Multiparameter optimization of nonuniform passive diffusion properties for creating coarse-grained equivalent models of cardiac propagation
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Computers in biology and medicine ; vol. 138.Éditeur·s
ElsevierAffiliation
Résumé·s
The arrhythmogenic role of discrete cardiac propagation may be assessed by comparing discrete
(fine-grained) and equivalent continuous (coarse-grained) models. We aim to develop an optimization algorithm for estimating the smooth conductivity field that best reproduces the diffusion
properties of a given discrete model. Our algorithm iteratively adjusts local conductivity of
the coarse-grained continuous model by simulating passive diffusion from white noise initial
conditions during 3 to 10 ms and computing the root mean square error with respect to the
discrete model. The coarse-grained conductivity field was interpolated from up to 300 evenly
spaced control points. We derived an approximate formula for the gradient of the cost function
that required (in two dimensions) only two additional simulations per iteration regardless of the
number of estimated parameters. Conjugate gradient solver facilitated simultaneous optimization
of multiple conductivity parameters. The method was tested in rectangular anisotropic tissues
with uniform and nonuniform conductivity (slow regions with sinusoidal profile) and random
diffuse fibrosis, as well as in a monolayer interconnected cable model of the left atrium with
spatially-varying fibrosis density. Comparison of activation maps served as validation. The
results showed that after convergence the errors in activation time were <1 ms for rectangular
geometries and 1-3 ms in the atrial model. Our approach based on the comparison of passive
properties (< 10 ms simulation) avoids performing active propagation simulations (> 100 ms)
at each iteration while reproducing activation maps, with possible applications to investigating
the impact of microstructure on arrhythmias.