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Acute Lesion Imaging in Predicting Chronic Tissue Injury in the Ventricles.
El Hajjar, Abdel Hadi; Huang, Chao; Zhang, Yichi; Mekhael, Mario; Noujaim, Charbel; Dagher, Lilas; Nedunchezhian, Saihariharan; Pottle, Christopher; Kholmovski, Eugene; Ayoub, Tarek; Dhorepatil, Aneesh; Barakat, Michel; Yamaguchi, Takano; Chelu, Mihail; Marrouche, Nassir.
Afiliação
  • El Hajjar AH; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Huang C; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Zhang Y; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Mekhael M; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Noujaim C; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Dagher L; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Nedunchezhian S; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Pottle C; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Kholmovski E; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Ayoub T; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
  • Dhorepatil A; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Barakat M; Tulane Research Innovation for Arrhythmia Discoveries, Tulane University School of Medicine, New Orleans, LA, United States.
  • Yamaguchi T; Department of Cardiology, PeaceHealth, Bellingham, WA, United States.
  • Chelu M; Department of Cardiology, Saga University, Saga, Japan.
  • Marrouche N; Baylor Heart Clinic, Baylor College of Medicine, Houston, TX, United States.
Front Cardiovasc Med ; 8: 791217, 2021.
Article em En | MEDLINE | ID: mdl-35155604
BACKGROUND: Chronic lesion formation after cardiac tissue ablation is an important indicator for procedural outcome. Moreover, there is a lack of knowledge regarding the features that predict chronic lesion formation. OBJECTIVE: The aim of this study is to determine whether acute lesion visualization using late gadolinium enhanced magnetic resonance imaging (LGE-MRI) can reliably predict chronic lesion size. METHODS: Focal lesions were created in left and right ventricles of canine models using either radiofrequency (RF) ablation or cryofocal ablation. Multiple ablation parameters were used. The first LGE-MRI was acquired within 1-5 h post-ablation and the second LGE-MRI was obtained 47-82 days later. Corview software was used to perform lesion segmentations and size calculations. RESULTS: Fifty-Five lesions were created in different locations in the ventricles. Chronic volume size decreased by a mean of 62.5 % (95% CI 58.83-67.97, p < 0.0005). Similar regression of lesion volume was observed regardless of ablation location (p = 0.32), ablation technique (p = 0.94), duration (p = 0.37), power (p = 0.55) and whether lesions were connected or not (p = 0.35). There was no significant difference in lesion volume reduction assessed at 47-54 days and 72-82 days after ablation (p = 0.31). Chronic lesion volume was equal to 0.32 of the acute lesion volumes (R2 = 0.75). CONCLUSION: Chronic tissue injury related to catheter ablation can be reliably modeled as a linear function of the acute lesion volume as assessed by LGE-MRI, regardless of the ablation parameters.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article