A predictive personalised model for the left atrium

Cesare Corrado; Steven Williams; Gernot Planck; Mark O'Neill; Steven Niederer

doi:10.22489/CinC.2017.201-136

A predictive personalised model for the left atrium

Cesare Corrado^*, Steven Williams, Gernot Planck, Mark O'Neill, Steven Niederer

^*Corresponding author for this work

Biomedical Engineering Department

Medizinische Universität

Research output: Contribution to journal › Conference paper › peer-review

1 Citation (Scopus)

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Abstract

We propose an integrated modelling and clinical protocol for characterising local tissue properties in the left atrium and validate the resulting personalised models in four patient cases. We generate a personalised model from a set of measured local activation times (LATs) obtained by pacing the left atrium in the proximity of the coronary sinus with a programmed pacing protocol. We validate the model by evaluating the correlation between a set of measured LATS, obtained by pacing on the high right atrium and a set numerically computed LATs. We then estimate if the tissue is capable of sustaining an atrial fibrillation or a tachycardia by triggering a spiral wave on the computational model and then analysing the activation frequencies and the time elapsed until the termination of the aberrant activation.

Original language	English
Pages (from-to)	1-4
Number of pages	4
Journal	Computing in Cardiology
Volume	44
DOIs	https://doi.org/10.22489/CinC.2017.201-136
Publication status	Published - 1 Jan 2017
Event	44th Computing in Cardiology Conference, CinC 2017 - Rennes, France Duration: 24 Sept 2017 → 27 Sept 2017

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10.22489/CinC.2017.201-136

A Predictive Personalised Model_CORRADO_2017_GREEN AAMAccepted author manuscript, 1.32 MB

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title = "A predictive personalised model for the left atrium",

abstract = "We propose an integrated modelling and clinical protocol for characterising local tissue properties in the left atrium and validate the resulting personalised models in four patient cases. We generate a personalised model from a set of measured local activation times (LATs) obtained by pacing the left atrium in the proximity of the coronary sinus with a programmed pacing protocol. We validate the model by evaluating the correlation between a set of measured LATS, obtained by pacing on the high right atrium and a set numerically computed LATs. We then estimate if the tissue is capable of sustaining an atrial fibrillation or a tachycardia by triggering a spiral wave on the computational model and then analysing the activation frequencies and the time elapsed until the termination of the aberrant activation.",

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AU - Corrado, Cesare

AU - Williams, Steven

AU - Planck, Gernot

AU - O'Neill, Mark

AU - Niederer, Steven

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Y1 - 2017/1/1

N2 - We propose an integrated modelling and clinical protocol for characterising local tissue properties in the left atrium and validate the resulting personalised models in four patient cases. We generate a personalised model from a set of measured local activation times (LATs) obtained by pacing the left atrium in the proximity of the coronary sinus with a programmed pacing protocol. We validate the model by evaluating the correlation between a set of measured LATS, obtained by pacing on the high right atrium and a set numerically computed LATs. We then estimate if the tissue is capable of sustaining an atrial fibrillation or a tachycardia by triggering a spiral wave on the computational model and then analysing the activation frequencies and the time elapsed until the termination of the aberrant activation.

AB - We propose an integrated modelling and clinical protocol for characterising local tissue properties in the left atrium and validate the resulting personalised models in four patient cases. We generate a personalised model from a set of measured local activation times (LATs) obtained by pacing the left atrium in the proximity of the coronary sinus with a programmed pacing protocol. We validate the model by evaluating the correlation between a set of measured LATS, obtained by pacing on the high right atrium and a set numerically computed LATs. We then estimate if the tissue is capable of sustaining an atrial fibrillation or a tachycardia by triggering a spiral wave on the computational model and then analysing the activation frequencies and the time elapsed until the termination of the aberrant activation.

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AN - SCOPUS:85045129043

SN - 2325-8861

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T2 - 44th Computing in Cardiology Conference, CinC 2017

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A predictive personalised model for the left atrium

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