AI-Based Shape and Function Analysis of Mitral Valve Prolapse Using 3D Ultrasound
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorIRCCS Policlinico S. Donato
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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.
Disqualifiers
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.
Trial population
The study will focus on patients referred to IRCCS Policlinico San Donato for surgical MVP repair. The study will exploit the standard clinical imaging required during MVP surgical repair and will have no impact on the clinical procedure. No variation in prophylaxis or follow-up is expected compared to those of practice as suggested by the international guideline. Hence, there are no physical, psychological, and social risks and/or direct benefits associated with the activities carried out during the study.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
Accuracy of automated MV substructure segmentation and extraction of anatomical landmarks from RT3DE
The accuracy of AI-based automated segmentation of MV substructures (anterior and posterior leaflets, mitral annulus, and papillary muscles) from RT3DE is assessed using expert manual segmentation as reference standard and analyzing the following measures: i) Dice Similarity Coefficient (DSC, -); ii) Mean Surface Distance (MSD, mm); iii) Hausdorff Distance (HD, mm). Accuracy of AI-based automated identification of key MV anatomical landmarks relevant to degenerative mitral valve prolapse is assessed compared with expert manual annotation analyzing the Euclidean distance error (mm) between automated and expert-defined landmarks (annular hinge points, leaflet free-edge points, coaptation line, papillary muscle tips).
Time frame
36 monthsSecondary outcomes
1
Automated quantification of MV morphometric and functional descriptors
Ability of the automated pipeline to derive consistent quantification - compared to commercially available solutions for RT3DE processing - of clinically relevant morphometric and functional descriptors of degenerative MVP from RT3DE: i) mitral annular dimensions (projected area, mm²; perimeter, mm; antero-posterior and commissural diameters, mm; height, mm; ellipticity, -); ii) leaflet surface area and billowing volume (mm², mm³); leaflet prolapse height and prolapse volume (mm, mm³); coaptation length and coaptation area (mm, mm²).
Time frame
36 months2
Change in mechanical stress of MV leaflets following surgical MVP repair
Assessment of change in mechanical stress of MV leaflets following surgical MVP repair using patient-specific FE MV models derived from RT3DE, comparing peak and mean leaflet stress (kPa) between degenerative MVP and post-repair conditions.
Time frame
Up to 1 month after MVP surgical repair3
Change in mechanical load transfer to MV sub-apparatus following surgical MVP repair
Assessment of changes in the mechanical load transfer to MV sub-apparatus following MV surgical repair using patient-specific FE MV models derived from RT3DE, comparing chordal forces and load transfer to MV papillary muscles (N) between degenerative MVP and post-repair conditions.
Time frame
Up to 1 month after MVP surgical repair4
Change in mechanical stress of MV papillary muscles following surgical MVP repair
Assessment of change in mechanical stress acting on MV papillary muscles following surgical MVP repair using patient-specific FE MV models derived from RT3DE, comparing peak and mean stress (kPa) between degenerative MVP and post-repair conditions.
Time frame
Up to 1 month after MVP surgical repairSponsors and contacts
Click on the lead sponsor to view all of their trials.
Source ClinicalTrials.gov