Automated Reports Generation of Cardiovascular Magnetic Resonance Imaging
Multi-step Automated Report Generation of Cardiovascular Magnetic Resonance Imaging Based on Visual Large Language Model
The goal of this observational study is to evaluate the accuracy, completeness, and clinical consistency of large language model-generated cardiac magnetic resonance (CMR) imaging reports compared with expert radiologist reports in patients undergoing routine clinical CMR examinations.
The main question(s) it aims to answer are:
Can automatically generated CMR reports produced by a large multimodal model accurately reflect key imaging findings and diagnoses when compared with reports written by experienced cardiovascular radiologists?
How does the quality of generated reports perform in terms of clinical correctness, completeness, and linguistic clarity, as assessed by quantitative metrics and expert review?
If there is a comparison group:
Researchers will compare AI-generated CMR reports with ground-truth reports authored by board-certified cardiovascular radiologists to see if the automated system achieves comparable diagnostic accuracy and report quality across different cardiac pathologies.
Participants will:
Undergo standard-of-care cardiac MRI examinations as part of routine clinical practice.
Have their anonymized CMR image data and corresponding radiologist reports retrospectively collected.
Contribute data that will be used to generate automated CMR reports, which will then be evaluated against expert reports using objective metrics (e.g., diagnostic agreement, entity-level accuracy) and subjective clinical scoring by radiologists.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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Beijing Municipality
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Beijing, Beijing Municipality, China, 100037
- Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
The study population consists of patients who underwent routine, clinically indicated cardiac magnetic resonance (CMR) examinations at a medical center,represents a real-world clinical population undergoing cardiac MRI for diagnostic evaluation of various cardiovascular diseases.
All CMR studies included in this observational study are retrospectively collected, fully de-identified, and accompanied by corresponding radiologist-authored clinical reports. The study population represents a real-world clinical cohort with a range of cardiac conditions commonly evaluated by CMR.
Description
Inclusion Criteria:
- Patients who underwent clinically indicated cardiac magnetic resonance (CMR) examinations.
- Availability of complete and de-identified CMR image data.
- Availability of corresponding clinical CMR reports authored by experienced cardiovascular radiologists.
- CMR studies acquired using standard clinical imaging protocols.
Exclusion Criteria:
- Incomplete or corrupted CMR image data.
- Absence of a reference radiologist report.
- Poor image quality that precludes reliable clinical interpretation.
- CMR studies with severe imaging artifacts affecting diagnostic evaluation.
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic Accuracy of AI-Generated Cardiac MRI Reports
Time Frame: Baseline
|
The primary outcome is the diagnostic accuracy of automatically generated cardiac magnetic resonance (CMR) reports produced by a large multimodal model. Diagnostic accuracy is assessed by comparing AI-generated reports with reference reports written by board-certified cardiovascular radiologists. Agreement is evaluated at the level of key clinical findings and final imaging impressions, using predefined criteria. Accuracy metrics include correctness of major diagnoses and presence or absence of clinically relevant imaging findings. |
Baseline
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- CMR_AutoReport
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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