Investigating Cardiac Motion Patterns Using Synthetic High-Resolution 3D Cardiovascular Magnetic Resonance Images and Statistical Shape Analysis

Figures

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  Figure 1. Image-processing pipeline to generate each subject LV anatomical model starting from cine and WH CMR images: (1) Synthetic WH images were created by combining WH with the cine images (2) and segmented with our automatic segmentation method; (3) LV meshes were exported and used to create the subject LV anatomical model.

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  Figure 2. After scaling and alignment (1), subject anatomical models were used to perform (2a) shape analysis on end-diastolic and end-systolic shapes, and (2b) motion analysis after subject-specific shape was removed.

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  Figure 3. Schematic representation of the concept of anatomical model. Template and deformations ϕi toward each shape are estimated with an alternate registration algorithm. The template is initialized as the mean shape and the deformations ϕi are estimated using a Large Deformation Diffeomorphic Mappings framework (23, 24). Each deformation ϕi is defined by a set of momenta vectors βik (arrows in the magnified panel) located at the control points grid.

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  Figure 4. Shape analysis pipeline: for each subject, only ED and ES shapes are used to (1) build an anatomical model representing the LVED, LVES shape variability within the population; (2) the momenta vectors are decomposed with a PCA and the resulting shape modes and shape vector are analyzed.

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  Figure 5. Motion analysis pipeline: (1) each subject LVj,Template is used to compute a general LV shape called LVSuperTemplate. (2) The latter is deformed with each subject-specific deformation, and all the obtained shapes are used to build a motion anatomical model (2). The resulting momenta vectors are decomposed with PCA (3), generating motion modes and motion vector describing each subject motion within the cardiac cycle.

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  Figure 6. WHSyn,jt from 5 evenly spaced frames of the cardiac cycle of the subject j = Control2, obtained by propagating the subject’s motion from the cine dataset onto the high-resolution WH image.

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  Figure 7. WHSyn,jt with overlaid automatic segmentation from 5 evenly spaced frames of the cardiac cycle of the subject j = Control2. Color code for main segmented structures: lemon-green, LV blood pool; orange, LV myocardium; red and dark blue, papillary muscles; light blue, aorta; brown, right ventricle; azure, right atrium; green, superior vena cava; pink, inferior vena cava; white, pulmonary trunk.

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  Figure 8. LVjt meshes for the 4 control and 4 AS subjects obtained by deforming subject-specific LVj,Template (first column) with the deformations estimated during the anatomical model computation, to reproduce 5 evenly spaced frames of the cardiac cycle illustrated in Figures 6 and 7 for each subject.

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  Figure 9. Extreme features (±2σ) of each of the first 4 modes of the shape analysis on LV shapes at ED are shown in the canonical cardiac views (horizontal long axis (HLA), SAX, and vertical long axis (VLA)). Each depicted shape was obtained by morphing the template shape with the extreme deformation represented by each mode. Colormap represents the distribution of regional deformations within each mode, obtained by deforming the ED template shape along the mode (red, high deformation; blue, low deformation).

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  Figure 10. Boxplot showing the variability of the coefficients of the shape vector of LVED shape analysis for the first 4 modes. Single values are reported in Table 2. On each box, the central mark is the median, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points not considered outliers.

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  Figure 11. Extreme features (±2σ) of each of the first 4 modes of the shape analysis on LV shapes at ES are shown in the canonical cardiac views (HLA, SAX, and VLA). Each depicted shape was obtained by morphing the template shape with the extreme deformation represented by each mode. Colormap represents the distribution of regional deformations within each mode, obtained by deforming the ES template shape along the mode (red, high deformation; blue, low deformation).

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  Figure 12. Boxplot showing the variability of the coefficients of the shape vector of LVES shape analysis for the first 4 modes. Single values are reported in Table 3. On each box, the central mark is the median, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points not considered outliers.