Novel systematic processing of cardiac magnetic resonance imaging identifies target regions associated with infarct-related ventricular tachycardia.

Ventricular tachycardia imaging processing magnetic resonance imaging radiofrequency ablation

Journal

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
ISSN: 1532-2092
Titre abrégé: Europace
Pays: England
ID NLM: 100883649

Informations de publication

Date de publication:
19 Sep 2024
Historique:
received: 27 05 2024
revised: 16 07 2024
accepted: 17 09 2024
medline: 20 9 2024
pubmed: 20 9 2024
entrez: 19 9 2024
Statut: aheadofprint

Résumé

There is lack of agreement on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging processing for guiding ventricular tachycardia (VT) ablation. We aim at developing and validating a systematic processing approach on LGE-CMR images to identify VT corridors that contain critical VT isthmus sites. Translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance. Clinical validation was conducted in a multicenter series of 33 patients with ischemic cardiomyopathy undergoing VT ablation. Three-dimensional CMR-LGE images were processed using systematic scanning of 15 signal intensity (SI) cut-off ranges to obtain surface visualization of all potential VT corridors. Analysis and comparisons of imaging and electrophysiological data were performed in individuals with full electrophysiological characterization of the isthmus sites of at least one VT morphology. In both the experimental pig model and patients undergoing VT ablation, all the electrophysiologically-defined isthmus sites (n=11 and n=19, respectively) showed overlapping regions with CMR-based potential VT corridors. Such imaging-based VT corridors were less specific than electrophysiologically-guided ablation lesions at critical isthmus sites. However, an optimized strategy using the 7 most relevant SI cut-off ranges among patients showed an increase in specificity compared to using 15 SI cut-off ranges (70% vs 62%, respectively), without diminishing the capability to detect VT isthmus sites (sensitivity 100%). Systematic imaging processing of LGE-CMR sequences using several SI cut-off ranges may improve and standardize procedure planning to identify VT isthmus sites.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
There is lack of agreement on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging processing for guiding ventricular tachycardia (VT) ablation. We aim at developing and validating a systematic processing approach on LGE-CMR images to identify VT corridors that contain critical VT isthmus sites.
METHODS METHODS
Translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance. Clinical validation was conducted in a multicenter series of 33 patients with ischemic cardiomyopathy undergoing VT ablation. Three-dimensional CMR-LGE images were processed using systematic scanning of 15 signal intensity (SI) cut-off ranges to obtain surface visualization of all potential VT corridors. Analysis and comparisons of imaging and electrophysiological data were performed in individuals with full electrophysiological characterization of the isthmus sites of at least one VT morphology.
RESULTS RESULTS
In both the experimental pig model and patients undergoing VT ablation, all the electrophysiologically-defined isthmus sites (n=11 and n=19, respectively) showed overlapping regions with CMR-based potential VT corridors. Such imaging-based VT corridors were less specific than electrophysiologically-guided ablation lesions at critical isthmus sites. However, an optimized strategy using the 7 most relevant SI cut-off ranges among patients showed an increase in specificity compared to using 15 SI cut-off ranges (70% vs 62%, respectively), without diminishing the capability to detect VT isthmus sites (sensitivity 100%).
CONCLUSIONS CONCLUSIONS
Systematic imaging processing of LGE-CMR sequences using several SI cut-off ranges may improve and standardize procedure planning to identify VT isthmus sites.

Identifiants

pubmed: 39298664
pii: 7762150
doi: 10.1093/europace/euae244
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.

Auteurs

Alba Ramos-Prada (A)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Fundación Interhospitalaria para la Investigación Cardiovascular (FIC). Madrid, Spain.

Andrés Redondo-Rodríguez (A)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.

Ivo Roca-Luque (I)

Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Hospital Clínic, Department of Cardiology. Barcelona, Spain.

Andreu Porta-Sánchez (A)

Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Hospital Clínic, Department of Cardiology. Barcelona, Spain.

Rachel M A Ter Bekke (RMA)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center. Department of Cardiology. Maastricht, The Netherlands.

Jorge G Quintanilla (JG)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Javier Sánchez-González (J)

Philips Healthcare Iberia. Madrid, Spain.

Rafael Peinado (R)

Hospital Universitario La Paz, Cardiology department. Madrid, Spain.

Jose Luis Merino (JL)

Hospital Universitario La Paz, Cardiology department. Madrid, Spain.

Matthijs Cluitmans (M)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University. Maastricht, The Netherlands.
Philips Research. Eindhoven, The Netherlands.

Robert J Holtackers (RJ)

Cardiovascular Research Institute Maastricht (CARIM), Maastricht University. Maastricht, The Netherlands.
Maastricht University Medical Center. Department of Radiology & Nuclear Medicine. Maastricht, The Netherlands.

Manuel Marina-Breysse (M)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.

Carlos Galán-Arriola (C)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.

Daniel Enríquez-Vázquez (D)

Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Unidad de Insuficiencia Cardíaca Avanzada y Trasplante Cardiaco, Department of cardiology, Complexo Hospitalario Universitario A Coruña. Instituto de Investigación Biomédica de A Coruña (INIBIC). A Coruña, Spain.

Sara Vázquez-Calvo (S)

Hospital Clínic, Department of Cardiology. Barcelona, Spain.

José Manuel Alfonso-Almazán (JM)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.

Gonzalo Pizarro (G)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Hospital Ruber Juan Bravo Quiron Salud, UEM, Cardiology Department. Madrid, Spain.

Borja Ibáñez (B)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
IIS-University Hospital Fundación Jiménez Díaz, Cardiology department. Madrid, Spain.

Juan José González-Ferrer (JJ)

Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Ricardo Salgado-Aranda (R)

Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Victoria Cañadas-Godoy (V)

Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

David Calvo (D)

Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Julián Pérez-Villacastín (J)

Fundación Interhospitalaria para la Investigación Cardiovascular (FIC). Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Nicasio Pérez-Castellano (N)

Fundación Interhospitalaria para la Investigación Cardiovascular (FIC). Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

David Filgueiras-Rama (D)

Centro Nacional de Investigaciones Cardiovasculares (CNIC), Novel Arrhythmogenic Mechanisms Program. Madrid, Spain.
Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV). Madrid, Spain.
Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Cardiovascular Institute. Madrid, Spain.

Classifications MeSH