Diagnostic ImagingNCT07555002
Prospective User Study and Clinical Validation of Multimodal Medical Imaging Large Models
An observational study of Diagnostic Imaging and Common Systemic Diseases, run by The Third Affiliated Hospital of Southern Medical University at 1 site in China.
Trial summary
Following model development and locking, the fixed model is evaluated in prospectively collected CT cohorts from a single center. The study is observational and does not affect clinical care. A subset of cases is used in a randomized crossover reader study. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Diagnostic Imaging, Common Systemic Diseases, Artificial Intelligence (AI)
- What is being tested?
- Standalone Radiologist Interpretation and AI-assisted Radiologist Interpretation
- How many people
- 310 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2026to 10 Jul 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients from The Third Affiliated Hospital of Southern Medical University who underwent systemic CT imaging for various clinical indications, representing a broad range of common systemic diseases.
Who may be able to join
- Patients who underwent CT examinations for common systemic diseases.
- Imaging data must have confirmed clinical reference standards, expert consensus, or pathological diagnosis.
- Availability of complete DICOM format images with standard acquisition protocols.
Who cannot join
- Poor image quality (e.g., severe motion or metal artifacts) that precludes definitive diagnosis.
- Cases with incomplete clinical or pathological reference standards.
- Corrupted image files or duplicate cases.
Trial locations and contacts
1 site in 1 country.
China1 site
The Third Affiliated Hospital of Southern Medical University
Guangzhou, Guangdong, 510630
About this study
Official title: Prospective User Study and Clinical Validation of Multimodal Medical Imaging Large Models in the Diagnosis of Common Systemic Diseases
Following model development and locking, the fixed model is evaluated in prospectively collected CT cohorts from a single center. The study is observational and does not affect clinical care. A subset of cases is used in a randomized crossover reader study.
Read the detailed description
After model locking, CT data are prospectively collected at a single center for observational validation without retraining or parameter adjustment. Model outputs do not influence patient management. A subset of eligible cases is selected for the randomized crossover reader study.
- Being tested
- Standalone Radiologist Interpretation, AI-assisted Radiologist Interpretation
- Keywords
- Multimodal Large Model, Deep Learning, Radiology, Diagnostic Performance
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Standalone Radiologist InterpretationOther
Radiologists interpret the medical images independently without any assistance from the AI model to establish a baseline performance.
AI-assisted Radiologist InterpretationOther
Radiologists interpret the same set of medical images with the assistance of the multimodal medical imaging large model to evaluate the improvement in diagnostic performance.
| Study group | Role | What they receive |
|---|---|---|
| Validation Cohort | Prospective Observational Validation Cohorts CT data are prospectively collected at a single center after model locking and used for observational model validation. A subset is included in the randomized crossover reader study. Receives: Other: Standalone Radiologist Interpretation; Other: AI-assisted Radiologist Interpretation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Case-level Diagnostic Accuracy and Area Under the ROC Curve (AUC)
Evaluation of case-level diagnostic accuracy (defined as the proportion of diagnostic decisions matching the clinical ground-truth label) and discrimination performance (measured by AUC) to compare unaided radiologist performance versus AI-assisted performance.
Measured: Up to 1 week per evaluation period
Secondary outcomes (3)
Diagnostic Efficiency (Reading and Reporting Time)
Measurement of diagnostic efficiency recorded as the time (in seconds) taken by radiologists to complete the case review and generate findings, with and without AI assistance.
Measured: Up to 1 week per evaluation period
Inter-rater Agreement (Fleiss' Kappa)
Assessment of diagnostic consensus and inter-rater consistency among participating radiologists measured using Fleiss' kappa (κ).
Measured: Up to 1 week per evaluation period
Clinical Report Quality and Semantic Accuracy Score
Assessment of AI-generated draft report quality evaluated by senior experts on a 5-point Likert scale (focusing on semantic accuracy and clinical relevance) and automated metrics (GREEN and ROUGE-L).
Measured: Up to 1 week per evaluation period
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Apr 2026
- Study start1 Jan 2026
- Primary completion8 Jun 2026
- Study completion10 Jul 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diagnostic ImagingStudies of the same condition, open and under way.
