HCM - Hypertrophic CardiomyopathyNCT07340762
Automated Reports Generation of Cardiovascular Magnetic Resonance Imaging
An observational study of HCM - Hypertrophic Cardiomyopathy, run by Chinese Academy of Medical Sciences, Fuwai Hospital at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- HCM - Hypertrophic Cardiomyopathy
- What is being tested?
- large lanuage model
- How many people
- 20,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Oct 2025to 1 Jan 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
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.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
China1 site
Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College
Beijing, Beijing Municipality, 100037
About this study
Official title: 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:
Read more
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.
- Conditions
- HCM - Hypertrophic Cardiomyopathy
- Being tested
- large lanuage model
- Medical subject headings
- Cardiomyopathy, Hypertrophic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
large lanuage modelOther
The intervention consists of an automated CMR report generation system based on a large multimodal deep learning model.
The model takes de-identified CMR image data as input, including standard clinical sequences (e.g., cine LGE), and automatically generates a free-text radiology report describing cardiac structure, function, and imaging findings.
The generated reports are produced offline and retrospectively, and are not used for clinical decision-making or patient management. No changes are made to the imaging acquisition protocol or standard clinical workflow.
For evaluation purposes, the AI-generated reports are compared with reference reports authored by experienced cardiovascular radiologists, using predefined quantitative accuracy metrics and expert qualitative assessment of clinical correctness, completeness, and readability.
This intervention is intended solely for research and performance evaluation of automated report generation and does not influence patient care.
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic Accuracy of AI-Generated Cardiac MRI Reports
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.
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Jan 2026
- Study start1 Oct 2025
- Primary completion1 Oct 2027 (estimated)
- Study completion1 Jan 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for HCM - Hypertrophic CardiomyopathyStudies of the same condition, open and under way.
- More trials run by Chinese Academy of Medical Sciences, Fuwai HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 20,000 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Minjie Lu, Chinese Academy of Medical Sciences, Fuwai Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07340762
- Sponsor's protocol ID
- CMR_AutoReport
- Status last verified
- Jan 2026
- First submitted
- 5 Jan 2026
- Last updated
- 21 Jan 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 21 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-step Automated Report Generation of Cardiovascular Magnetic Resonance Imaging Based on Visual Large Language Model
- ClinicalTrials.gov ID
- NCT07340762
- Acronym / sponsor ID
- CMR_AutoReport
- Conditions
- HCM - Hypertrophic Cardiomyopathy
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 20,000 participants (actual)
- Lead sponsor
- Chinese Academy of Medical Sciences, Fuwai HospitalUniversity, hospital or other
- Study start
- 1 Oct 2025 (actual)
- Primary completion
- 1 Oct 2027 (estimated)
- Study completion
- 1 Jan 2028 (estimated)
- First posted
- 14 Jan 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- 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.
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (4 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| large lanuage modelThe intervention consists of an automated CMR report generation system based on a large multimodal deep learning model. The model takes de-identified CMR image data as input, including standard clinical sequences (e.g., cine LGE), and automatically generates a free-text radiology report describing cardiac structure, function, and imaging findings. The generated reports are produced offline and retrospectively, and are not used for clinical decision-making or patient management. No changes are made to the imaging acquisition protocol or standard clinical workflow. For evaluation purposes, the AI-generated reports are compared with reference reports authored by experienced cardiovascular radiologists, using predefined quantitative accuracy metrics and expert qualitative assessment of clinical correctness, completeness, and readability. This intervention is intended solely for research and performance evaluation of automated report generation and does not influence patient care. | Other | – |
Primary outcome
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jan 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of HCM - Hypertrophic Cardiomyopathy, run by Chinese Academy of Medical Sciences, Fuwai Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 21 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic Accuracy of AI-Generated Cardiac MRI Reports (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jan 2026.