Abstract:The assessment of left ventricular shape changes during cardiac revolution may be a new step in clinical cardiology to ease early diagnosis and treatment. To quantify these changes, only point registration was adopted and neither Generalized Procrustes Analysis nor Principal Component Analysis were applied as we did previously to study a group of healthy subjects. Here, we extend to patients affected by hypertrophic cardiomyopathy the original approach and preliminarily include genotype positive/phenotype nega… Show more
“…Motion analysis is particularly appropriate to apply PT strategies (Euclidean or Riemannian). Piras et al (2014) and Madeo et al (2015) used it in order to model the shape and size modifications of the human left ventricle (LV) during its cycle. Heart cycle, and in particular LV revolution, is paradigmatic of the higher importance of deformation in comparison to initial shape differences.…”
Section: Discussionmentioning
confidence: 99%
“…This approach is a Euclidean type of PT, based on simple operations such as addition and subtraction, and has been effectively applied in Piras et al (2014) and Madeo et al (2015) under the name "linear shift" (LS).…”
Section: Parallel Transport In a Nutshellmentioning
confidence: 99%
“…It is important to tell apart open from closed allometric shape paths (such as in heart cycle characterized by the two distinct phases diastole-systole and systole-diastole- Piras et al 2014;Madeo et al 2015;Piras et al 2016) as the latter are unrelated to individual growth.…”
Ontogeny is usually studied by analyzing a deformation series spanning over juvenile to adult shapes. In geometric morphometrics, this approach implies applying generalized Procrustes analysis coupled with principal component analysis on multiple individuals or multiple species datasets. The trouble with such a procedure is that it mixes intra- and inter-group variation. While MANCOVA models are relevant statistical/mathematical tools to draw inferences about the similarities of trajectories, if one wants to observe and interpret the morphological deformation alone by filtering inter-group variability, a particular tool, namely parallel transport, is necessary. In the context of ontogenetic trajectories, one should firstly perform separate multivariate regressions between shape and size, using regression predictions to estimate within-group deformations relative to the smallest individuals. These deformations are then applied to a common reference (the mean of per-group smallest individuals). The estimation of deformations can be performed on the Riemannian manifold by using sophisticated connection metrics. Nevertheless, parallel transport can be effectively achieved by estimating deformations in the Euclidean space via ordinary Procrustes analysis. This approach proved very useful in comparing ontogenetic trajectories of species presenting large morphological differences at early developmental stages.
“…Motion analysis is particularly appropriate to apply PT strategies (Euclidean or Riemannian). Piras et al (2014) and Madeo et al (2015) used it in order to model the shape and size modifications of the human left ventricle (LV) during its cycle. Heart cycle, and in particular LV revolution, is paradigmatic of the higher importance of deformation in comparison to initial shape differences.…”
Section: Discussionmentioning
confidence: 99%
“…This approach is a Euclidean type of PT, based on simple operations such as addition and subtraction, and has been effectively applied in Piras et al (2014) and Madeo et al (2015) under the name "linear shift" (LS).…”
Section: Parallel Transport In a Nutshellmentioning
confidence: 99%
“…It is important to tell apart open from closed allometric shape paths (such as in heart cycle characterized by the two distinct phases diastole-systole and systole-diastole- Piras et al 2014;Madeo et al 2015;Piras et al 2016) as the latter are unrelated to individual growth.…”
Ontogeny is usually studied by analyzing a deformation series spanning over juvenile to adult shapes. In geometric morphometrics, this approach implies applying generalized Procrustes analysis coupled with principal component analysis on multiple individuals or multiple species datasets. The trouble with such a procedure is that it mixes intra- and inter-group variation. While MANCOVA models are relevant statistical/mathematical tools to draw inferences about the similarities of trajectories, if one wants to observe and interpret the morphological deformation alone by filtering inter-group variability, a particular tool, namely parallel transport, is necessary. In the context of ontogenetic trajectories, one should firstly perform separate multivariate regressions between shape and size, using regression predictions to estimate within-group deformations relative to the smallest individuals. These deformations are then applied to a common reference (the mean of per-group smallest individuals). The estimation of deformations can be performed on the Riemannian manifold by using sophisticated connection metrics. Nevertheless, parallel transport can be effectively achieved by estimating deformations in the Euclidean space via ordinary Procrustes analysis. This approach proved very useful in comparing ontogenetic trajectories of species presenting large morphological differences at early developmental stages.
Abstract-Goal: Hexahedral automatic model generation is a recurrent problem in computer vision and computational biomechanics. It may even become a challenging problem when one wants to develop a patient-specific finite-element (FE) model of the left ventricle (LV), particularly when only low resolution images are available. In the present study, a fast and efficient algorithm is presented and tested to address such a situation. Methods: A template FE hexahedral model was created for a LV geometry using a General Electric (GE) ultrasound (US) system. A system of centerline was considered for this LV mesh. Then, the nodes located over the endocardial and epicardial surfaces are respectively projected from this centerline onto the actual endocardial and epicardial surfaces reconstructed from a patient's US data. Finally, the position of the internal nodes is derived by finding the deformations with minimal elastic energy. This approach was applied to eight patients suffering from congestive heart disease. A FE analysis was performed to derive the stress induced in the LV tissue by diastolic blood pressure on each of them. Results: Our model morphing algorithm was applied successfully and the obtained meshes showed only marginal mismatches when compared to the corresponding US geometries. The diastolic FE analyses were successfully performed in seven patients to derive the distribution of principal stresses. Conclusion: The original model morphing algorithm is fast and robust with low computational cost. Significance: This low cost model morphing algorithm may be highly beneficial for future patient-specific reduced-order modelling of the LV with potential application to other crucial organs.
“…In order to study trajectory attributes, it is essential to evaluate shapes at physiologically homologous times. While in 8, 14, 16 the set of homologous times refer to LV or LA only, in this study we needed to set them according to the concomitant function of both chambers. Figure 7 shows the concept of our procedure as applied to two heart beats.Figure 7Interpolation procedure.…”
Left ventricle and left atrium are and have been practically always analyzed separately in common clinically and non-clinically oriented cardiovascular investigations. Both classic and speckle tracking echocardiographic data contributed to the knowledge about deformational impairments occurring in systo-diastolic differences. Recently new trajectory based approaches allowed a greater awareness about the entire left ventricle or left atrium revolution and on their deficiencies that take place in presence of hypertrophic cardiomyopathy. However, surprisingly, the concomitant function of the two left heart chambers has not been analyzed for their geometrical/mechanical relationship. For the first time we study here, by acquiring left ventricle and left atrial geometries on the same heartbeat, the trajectory attributes of the entire left heart treated as a whole shape and the shape covariation of its two subunits. We contrasted healthy subjects with patients affected by hypertrophic cardiomyopathy. We found impaired left heart trajectory mainly in terms of orientation and size. More importantly, we found profound differences in the direction of morphological covariation of left ventricle and left atrium. These findings open to new perspectives in pathophysiological evaluation of different diseases by allowing the appreciation of concomitant functioning of both left heart whole geometry and of its two chambers.
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