Abstract Fri007: Ventricular Tachycardia Ablation Using MRI Guidance: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The identification of ventricular tachycardia (VT) substrate is crucial for optimizing the success of VT ablation. Recently, multi-modality imaging has gained interest in VT substrate identification before ablation. Objective: This study aims to compare VT recurrence and all-cause mortality in patients undergoing MRI-guided versus MRI-aided VT ablation. Methods: A systematic literature review was conducted from inception until November 30, 2024, following PRISMA guidelines. Two independent reviewers screened studies meeting the following inclusion criteria: VT due to ischemic (ICM) or non-ischemic cardiomyopathy (NICM), MRI-guided ablation (MRI data integrated with electroanatomic mapping), or MRI-aided ablation (MRI reviewed by radiologists and electrophysiologists), age >18 years, and clinical trials or observational studies. Primary endpoints included VT recurrence and all-cause mortality. A stratified subgroup analysis for ICM and NICM was performed. Event rates were estimated using a generic variance random-effects model (CMA IV), with heterogeneity assessed via Cochrane’s Q-statistic (I2>75% indicating high heterogeneity) and study quality evaluated using the Newcastle-Ottawa Scale. Results: Fifteen studies (N=565, MRI-guided: n=238; MRI-aided: n=327) were included, with a mean follow-up of 24 months. VT recurrence was 25% (CI: 15%-38%, I2=41%, p=0.012) and all-cause mortality was 5.7% (CI: 2.5%-13%, I2=0%, p=0.64) in the MRI-guided group. Subgroup analysis showed VT recurrence rates of 27% in ICM (CI: 17%-40%, I2=11%, p=0.342) and 35% in NICM (CI: 18%-56%, I2=0%, p=0.963). In the MRI-aided group, VT recurrence was 29% (CI: 18%-45%, I2=69%, p=0.04) and all-cause mortality was 4.2% (CI: 1.5%-11%, I2=0%, p=0.669). Subgroup analysis showed VT recurrence of 46.5% in ICM (CI: 29%-65%, I2=37%, p=0.205) and 41% in NICM (CI: 23%-63%, I2=74%, p=0.004). Study quality ranged from moderate to high. Conclusion: MRI-guided VT ablation is associated with lower VT recurrence rates compared to MRI-aided VT ablation, while all-cause mortality remains similar between both techniques. Stratified analysis suggests that MRI-guided VT ablation may be particularly beneficial in reducing VT recurrence in the ICM subgroup.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".