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NCT Number: NCT07555002

Prospective User Study and Multicenter Validation of Multimodal Medical Imaging Large Models

Following model development and locking, the fixed model is evaluated in prospectively collected CT cohorts from two centers. The study is observational and does not affect clinical care. A subset of cases is used in a randomized crossover reader study.

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Key information

Conditions

Diagnostic Imaging Artificial Intelligence (AI) Common Systemic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

The Third Affiliated Hospital of Southern Medical University

Guangzhou, Guangdong, 510630, China

About this study

After model locking, CT data are prospectively collected at two centers 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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • 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.

Exclusion criteria

  • 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.

Treatment and study plan

Standalone Radiologist Interpretation

Other

Radiologists interpret the medical images independently without any assistance from the AI model to establish a baseline performance.

AI-assisted Radiologist Interpretation

Other

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.

Primary outcomes

  1. 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.

Secondary outcomes

  1. Diagnostic Efficiency (Reading and Reporting Time)

    Time frame: Up to 1 week per evaluation period

    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.

  2. Inter-rater Agreement (Fleiss' Kappa)

    Time frame: Up to 1 week per evaluation period

    Assessment of diagnostic consensus and inter-rater consistency among participating radiologists measured using Fleiss' kappa (κ).

  3. Clinical Report Quality and Semantic Accuracy Score

    Time frame: Up to 1 week per evaluation period

    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).

Sponsors and collaborators

Lead sponsor

The Third Affiliated Hospital of Southern Medical University

Other Gov

Registry information

Official study title

Prospective User Study and Multicenter Validation of Multimodal Medical Imaging Large Models in the Diagnosis of Common Systemic Diseases

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Apr 28, 2026
Registry last updated
Aug 7, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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