Abstract Body (Do not enter title and authors here):
Background: Accurate tracking of the aortic valve in 4D transesophageal echocardiography (TEE) and subsequent leaflet strain measurement remain a challenge due to limited imaging temporal resolution. Conventional intensity-based image registration techniques often fail to capture the rapid nonlinear deformation of valve leaflets across cardiac phases. The objective of this work is to present an image analysis framework that temporally augments 4D TEE with finite element modeling (FEM) to reconstruct patient-specific valve motion and quantify leaflet strain in both trileaflet and bicuspid aortic valves.

Methods: We propose a hybrid framework that integrates FEM with deformable image registration to achieve leaflet tracking in 4D TEE sequences (Fig 1). First, the aortic valve is manually segmented in a mid-systolic “reference” (open) frame. A shell representation of the segmented leaflets is created and integrated with FEM to simulate valve closure. A final mid-diastolic segmentation of the leaflets is obtained by applying the following transformations to the mid-systolic reference segmentation: (1) the FEM-recovered transformations of valve closure and (2) the registration-derived transformation between an FEM-derived synthetic mid-diastolic image and the real mid-diastolic image. The proposed method was tested on six patients with varying aortic valve abnormalities (Table 1), and leaflet strains were computed.

Results: The proposed method significantly improved segmentation tracking accuracy compared to conventional registration. The mean distance between the tracked closed-state segmentation and manual ground truth for six patients was 1.67 ± 0.49 mm using our hybrid approach, versus 3.19 ± 1.17 mm with conventional registration (no FEM). Strain maps showed physiologically consistent patterns with elevated strain near coaptation lines. Notably, patient 4, with severe calcification, exhibited the lowest strain. Representative results are shown in Figure 2.

Conclusions: These findings confirm that biomechanically generated intermediate frames enhance registration accuracy and patient-specific geometric fidelity of the aortic valve, enabling strain analysis. The approach has the potential to inform our understanding of diverse valve mechanics and facilitate translational application to the assessment of structural heart disease.