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Research on the Development and Application of a Preoperative Assessment Model for Transcatheter Mitral Valve Edge-to-Edge Repair Based on Visual Foundation Models

NCT07247890 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 800

Last updated 2025-11-25

No results posted yet for this study

Summary

Mitral regurgitation (MR) is the most prevalent valvular heart disease in China. Transcatheter edge-to-edge repair (TEER) is currently the preferred treatment for patients with severe MR who face high surgical risks. However, existing preoperative assessment methods for TEER suffer from numerous limitations, including complex measurement parameters, high technical demands, and significant subjectivity. Vision Mamba, a cutting-edge technology in the visual domain, overcomes the limitations of common computational units in convolutional neural networks and Transformers through bidirectional state space models and positional encoding, demonstrating exceptional performance in visual tasks. To date, no studies have applied Vision Mamba to ultrasound videos for constructing TEER preoperative assessment models. Our team previously established a Transformer-based evaluation model using a small, single-center cohort. This study innovatively introduces a Vision Mamba-based visual foundation model. By integrating multi-faceted, multi-modal ultrasound videos from multiple centers, we develop a one-stop preoperative TEER assessment model for MR patients \[slice identification → video analysis → multi-modal information fusion → preoperative assessment recommendation (suitable/challenging/unsuitable)\]. This model will optimize surgical patient identification and accurately screen patients with contraindications. Furthermore, the one-stop model is fast and objective, significantly improving clinical efficiency. It holds promise for deployment at primary care levels to optimize healthcare resource allocation.

Conditions

  • Mitral Regurgitation (MR)

Interventions

OTHER

Model Construction, Validation, and Optimization

Data from patients in this study will be used for model construction, validation, and optimization.

Sponsors & Collaborators

  • Beijing Hospital

    lead OTHER_GOV

Eligibility

Min Age
18 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-12-31
Primary Completion
2027-12-31
Completion
2027-12-31

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07247890 on ClinicalTrials.gov