Imaging phenotypes and substrates in ventricular tachycardia.
This review reframes ventricular tachycardia substrate assessment away from scar burden as a single number and toward imaging phenotype — ischemic scar, nonischemic fibrosis, inflammatory injury, and fibrofatty remodeling each carry different mechanisms and different ablation implications.
The authors argue that substrate location, depth, tissue composition, and spatial distribution, characterized by CMR and increasingly by multimodality imaging, should shape procedural strategy and follow-up rather than being collapsed into a percentage of LV mass.
The framework is sensible and aligns with where the electrophysiology field has been drifting, but this is expert synthesis, not comparative outcome data.
No randomized evidence yet shows that phenotype-directed ablation planning improves freedom from VT recurrence over standard voltage-mapped approaches.
Ventricular tachycardia (VT) remains challenging, as the underlying substrate is heterogeneous and not adequately described by scar burden alone. Imaging is increasingly used to identify structural heart disease, characterize myocardial abnormality, and support VT ablation planning. Distinct imaging findings reflect specific myocardial phenotypes and substrate architectures, such as ischemic scar, nonischemic fibrosis, inflammatory injury, and fibrofatty remodelling. These phenotypes do not represent the same arrhythmic substrate and do not carry the same implications for mechanism, procedural strategy, or follow-up. This review discusses VT in terms of imaging phenotype and substrate rather than scar alone. It also summarizes how imaging can define substrate location, depth, tissue composition, and spatial distribution, and how this may improve understanding of the arrhythmic ventricle. The therapeutic implications of this framework are then discussed, including relevance for treatment planning, interpretation of treatment effect, and assessment of recurrence. Finally, current limitations and future directions of imaging-based substrate assessment in VT are addressed.
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