Real-time magnetic resonance-guided radiofrequency ablation and lesion evaluation in an magnetic resonance-compatible isolated beating pig heart platform
Bibliographic record
Abstract
Background: Interventional cardiovascular magnetic resonance imaging (MRI) offers real-time, radiation-free guidance for complex procedures such as myocardial ablation, marking a promising advance in electrophysiology. However, further development is limited by challenges in magnetic resonance (MR)-compatible instrument testing, MRI sequence validation, and accurate correlation with histopathology, hindered by the limitations of in vivo tissue evaluation. Objective: This study investigated the feasibility of real-time MR-guided radiofrequency (RF) ablation in an MR-compatible isolated beating pig heart platform and characterized ablation lesions using MRI and histopathology. Methods: A heart from a pig slaughtered for human consumption was prepared under regulatory guidelines and connected to a custom-built, MR-compatible perfusion platform supporting left ventricular function in both Langendorff and working modes. Autologous heparinized blood circulated at physiological pressures and temperatures. MR-guided catheter navigation and RF ablation were performed on a Philips 3T scanner using active catheter tracking. Native T1 and T2 mapping were acquired before and after ablation. Lesions were confirmed by histologic analysis. Results: RF ablation (50 W, 60 seconds) was successfully performed at 5 left ventricular sites. MRI showed focal reductions in T1 (936 ± 80 ms) surrounded by elevated T1 (1357 ± 18 ms) and T2 values (86 ± 10 ms) compared with nonablated myocardium (T1 1192 ± 26 ms; T2 66 ± 6 ms), consistent with necrosis and edema. Histology confirmed a necrotic core with a surrounding rim showing contraction band necrosis and erythrocyte extravasation. Conclusion: This study demonstrates the feasibility of real-time MR-guided ablation in a beating pig heart platform. The setup allows high-resolution lesion assessment and histologic correlation, supporting future developments in MR-guided therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".