An interactive tool for rapid biventricular analysis of congenital heart disease

Gilbert, Kathleen; Lam, H.; Pontré, Beau; Cowan, Brett R.; Occleshaw, Chris; Jy, Liu; Young, Alistair A.

doi:10.1111/cpf.12319

Cited by 10 publications

(14 citation statements)

References 24 publications

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“…On the other hand the finite element models, such as used in Young et al (2011); Gilbert et al (2015), are more versatile in terms of parameterization and can be used to represent the whole of the cardiac chambers up to the valves with any number of holes. In this case, the point correspondence across the population is established using registration techniques or model fitting to an image.…”

Section: Discussionmentioning

confidence: 99%

“…This limitation is based on the idea that such geometries can be conveniently flattened into a disk. However if more than one opening is present, as in the case of inflow and outflow tracts of the right ventricle (as in Gilbert et al (2015)) the proposed approach can be modified in two ways: use one of the holes as the boundary and leave the other hole in the interior of the flat disk, similarly to Tobon-Gomez et al (2015); or if the 2D visualization is not crucial, the parameterization can also be achieved by mapping the whole chamber to a spherical shell using exactly the same methodology with an additional registration step to make sure the holes match on the sphere.…”

Section: Mapping Of Human Heart Datasets Including Inflow and Outflowmentioning

confidence: 99%

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Patient independent representation of the detailed cardiac ventricular anatomy

Paun

Bijnens

Iles³

et al. 2017

Medical Image Analysis

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Reparameterization of surfaces is a widely used tool in computer graphics known mostly from the remeshing algorithms. Recently, the surface reparameterization techniques started to gain popularity in the field of medical imaging, but mostly for convenient 2D visualization of the information initially represented on 3D surfaces (e.g. continuous bulls-eye plot). However, by consistently mapping the 3D information to the same 2D domain, surface reparameterization techniques allow us to put into correspondence anatomical shapes of inherently different geometry. In this paper, we propose a method for anatomical parameterization of cardiac ventricular anatomies that include myocardium, trabeculations, tendons and papillary muscles. The proposed method utilizes a quasi-conformal flattening of the myocardial surfaces of the left and right cardiac ventricles and extending it to cover the interior of the cavities using the local coordinates given by the solution of the Laplace's equation. Subsequently, we define a geometry independent representation for the detailed cardiac left and right ventricular anatomies that can be used for convenient visualization and statistical analysis of the trabeculations in a population. Lastly we show how it can be used for mapping the detailed cardiac anatomy between different hearts, which is of considerable interest for detailed cardiac computational models or shape atlases.

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Section: Discussionmentioning

confidence: 99%

Section: Mapping Of Human Heart Datasets Including Inflow and Outflowmentioning

confidence: 99%

Patient independent representation of the detailed cardiac ventricular anatomy

Paun

Bijnens

Iles³

et al. 2017

Medical Image Analysis

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“…Guide-point modelling [25, 6] was used to interactively customize a 3D time-varying finite element model to a patient’s cardiac MRI scan. The biventricular finite element model is shown in Figure 2 and consisted of 82 3D elements with Bézier interpolation and C 1 continuity, meaning surfaces were continuous in slope across the element boundaries.…”

Section: Methodsmentioning

confidence: 99%

“…Predicted points were calculated algorithmically to improve computational efficiency in the optimization process [6] by using a simple model defined in prolate spheroid coordinates to represent the LV endocardial surface and the biventricular epicardial surface [5]. Figure 4 (a) shows the LV prolate model.…”

Section: Methodsmentioning

confidence: 99%

“…The smoothing term in Equation 1 is required to regularize the solution in the presence of sparse data. Previously, a Sobolev smoothing term [12, 23] has been used for this purpose [6]; however, this has the disadvantage of being sensitive to large rotations and motions, as are often seen around the RV, leaving artifacts in the model surfaces. In this work we used a D-Affine smoothing term [5], which penalized change in deformation across the model.…”

Section: Methodsmentioning

confidence: 99%

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4D modelling for rapid assessment of biventricular function in congenital heart disease

Gilbert

Pontré

Occleshaw

et al. 2017

Int J Cardiovasc Imaging

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Although more patients with congenital heart disease (CHD) are now living longer due to better surgical interventions, they require regular imaging to monitor cardiac performance. There is a need for robust clinical tools which can accurately assess cardiac function of both the left and right ventricles in these patients. We have developed methods to rapidly quantify 4D (3D + time) biventricular function from standard cardiac MRI examinations. A finite element model was interactively customized to patient images using guide-point modelling. Computational efficiency and ability to model large deformations was improved by predicting cardiac motion for the left ventricle and epicardium with a polar model. In addition, large deformations through the cycle were more accurately modeled using a Cartesian deformation penalty term. The model was fitted to user-defined guide points and image feature tracking displacements throughout the cardiac cycle. We tested the methods in 60 cases comprising a variety of congenital heart diseases and showed good correlation with the gold standard manual analysis, with acceptable inter-observer error. The algorithm was considerably faster than standard analysis and shows promise as a clinical tool for patients with CHD.

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