- 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
- Prospective
- Enrolment
- 310 participants (actual)
Sponsor and investigators
- Lead sponsor
- The Third Affiliated Hospital of Southern Medical University
- Sponsor type
- Other government
- Responsible party
- Principal investigator, Junyan Li, The Third Affiliated Hospital of Southern Medical University
- Investigators
- Yinghua Zhao, PhD, Principal investigator, The Third Affiliated Hospital of Southern Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07555002
- Sponsor's protocol ID
- 2025-ER-141
- Status last verified
- Oct 2026
- First submitted
- 21 Apr 2026
- Last updated
- 19 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: To protect patient privacy and comply with institutional data security regulations.
Study at a glance
From the registry record, last updated by the sponsor on 19 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective User Study and Clinical Validation of Multimodal Medical Imaging Large Models in the Diagnosis of Common Systemic Diseases
- ClinicalTrials.gov ID
- NCT07555002
- Acronym / sponsor ID
- 2025-ER-141
- Keywords
- Multimodal Large Model, Deep Learning, Radiology, Diagnostic Performance
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 310 participants (actual)
- Lead sponsor
- The Third Affiliated Hospital of Southern Medical UniversityOther government
- Study start
- 1 Jan 2026 (actual)
- Primary completion
- 8 Jun 2026 (actual)
- Study completion
- 10 Jul 2026 (actual)
- First posted
- 28 Apr 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.
Following model development and locking, the fixed model is evaluated in prospectively collected CT cohorts from a single center. The study is observational and does not affect clinical care. A subset of cases is used in a randomized crossover reader study.
Detailed description
After model locking, CT data are prospectively collected at a single center for observational validation without retraining or parameter adjustment. Model outputs do not influence patient management. A subset of eligible cases is selected for the randomized crossover reader study.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Validation Cohort | – | Other: Standalone Radiologist Interpretation, Other: AI-assisted Radiologist InterpretationProspective Observational Validation Cohorts CT data are prospectively collected at a single center after model locking and used for observational model validation. A subset is included in the randomized crossover reader study. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients from The Third Affiliated Hospital of Southern Medical University who underwent systemic CT imaging for various clinical indications, representing a broad range of common systemic diseases.
Key inclusion criteria (3 listed)
- Patients who underwent CT examinations for common systemic diseases.
- Imaging data must have confirmed clinical reference standards, expert consensus, or pathological diagnosis.
- Availability of complete DICOM format images with standard acquisition protocols.
Key exclusion criteria (3 listed)
- Poor image quality (e.g., severe motion or metal artifacts) that precludes definitive diagnosis.
- Cases with incomplete clinical or pathological reference standards.
- Corrupted image files or duplicate cases.
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 |
|---|---|---|
| Standalone Radiologist InterpretationRadiologists interpret the medical images independently without any assistance from the AI model to establish a baseline performance. | Other | Validation Cohort |
| AI-assisted Radiologist InterpretationRadiologists interpret the same set of medical images with the assistance of the multimodal medical imaging large model to evaluate the improvement in diagnostic performance. | Other | Validation Cohort |
Primary outcome
Case-level Diagnostic Accuracy and Area Under the ROC Curve (AUC)
Time frame: Up to 1 week per evaluation period
Evaluation of case-level diagnostic accuracy (defined as the proportion of diagnostic decisions matching the clinical ground-truth label) and discrimination performance (measured by AUC) to compare unaided radiologist performance versus AI-assisted performance.
3 secondary outcomes
Diagnostic Efficiency (Reading and Reporting Time)
Time frame: Up to 1 week per evaluation period
Inter-rater Agreement (Fleiss' Kappa)
Time frame: Up to 1 week per evaluation period
Clinical Report Quality and Semantic Accuracy Score
Time frame: Up to 1 week per evaluation period
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Oct 2026.
- Individual participant dataSharing planned: No. To protect patient privacy and comply with institutional data security regulations.
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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.
Yinghua Zhao, PhD principal investigator
The Third Affiliated Hospital of Southern Medical University
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 Diagnostic Imaging and Common Systemic Diseases, run by The Third Affiliated Hospital of Southern Medical University 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 3 inclusion and 3 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: finished, as of the sponsor's last update on 19 Oct 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Case-level Diagnostic Accuracy and Area Under the ROC Curve (AUC) (time frame: Up to 1 week per evaluation period). 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 19 Oct 2026.