquired from the patient populations served by the participating centers. The scans are stratified into two groups based on the date of acquisition: before and after the implementation of the AI reporting system.
- Ages
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18 years and older
- Sex
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Anyone
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
The study participants include both the radiologists whose performance is evaluated and the chest CT scans they interpret. Eligibility criteria are defined for both. 1\. Inclusion Criteria 1.1 For Radiologists 1. Board-certified radiologists specializing in or routinely performing thoracic imaging. 2. Employed at one of the participating study centers for the entire duration of both the without-AI and with-AI study periods. 3. Interpreted a minimum of eligible chest CT scans (e.g., \> 50 scans) during both the without-AI and with-AI data collection periods. 1.2 For Chest CT Scans 1. Non-contrast chest CT examinations performed for any clinical indication. 2. Scans completed and finalized during the defined with-AI or without-AI study periods. 3. Patient age 18 years or older at the time of the scan. 2\. Exclusion Criteria 2.1 For Radiologists: 1. Radiologists who joined, left, or were on extended leave (e.g., \>4 weeks) from the participating center between the with-AI and without-AI study periods. 2. Radiologists who interpreted fewer than the minimum required number of eligible scans in either study period. 3. Radiologists who voluntarily decline to have their de-identified performance data included in the study analysis. 4. Radiologists who decline to provide demographic or occupational information (e.g., years of professional experience or sex)-variables that may serve as potential confounders-will be excluded from adjusted and stratified analyses that require such covariates. 2.2 For Chest CT Scans 1. CT scans of pediatric patients (age \< 18 years). 2. Contrast-enhanced chest CT studies. 3. Studies performed for specific procedural guidance (e.g., biopsy, ablation). 4. Studies deemed technically inadequate for primary interpretation by radiologist (e.g., severe motion artifact, incomplete study). 5. Studies for which the AI system fails to generate a valid preliminary report draft. This includes possible system failures, algorithm errors, or cases where the generated draft is deemed technically unusable (e.g., empty, garbled, or based on critically flawed image analysis). 6. The lack of relevant information (diagnosis, clinical scenario, etc.). Chest CT data will be excluded from corresponding analyses if the required information, which is necessary for confounding control, subgroup analyses, or other pre-specified analyses, is unavailable. Such scenarios include data that cannot be retrospectively retrieved, incompletely recorded, or restricted due to ethical or institutional requirements.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
2 sites. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai
Shanghai, China
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United Imaging Intelligence, Shanghai, Shanghai
Shanghai, China
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