Personalization of Cardiac Motion and Contractility From Images Using Variational Data Assimilation

Delingette, Hervé; Billet, Florence; Wong, Ken C. L.; Sermesant, Maxime; Rhode, Kawal; Ginks, Matthew; Rinaldi, Christopher Aldo; Razavi, Reza; Ayache, Nicholas

doi:10.1109/tbme.2011.2160347

Cited by 45 publications

(38 citation statements)

References 14 publications

(14 reference statements)

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“…A more flexible way is to embed the pressure data into the objective function, which will be investigated in the future. This framework is similar to other parameter estimation frameworks (Chabiniok et al, 2011;Delingette et al, 2012;Liu and Shi, 2009;Wang et al, 2009;Xi et al, 2011), and therefore suffers from the curse of dimensionality. Although the subplex method has already helped to alleviate the problem by decomposing the high-dimensional space into subspaces, the numbers of iterations required are still large, and it will be computationally very challenging with more number of zones.…”

Section: Discussionmentioning

confidence: 91%

“…To estimate the contraction parameters, the optimization problems were solved using gradient-based algorithms on synthetic data in Sermesant et al (2006b); Sundar et al (2009), and on clinical data in Delingette et al (2012). In Delingette et al (2012), the gradient-based quasi-Newton L-BFGS-B algorithm was used.…”

Section: Derivative-free Optimizationmentioning

confidence: 99%

“…In Delingette et al (2012), the gradient-based quasi-Newton L-BFGS-B algorithm was used. As the model involves interactions between myocardial deformation, ventricular pressures, contraction stresses, and different boundary conditions, it is difficult to compute the gradient analytically without making significant simplifications which sacrifice the model integrity and thus the estimation accuracy.…”

Section: Derivative-free Optimizationmentioning

confidence: 99%

“…While efforts have been spent on estimating maximum contraction stresses (Hu et al, 2003;Chabiniok et al, 2011;Delingette et al, 2012), the estimations of contraction and relaxation rates have seldom been studied. As these rates are related to clinically important measurements such as the rates of blood pressure (Rushmer et al, 1964;Mason et al, 1971), they are important parameters which should also be estimated.…”

Section: Introductionmentioning

confidence: 99%

“…This limits the exploration of the proper objective functions and also the types of parameters to be estimated, as some objective functions are highly nonlinear with respect to the desired parameters. Therefore, only the maximum contraction stresses were estimated in Delingette et al (2012) even after some model simplifications.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Velocity-based cardiac contractility personalization from images using derivative-free optimization

Wong

Sermesant

Rhode

et al. 2015

Journal of the Mechanical Behavior of Biomedical Materials

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Model personalization is a key aspect for biophysical models to impact clinical practice, and cardiac contractility personalization from medical images is a major step in this direction. Existing gradient-based optimization approaches show promising results of identifying the maximum contractility from images, but the contraction and relaxation rates are not accounted for. A main reason is the limited choices of objective functions when their gradients are required. For complicated cardiac models, analytical evaluations of gradients are very difficult if not impossible, and finite difference approximations are computationally expensive and may introduce numerical difficulties. By removing such limitations with derivative-free optimization, we found that a velocity-based objective function can properly identify regional maximum contraction stresses, contraction rates, and relaxation rates simultaneously with intact model complexity. Experiments on synthetic data show that the parameters are better identified using the velocity-based objective function than its position-based counterpart, and the proposed framework is insensitive to initial parameters with the adopted derivative-free optimization algorithm. Experiments on clinical data show that the framework can provide personalized contractility parameters which are consistent with the underlying physiologies of the patients and healthy volunteers.

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Section: Discussionmentioning

confidence: 91%

Section: Derivative-free Optimizationmentioning

confidence: 99%

Section: Derivative-free Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Velocity-based cardiac contractility personalization from images using derivative-free optimization

Wong

Sermesant

Rhode

et al. 2015

Journal of the Mechanical Behavior of Biomedical Materials

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Personalization of Electromechanical Models of the Cardiac Ventricular Function by Heterogeneous Clinical Data Assimilation

Marchesseau¹,

Sermesant²,

Billet³

et al. 2015

Multi‐Modality Cardiac Imaging

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High‐resolution data assimilation of cardiac mechanics applied to a dyssynchronous ventricle

Balaban

Finsberg

Odland

et al. 2017

Numer Methods Biomed Eng

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The objective of this transformative action research project was to explore and develop sustainable methods to promote female empowerment through science education in rural, disadvantaged sectors of South Africa. In an attempt to achieve this we collaborated with local community members to develop and implement a contextualized science curriculum at a school in the aforementioned setting. As soon as the project was launched it became increasingly clear that although the ideology of 'empowerment through science education' seemed a promising venture, it could also be an extremely complex and often frustrating undertaking. This was especially true when working within an unfamiliar cultural setting. Numerous challenges, such as the lack of teacher motivation, malnutrition amongst the learners, and conflicts stemming from differences between the indigenous knowledge and the western concept of science, greatly impeded the delivery of quality education in the area. These challenges had to be addressed both in pedagogical and practical terms before any attempt towards libratory education could be made. This article sheds light on the complex inter-relationship between the human factor and the organizational and physical infrastructure at a school. It begins with a brief description of the local context and goes on to identify the theoretical underpinnings and chosen methodology for the project. The article concludes with a review of the complexities involved in possible attempts to initiate and foster educational and social transformations in a rural South African setting. We contend that it is essential to first be thoroughly familiar with the background, culture, and needs of any community before any attempts are made towards social justice.

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Personalization of Cardiac Motion and Contractility From Images Using Variational Data Assimilation

Cited by 45 publications

References 14 publications

Velocity-based cardiac contractility personalization from images using derivative-free optimization

Velocity-based cardiac contractility personalization from images using derivative-free optimization

Personalization of Electromechanical Models of the Cardiac Ventricular Function by Heterogeneous Clinical Data Assimilation

High‐resolution data assimilation of cardiac mechanics applied to a dyssynchronous ventricle

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