Acute Lesion Imaging in Predicting Chronic Tissue Injury in the Ventricles.

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 (R ² = 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.
Competing Interests: NM reports receiving grant support and consulting fees from Abbott, Medtronic, Biosense Webster, Boston Scientific, and Siemens, receiving consulting fees from Preventice, and holding equity Cardiac Design. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2022 El Hajjar, Huang, Zhang, Mekhael, Noujaim, Dagher, Nedunchezhian, Pottle, Kholmovski, Ayoub, Dhorepatil, Barakat, Yamaguchi, Chelu and Marrouche.)