AI-Based Morphological Analysis and Biomechanical Numerical Evaluation of Mitral Valve Prolapse (MVP) From Real-Time 3D Echocardiography (RT3DE)
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 150
- 试验地点
- 1
- 主要终点
- Accuracy of automated MV substructure segmentation and extraction of anatomical landmarks from RT3DE
研究概览
简要总结
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.
详细描述
This prospective study aims to investigate the anatomical and biomechanical characteristics of MVP using RT3DEE and advanced artificial intelligence (AI)-based image analysis techniques. The goal is to develop an automated framework for the segmentation and morphological assessment of the MV apparatus, and to conduct FE modeling to evaluate the biomechanical implications of degenerative MVP and associated surgical repairs.
Imaging Protocol Intraoperative RT3DE will be performed in the operating room as part of the standard imaging protocol during surgical MVP repair. A Vivid S70N ultrasound system (GE Healthcare) equipped with a 6VT 4D multiplane RT3DE probe will be used. Standard mid-esophageal RT3DE views will be acquired, including full left ventricular (LV) chamber volumes and zoomed, gated 3D views of the MV complex (annulus, leaflets, and papillary muscles). To enhance image quality, zoomed acquisitions will be limited to the smallest pyramidal volume capturing the entire mitral complex, ensuring frame rates ≥20 Hz. All imaging datasets will be anonymized prior to analysis.
Surgical Protocol MVP surgical repair will be conducted under general anesthesia through a right mini-thoracotomy. Surgical techniques will include: i) leaflet resection (removal of excess leaflet tissue); ii) neochordal implantation (placement of expanded polytetrafluoroethylene, ePTFE, artificial chordae); annuloplasty (implantation of an annuloplasty ring or pericardial band for annular stabilization).
In cases where significant leaflet tissue is excised (≥10×10 mm), samples will be collected and stored in the institutional BioCor biobank for histological and morphometric analysis. Samples will be decontaminated, cryopreserved, and stored at -80°C. After histological evaluation, all biological material will be destroyed.
Clinical Data Collection Demographic (e.g., age, sex) and clinical data (e.g., diagnosis, medications, comorbidities) will be obtained from medical records and anonymized.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Accuracy of automated MV substructure segmentation and extraction of anatomical landmarks from RT3DE
时间窗: 36 months
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).
次要结局
- Automated quantification of MV morphometric and functional descriptors(36 months)
- Change in mechanical stress of MV leaflets following surgical MVP repair(Up to 1 month after MVP surgical repair)
- Change in mechanical load transfer to MV sub-apparatus following surgical MVP repair(Up to 1 month after MVP surgical repair)
- Change in mechanical stress of MV papillary muscles following surgical MVP repair(Up to 1 month after MVP surgical repair)
- Change in coaptation of MV leaflets following surgical MV repair(Up to 1 month after MVP surgical repair)
- Thickness of MV leaflet tissue excised during MVP surgical repair(Up to 2 weeks after MVP surgical repair)
- Degree of myxomatous degeneration of excised MV leaflet tissue(Up to 2 weeks after MVP surgical repair)
- Structural histological analysis of excised myxomatous MV leaflet tissue(Up to 2 weeks after MVP surgical repair)