Is Single‐View Fluoroscopy Sufficient in Guiding Cardiac Ablation Procedures?
Bibliographic record
Abstract
The CARTO XP ablation system provides real-time data on 3D, color-coded maps of the electrical activity of the heart; however, it is expensive and can only use a dedicated costly magnetic catheter per patient intervention. The purpose of our study is to shorten the duration of the radiofrequency ablation procedure and increase its efficacy by developing an affordable prototype catheter navigation system that simulates the CARTO system. To obtain 3D geometrical data from catheter locations inside the heart chamber, we acquired only single-view images using an Integris Allura fluoroscope and estimated the depth of the mapping electrode using pattern recognition techniques. Validation was performed in ideal and clinical conditions. For phantom experiment, when using a 7-French catheter, the average recovered depth error was 2.05 +/- 1.46 mm using a single image. However, when using the 8-French catheter, the average recovered depth error was 1.54 +/- 1.29 mm. In clinical experimentation, the standard error of estimate for the estimated depth was about 13.1 mm and 10.1 mm, respectively, for the posterior and lateral views. In conclusion, this paper describes our achievements and shortfalls in developing an affordable fluoroscopic navigation system to guide RF catheter ablation of cardiac arrhythmias.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".