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Universal atrial coordinates applied to visualisation, registration and construction of patient specific meshes

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arxiv 1810.06630 v1 pith:XKSR6O6T submitted 2018-10-15 physics.med-ph q-bio.TO

classification physics.med-phq-bio.TO
keywords atrialdatapatientcoordinatespecificsystemweremesh
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Integrating spatial information about atrial physiology and anatomy in a single patient from multimodal datasets, as well as generalizing these data across patients, requires a common coordinate system. In the atria, this is challenging due to the complexity and variability of the anatomy. We aimed to develop and validate a universal atrial coordinate system for the following applications: combination and assessment of multimodal data; comparison of spatial data across patients; 2D visualization; and construction of patient specific geometries to test mechanistic hypotheses. Left and right atrial LGE-MRI data were segmented and meshed. Two coordinates were calculated for each atrium by solving Laplace's equation, with boundary conditions assigned using five landmark points. The coordinate system was used to map spatial information between atrial meshes, including atrial anatomic structures and fibre directions from a reference geometry. Average error in point transfer from a source mesh to a destination mesh and back again was less than 6% of the average mesh element edge length. Scalar mapping from electroanatomic to MRI geometries was compared to an affine registration technique (mean difference in bipolar voltage: <10% of voltage range). Patient specific meshes were constructed using UACs and phase singularity density maps from arrhythmia simulations were visualised in 2D. We have developed a universal atrial coordinate system allowing automatic registration of imaging and electroanatomic mapping data, 2D visualisation, and patient specific model creation, using just five landmark points.

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  1. An efficient end-to-end computational framework for the generation of ECG calibrated volumetric models of human atrial electrophysiology

    math.NA 2025-02 conditional novelty 7.0 of 10

    An end-to-end workflow automatically generates volumetric biatrial models and fast ECG P-wave simulations from patient CT scans, demonstrated on 50 AF patients.

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