RecruitingNCT07449130

AI Assisted Screening for VHD Using Routine Chest CT Scans

Artificial-Intelligence Assisted Opportunistic Screening for Valvular Heart Disease Using Non-contrast Chest CT Scans: A Prospective, Multicenter Study

Sponsor

Second Affiliated Hospital, School of Medicine, Zhejiang University

Enrollment

3,000 participants

Start Date

Mar 2, 2026

Study Type

OBSERVATIONAL

Conditions

Heart Valve Diseases

Summary

This is a prospective, multicenter study designed to develop and validate a deep learning model for screening valvular heart diseases using routine, non-contrast chest computed tomography (CT) scans. The primary objective is to evaluate the model's diagnostic performance, with the sensitivity serving as the primary efficacy endpoint. Secondary endpoints will include other performance metrics such as area under the receiver operating characteristic curve (AUC), specificity, and accuracy, etc.

Eligibility

Min Age: 18 Years

Inclusion Criteria4

Age ≥ 18 years.
Complete electronic health record.
Non-contrast chest CT performed between Nov 1, 2025 - Nov 1, 2026 (physical exam or outpatient).
AI-predicted moderate or severe valvular heart disease, or deemed to require clinical intervention.

Exclusion Criteria4

Poor-quality non-contrast chest CT images.
Incomplete clinical records, involving severe deficiencies in critical diagnostic results, treatment records, imaging data, surgical records, medical history summaries, laboratory test results, or other essential medical information.
Presence of prosthetic valve implants, including aortic valves (mechanical valves, bioprosthetic valves), mitral valves (transcatheter edge-to-edge repair, bioprosthetic valves, mechanical valves, annuloplasty rings), tricuspid valves (TEER clipping, bioprosthetic valves, mechanical valves, annuloplasty rings), pulmonary valves (bioprosthetic valves), etc.
Abnormalities or conditions deemed by the investigator to warrant exclusion from the study enrollment.

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