Space–time shape uncertainties in the forward and inverse problem of electrocardiography. (8th September 2021)

• Record Type: Journal Article
• Authors: Gander, Lia; Krause, Rolf; Multerer, Michael; Pezzuto, Simone
• Is Part Of: International journal for numerical methods in biomedical engineering. Volume 37:Number 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-08
• Subjects: H1/2 regularisation -- boundary integral formulation -- inverse problem of electrocardiography -- quasi‐Monte Carlo method -- space‐time shape uncertainty -- sparse quadrature; Biomedical engineering -- Periodicals; Imaging systems in medicine -- Periodicals; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 610.28
• DOI: 10.1002/cnm.3522
• Languages: English
• ISSNs: 2040-7939

Abstract

Abstract: In electrocardiography, the "classic" inverse problem is the reconstruction of electric potentials at a surface enclosing the heart from remote recordings at the body surface and an accurate description of the anatomy. The latter being affected by noise and obtained with limited resolution due to clinical constraints, a possibly large uncertainty may be perpetuated in the inverse reconstruction. The purpose of this work is to study the effect of shape uncertainty on the forward and the inverse problem of electrocardiography. To this aim, the problem is first recast into a boundary integral formulation and then discretised with a collocation method to achieve high convergence rates and a fast time to solution. The shape uncertainty of the domain is represented by a random deformation field defined on a reference configuration. We propose a periodic‐in‐time covariance kernel for the random field and approximate the Karhunen–Loève expansion using low‐rank techniques for fast sampling. The space–time uncertainty in the expected potential and its variance is evaluated with an anisotropic sparse quadrature approach and validated by a quasi‐Monte Carlo method. We present several numerical experiments on a simplified but physiologically grounded two‐dimensional geometry to illustrate the validity of the approach. The tested parametric dimension ranged from 100 up to 600. For the forward problem, the sparse quadrature is very effective. In the inverse problem, the sparse quadrature and the quasi‐Monte Carlo method perform as expected, except for the total variation regularisation, where convergence is limited by lack of regularity. We finally investigate an H 1 / 2 regularisation, which naturally stems from the boundary integral formulation, and compare it to more classical approaches. Abstract : The solution to the forward and inverse problems of electrocardiography requires a description of the torso anatomy. The latter varies over time and is source of uncertainty, since it is obtained from images with limited resolution. We study the effect of the space–time shape uncertainty on the forward and inverse solutions. The uncertainty is represented by a random deformation field with high‐dimensional Karhunen–Loève expansion. Therefore, we employ the anisotropic sparse quadrature to estimate our quantities of interest.