Conversion of the bronchial tree into a conforming electrode to ablate the lung nodule in a porcine model
Bibliographic record
Abstract
BACKGROUND: Radiofrequency ablation (RFA) is one of the treatment options for lung nodules. However, the need for exact delivery of the rigid metal electrode into the center of the target mass often leads to complications or suboptimal results. To overcome these limitations, a concept of conforming electrodes using a flexible material has been tested in this study. METHODS: A bronchoscopy-guided RFA (CAROL) under a temperature-controlled mode was tested in in-vivo and ex-vivo porcine lungs. Gallium-based liquid metal was used for turning the bronchial tree into temporary RF electrodes. A customized bronchoscopy-guided balloon-tipped guiding catheter (CAROL catheter) was used to make the procedure feasible under fluoroscopy imaging guidance. The computer simulation was also performed to gain further insight into the ablation results. Safety was also assessed including the liquid metal remaining in the body. RESULTS: The bronchial electrode injected from the CAROL catheter was able to turn the target site bronchial air pipe into a temporally multi-tined RF electrode. The mean volume of Gallium for each effective CAROL was 0.46 ± 0.47 ml. The ablation results showed highly efficacious and consistent results, especially in the peripheral lung. Most bronchial electrodes were also retrieved by either bronchoscopic suction immediately after the procedure or by natural expectoration thereafter. The liquid metal used in these experiments did not have any significant safety issues. Computer simulation also supports these results. CONCLUSION: The CAROL ablation was very effective and safe in porcine lungs showing encouraging potential to overcome the conventional approaches.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".