Abstract:The aim of this study is to investigate human left ventricular heart morphological changes in time among 17 healthy subjects. Preliminarily, 2 patients with volumetric overload due to aortic insufficiency were added to our analyses. We propose a special strategy to compare the shape, orientation and size of cardiac cycle’s morphological trajectories in time. We used 3D data obtained by Speckle Tracking Echocardiography in order to detect semi-automated and homologous landmarks clouds as proxies of left ventric… Show more
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.
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.
“…These landmarks can be considered (with a certain degree of approximation) anatomically homologous or not between different subjects. In the former case, anatomical homology allows the possibility of analysing landmarks with the standard geometric morphometrics (GM) toolkit successfully applied in a wide range of disciplines from paleobiology to medicine …”
Section: Introduction: Shape Analysis In Cardiac Imagingmentioning
confidence: 99%
“…Very often, in medical applications, the goal of shape analysis is not the assessment of differences between shapes; rather, the main aim is to find differences between deformations. This distinction is crucial and inevitably leads to the definition and quantification of deformation occurring between two shapes, eg, a source and a target . In this paper, we focus on the left ventricle (LV) cardiac revolution represented by 2D shapes deriving from projections on the coronal plane of the whole LV 3D reconstruction coming from 3D speckle tracking echocardiography (3DSTE).…”
Section: Introduction: Shape Analysis In Cardiac Imagingmentioning
confidence: 99%
“…In the former case, anatomical homology allows the possibility of analysing landmarks with the standard geometric morphometrics (GM) toolkit successfully applied in a wide range of disciplines from paleobiology 1-3 to medicine. 4 Without the homology assumption, several strategies have been developed in order to perform shape-matching basing on a plethora of algorithms 5,6 whose review is not the scope of the present paper. In recent years, the emerging disciplines of diffeomorphometry and the related functional anatomy have been applied to supplement classic GM through Int J Numer Meth Biomed Engng.…”
In a previous contribution, a new Riemannian shape space, named TPS space, was introduced to perform statistics on shape data. This space was endowed with a Riemannian metric and a flat connection, with torsion, compatible with the given metric. This connection allows the definition of a Parallel Transport of the deformation compatible with the three‐fold decomposition in spherical, deviatoric, and non‐affine components. Such a parallel transport also conserves the Γ‐energy, strictly related to the total elastic strain energy stored by the body in the original deformation. A new approach is here presented in order to calculate the bending energy on the body alone (body bending energy) and to restrict it exclusively within physical boundaries of objects involved in the deformation analysis. The novelty of this new procedure resides in the fact that we propose a new metric to be preserved during the TPS direct transport. This allows transporting the shape change more coherently with the mechanical meaning of the deformation. The geometry of the TPS space is then further discussed in order to better represent the relationship between the Γ‐energy, the strain energy, and the so‐called bending energy densities.
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