A Geometric Feature Tracking Approach for Noninvasive Patient-Specific Estimation of Leaflet Strain from 3D Images of Heart Valves

Figures

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  Fig. 1. Feature tracking-informed strain quantification framework. A The atrial surfaces of the valves were extracted from segmentation models and triangulated with 1000 points uniformly distributed across each leaflet. B Within each patient cohort, one diastolic valve was randomly selected as the reference. Leaflets of the same anatomical category were registered to the corresponding reference leaflet to establish point-to-point correspondence. The registered leaflets were then aligned, and the mean shape (reference atlas) was estimated using generalized Procrustes analysis. The mean shape was registered to both the diastolic and systolic frames of that leaflet and leaflet deformation was derived to compute strain on individual leaflets. Supplementary file 1 provides a video to demonstrate the DW-CPD feature tracking process. C For patient cohort analysis, mean valve shapes at diastole and systole were first estimated using generalized Procrustes analysis. Principal component analysis was applied to determine shape variation within each cohort. Finally, valves were registered between the open and closed phases to estimate systolic valve strain.

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  Fig. 2. Feature tracking verification results. A Ground truth areal and 1st principal strain of an image-derived mitral valve (MV) finite element model were used to compare the performance of the proposed and established feature tracking methods. B Qualitative comparisons of the deformed geometry and strain distributions are provided. Both coherent point drift (CPD) and distance-weighted coherent point drift (DW-CPD) successfully captured the large valve deformation and the strain patterns. C DW-CPD yielded more accurate estimates of mean symmetric distance (MSD), areal strain mean absolute error (MAE), and 1st principal strain MAE compared to existing CPD approaches. D The discrepancy in strain estimation using DW-CPD is most noticeable in the commissural folds. E Scatter plots show strong correlations between areal and 1st principal strain generated from DW-CPD and FEA.

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  Fig. 3. Feature tracking performance. A This example illustrates that CPD resulted in self-penetration at the leaflet edge, while the proposed DW-CPD eliminated this defect with improved feature tracking fidelity. B DW-CPD was applied to 3 groups of atrioventricular valves and verified against ground truth segmentation. Strong shape agreement was observed, with MSD values below 0.4 mm and 95th percentile Hausdorff distance (HD95) values below 1 mm across all leaflets.

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  Fig. 4. Pediatric tricuspid valve analysis (N=11). A The estimated systolic atrial surfaces were superimposed onto 3D Transesophageal echocardiographic(TEE) images along with the ground truth segmentation models. Excellent feature tracking accuracy was obtained, as demonstrated in the visualization of the three cut planes shown. B The study cohorts included patients spanning a wide age range, from 5 days to 17 years. For each patient, the surgical stage at the time of image acquisition, as well as the pathological characteristics of the TVs, were reported. C The distributions of 1st principal strain, as well as their median and interquartile range (IQR), were compared across the three leaflets in all 11 patients. Billowing leaflets were typically characterized by a high median and strain IQR, with a relatively uniform strain distribution profile. D Average areal strain and 1st principal strain were compared between the trivial to mild and mild or greater TR cohorts. The trivial to mild cohort exhibited lower areal and 1st principal strain in the anterior leaflet but higher values in the posterior leaflet relative to the mild or greater cohort. Both cohorts showed near zero areal strain…

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  Fig. 5. Pediatric mitral valve analysis (N=10). A Visualization of the ground truth segmentation models and estimated atrial surfaces were superimposed onto 3D TEE images on the three cut planes shown. B The study cohorts included patients from 2 to 16 years old at the time of image acquisition. The MV pathological characteristics for each patient were provided. C The median, IQR, and distribution of 1st principal strain were compared across the anterior and posterior leaflets in all 10 patients. Patient 10 was the only case with leaflet strain exhibiting a median and IQR greater than 0.5, which also corresponded to billowing morphology. D Average areal strain and 1st principal strain were compared between the normal and diseased cohorts. Both cohorts showed negligible changes in leaflet surface area and demonstrated higher average 1st principal strain in the posterior leaflet than in the anterior leaflet. E Population-based strain analysis showed that higher average 1st principal strains at both ends of the shape spectrum compared with the mean shape. In addition, strain SD increased as valve morphology deviated from the mean.

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  Fig. 6. Adult mitral valve analysis (N=10). A Visualization of the ground truth segmentation models and estimated atrial surfaces were superimposed onto 3D TEE images. B The study included adult patients aged 49 to 78 years at the time of image acquisition. All patients had normal MV function but presented with other cardiac conditions. C Narrow 1st principal strain distributions were observed in all MV leaflets. Further, the median and IQR of the strain distributions were below 0.5 across all 10 patients. D Both anterior and posterior leaflets exhibited negative areal strain, which may suggest substantial annular contraction between the mid-diastolic and mid-systolic frames in this cohort. For 1st principal strain, consistent with the pediatric MV study, the posterior leaflet showed higher strain than the anterior leaflet. E In the population-based strain analysis, average areal strain and 1st principal strain both increased with increasing anterior-posterior diameter.