X-ray Assisted Diagnostic System

March 22, 2026 updated by: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial

X-ray examination is one of the most commonly used imaging modalities, especially chest X-ray, which is routinely performed for hospitalized patients. However, due to the low density resolution of X-ray images, radiologists' ability to diagnose diseases-particularly small lesions-is often affected. Studies have shown that the diagnostic accuracy of radiologists using chest X-rays is only around 70%, which does not meet clinical demands.

Based on this, we developed an artificial intelligence model to assist radiologists in interpreting X-ray images and generating reports, with the aim of improving diagnostic accuracy and reducing interpretation time.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

16000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
      • Zhengzhou, China
        • The First Affiliated Hospital of Zhengzhou University
        • Contact:
    • Hubei
      • Wuhan, Hubei, China, 430022
        • Wuhan Union Hospital
        • Contact:
      • Wuhan, Hubei, China, 430022
      • Wuhan, Hubei, China, 430022
        • Wuhan Union Jinyin Lake Hospital
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Probability Sample

Study Population

Patients scheduled to undergo X-ray examination

Description

Inclusion Criteria:

  • Clinically suspected thoracic diseases (such as pneumonia, tuberculosis, or lung cancer) requiring X-ray diagnosis；
  • Patients providing written informed consent for research data use；
  • Complete clinical records (including chief complaints, medical history, and laboratory test results)

Exclusion Criteria:

  • Substandard X-ray image quality (including severe motion artifacts, over-/underexposure, or missing anatomical structures)
  • Pregnant or lactating women

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
Diagnostic test: Radiologist diagnostic group
After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis.
AI-assisted radiologist diagnostic group
After the patient undergoes an X-ray examination, an AI-assisted radiologist generates the report and makes the diagnosis.
Diagnostic test: AI-assisted radiologist diagnostic group
Based on the previously developed X-ray image diagnosis and report generation model, radiologists are assisted in interpreting X-ray images and generating reports.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Area Under the Curve
Time Frame: From enrollment to the end of X-ray image acquisition at 1 week
The primary outcome was the AUC to evaluate diagnostic performance, comparing radiologists with and without AI assistance.
From enrollment to the end of X-ray image acquisition at 1 week

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
X-ray report generation time
Time Frame: From enrollment to the end of X-ray image acquisition at 1 week
X-ray report generation time refers to the amount of time required to produce a diagnostic report after an X-ray examination has been performed. It typically measures the interval from when the X-ray images are acquired to when the radiologist (with or without AI assistance) completes and finalizes the report.
From enrollment to the end of X-ray image acquisition at 1 week

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Radiologist score
Time Frame: From enrollment to the end of X-ray image acquisition at 4 weeks
Radiologist score refers to the evaluation or rating assigned by senior radiologists based on imaging findings generated by AI or AI+radiologist.
From enrollment to the end of X-ray image acquisition at 4 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

May 1, 2026

Primary Completion (Estimated)

October 31, 2026

Study Completion (Estimated)

November 30, 2026

Study Registration Dates

First Submitted

March 22, 2026

First Submitted That Met QC Criteria

March 22, 2026

First Posted (Actual)

March 27, 2026

Study Record Updates

Last Update Posted (Actual)

March 27, 2026

Last Update Submitted That Met QC Criteria

March 22, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • X-Ray-001

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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