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Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search

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Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search. / Nuñez-Garcia, Marta; Camara, Oscar; O’Neill, Mark D.; Razavi, Reza; Chubb, Henry; Butakoff, Constantine.

In: Medical Image Analysis, 10.10.2018.

Research output: Contribution to journalArticle

Harvard

Nuñez-Garcia, M, Camara, O, O’Neill, MD, Razavi, R, Chubb, H & Butakoff, C 2018, 'Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search', Medical Image Analysis. https://doi.org/10.1016/j.media.2018.10.001

APA

Nuñez-Garcia, M., Camara, O., O’Neill, M. D., Razavi, R., Chubb, H., & Butakoff, C. (2018). Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search. Medical Image Analysis. https://doi.org/10.1016/j.media.2018.10.001

Vancouver

Nuñez-Garcia M, Camara O, O’Neill MD, Razavi R, Chubb H, Butakoff C. Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search. Medical Image Analysis. 2018 Oct 10. https://doi.org/10.1016/j.media.2018.10.001

Author

Nuñez-Garcia, Marta ; Camara, Oscar ; O’Neill, Mark D. ; Razavi, Reza ; Chubb, Henry ; Butakoff, Constantine. / Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search. In: Medical Image Analysis. 2018.

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@article{fe86ca08d70a4fbebdddcebdcf4d89d3,
title = "Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search",
abstract = "Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF) since the initial trigger for AF frequently originates in the pulmonary veins. A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p ",
keywords = "Ablation gap, Minimal path search, Geodesic distance, Distance transform, Atrial fibrillation, Pulmonary vein isolation",
author = "Marta Nu{\~n}ez-Garcia and Oscar Camara and O’Neill, {Mark D.} and Reza Razavi and Henry Chubb and Constantine Butakoff",
year = "2018",
month = "10",
day = "10",
doi = "10.1016/j.media.2018.10.001",
language = "English",
journal = "Medical Image Analysis",
issn = "1361-8415",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Mind the gap: quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search

AU - Nuñez-Garcia, Marta

AU - Camara, Oscar

AU - O’Neill, Mark D.

AU - Razavi, Reza

AU - Chubb, Henry

AU - Butakoff, Constantine

PY - 2018/10/10

Y1 - 2018/10/10

N2 - Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF) since the initial trigger for AF frequently originates in the pulmonary veins. A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p 

AB - Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF) since the initial trigger for AF frequently originates in the pulmonary veins. A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p 

KW - Ablation gap

KW - Minimal path search

KW - Geodesic distance

KW - Distance transform

KW - Atrial fibrillation

KW - Pulmonary vein isolation

U2 - 10.1016/j.media.2018.10.001

DO - 10.1016/j.media.2018.10.001

M3 - Article

JO - Medical Image Analysis

JF - Medical Image Analysis

SN - 1361-8415

ER -

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