AI-Based Shape and Function Analysis of Mitral Valve Prolapse Using 3D Ultrasound (NCT07384871) | Clinical Trial Compass
RecruitingNot Applicable
AI-Based Shape and Function Analysis of Mitral Valve Prolapse Using 3D Ultrasound
Italy150 participantsStarted 2025-05-26
Plain-language summary
This study aims to develop and validate a fully automated imaging and modeling pipeline for the analysis of mitral valve prolapse (MVP) using real-time three-dimensional transesophageal echocardiography (RT3DE). The primary goal is to automatically segment mitral valve (MV) substructures, extract anatomical landmarks, and generate 3D models of the MV apparatus to characterize morphological and functional features of degenerative MVP. Advanced deep learning techniques and geometric processing tools will be applied to enable automated analysis.
A secondary objective is to build patient-specific finite element (FE) models based on RT3DE data to evaluate the biomechanical consequences of MVP and to simulate the effects of surgical repair. These simulations will assess stress distribution and force transmission within the MV apparatus.
Additionally, in cases where substantial surgical resection of MV tissue occurs, excised leaflet samples will be collected and preserved for histological and morphometric analysis.
Who can participate
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion Criteria:
* Adult patients (age \> 18 years old);
* Documented symptomatic degenerative MR with indication to MVP surgical repair, following the Heart Team decision;
* Periprocedural transesophageal 3DRTE of the MV apparatus, which is clinical standard modality for morphological assessment and guidance during MVP surgical repair;
* Signed informed consent.
Exclusion Criteria:
* Inadequate quality of 3DRTE imaging, e.g., due to inadequate patient-specific acoustic window;
* 3DRTE imaging with a temporal resolution of \< 20 Hz;
* Patient treated through prosthetic MV replacement.
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Accuracy of automated MV substructure segmentation and extraction of anatomical landmarks from RT3DE