A Technique for Measuring Anisotropy in Atrial Conduction to Estimate Conduction Velocity and Atrial Fibre Direction

Caroline H Roney; John Whitaker; Iain James Wyness Sim; Louisa Jane O'Neill; Rahul Kumar Mukherjee; Orod Razeghi; Edward Vigmond; Matthew Wright; Mark O'Neill; Steven E Williams; Steven A Niederer

doi:10.1016/j.compbiomed.2018.10.019

A Technique for Measuring Anisotropy in Atrial Conduction to Estimate Conduction Velocity and Atrial Fibre Direction

Caroline H Roney, John Whitaker, Iain James Wyness Sim, Louisa Jane O'Neill, Rahul Kumar Mukherjee, Orod Razeghi, Edward Vigmond, Matthew Wright, Mark O'Neill, Steven E Williams, Steven A Niederer

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Abstract

Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. Methods: We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). Results: Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20 degrees. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. Conclusions: We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.

Original language	English
Pages (from-to)	278-290
Journal	Computers in Biology and Medicine
Volume	104
Early online date	1 Nov 2018
DOIs	https://doi.org/10.1016/j.compbiomed.2018.10.019
Publication status	Published - Jan 2019

Keywords

Conduction Velocity
Anisotropy
Atrial Fibres
Atrial fibrillation
Fibrosis

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10.1016/j.compbiomed.2018.10.019

A Technique for Measuring_RONEY_Accepted17October2018_GREEN AAMAccepted author manuscript, 9.87 MBLicence: CC BY-NC-ND

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Roney, C. H., Whitaker, J., Sim, I. J. W., O'Neill, L. J., Mukherjee, R. K., Razeghi, O., Vigmond, E., Wright, M., O'Neill, M., Williams, S. E., & Niederer, S. A. (2019). A Technique for Measuring Anisotropy in Atrial Conduction to Estimate Conduction Velocity and Atrial Fibre Direction. Computers in Biology and Medicine, 104, 278-290. https://doi.org/10.1016/j.compbiomed.2018.10.019

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title = "A Technique for Measuring Anisotropy in Atrial Conduction to Estimate Conduction Velocity and Atrial Fibre Direction",

abstract = "Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. Methods: We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). Results: Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20 degrees. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. Conclusions: We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.",

keywords = "Conduction Velocity, Anisotropy, Atrial Fibres, Atrial fibrillation, Fibrosis",

author = "Roney, {Caroline H} and John Whitaker and Sim, {Iain James Wyness} and O'Neill, {Louisa Jane} and Mukherjee, {Rahul Kumar} and Orod Razeghi and Edward Vigmond and Matthew Wright and Mark O'Neill and Williams, {Steven E} and Niederer, {Steven A}",

year = "2019",

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doi = "10.1016/j.compbiomed.2018.10.019",

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AU - Roney, Caroline H

AU - Whitaker, John

AU - Sim, Iain James Wyness

AU - O'Neill, Louisa Jane

AU - Mukherjee, Rahul Kumar

AU - Razeghi, Orod

AU - Vigmond, Edward

AU - Wright, Matthew

AU - O'Neill, Mark

AU - Williams, Steven E

AU - Niederer, Steven A

PY - 2019/1

Y1 - 2019/1

N2 - Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. Methods: We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). Results: Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20 degrees. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. Conclusions: We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.

AB - Cardiac conduction properties exhibit large variability, and affect patient-specific arrhythmia mechanisms. However, it is challenging to clinically measure conduction velocity (CV), anisotropy and fibre direction. Our aim is to develop a technique to estimate conduction anisotropy and fibre direction from clinically available electrical recordings. Methods: We developed and validated automated algorithms for estimating cardiac CV anisotropy, from any distribution of recording locations on the atrial surface. The first algorithm is for elliptical wavefront fitting to a single activation map (method 1), which works well close to the pacing location, but decreases in accuracy further from the pacing location (due to spatial heterogeneity in the conductivity and fibre fields). As such, we developed a second methodology for measuring local conduction anisotropy, using data from two or three activation maps (method 2: ellipse fitting to wavefront propagation velocity vectors from multiple activation maps). Results: Ellipse fitting to CV vectors from two activation maps (method 2) leads to an improved estimation of longitudinal and transverse CV compared to method 1, but fibre direction estimation is still relatively poor. Using three activation maps with method 2 provides accurate estimation, with approximately 70% of atrial fibres estimated within 20 degrees. We applied the technique to clinical activation maps to demonstrate the presence of heterogeneous conduction anisotropy, and then tested the effects of this conduction anisotropy on predicted arrhythmia dynamics using computational simulation. Conclusions: We have developed novel algorithms for calculating CV and measuring the direction dependency of atrial activation to estimate atrial fibre direction, without the need for specialised pacing protocols, using clinically available electrical recordings.

KW - Conduction Velocity

KW - Anisotropy

KW - Atrial Fibres

KW - Atrial fibrillation

KW - Fibrosis

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DO - 10.1016/j.compbiomed.2018.10.019

M3 - Article

SN - 0010-4825

VL - 104

SP - 278

EP - 290

JO - Computers in Biology and Medicine

JF - Computers in Biology and Medicine

ER -

A Technique for Measuring Anisotropy in Atrial Conduction to Estimate Conduction Velocity and Atrial Fibre Direction

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