A new approach to feedback control of radiofrequency ablation systems for large coagulation zones
Bibliographic record
Abstract
Aim: The aim of this study was to investigate the feasibility of achieving relatively large coagulation zones (i.e. ≥3 cm in diameter) with radiofrequency ablation (RFA) by using a broad control system.Materials and methods: A broad control system consists of information such as (i) the area of the tumour tissue for feedback control, (ii) the set-point temperature and (iii) the control law. The proposed approach has advanced knowledge in (i) and (ii) in particular. RFA is known to be limited by tissue dehydration that occurs around the electrode, which results in impedance such that no further energy can be delivered to the tissues. We proposed the notion of “energy gate”, an area on the electrode, which is not covered by the dehydrated tissue and through which energy can still be delivered to the surrounding tissues. Given a specific size of energy gate, both (i) the area of the tissue in which the temperature is monitored and (ii) the set-point temperature were determined. A reliable finite element model or simulator for a commercially available electrode was used and the tissue surrounding the RFA electrode was divided into three areas for a comprehensive study of the issues (i) and (ii). Porcine liver tissue (30 specimens in total) and a custom-made RFA device with a RF power generator (100 W and 460 ± 30 kHz) and a Covidien cool-tip electrode (17 gauge and 30 mm exposure) were used to validate the findings regarding the area of the tissue for feedback control and the set-point temperature.Results: The size of coagulation zone achieved was maximised when the area of tissue surrounding the middle part of the active tip (i.e. Point 7) was used for feedback control and when the set-point temperature was set to 90 ^ C (this temperature is determined based on the energy gate through a trial-and-error procedure). At both 80 and 90 ^ C, the coagulation zones generated using Area II were significantly larger than that generated using Area I (p = 0.0028 and 0.0003, respectively) and Area III (P = 0.0010 and < 0.0001, respectively). A similar finding regarding the control area and set-point temperature was confirmed by the in-vitro experiment. When compared with Point a (p < 0.0001) and Point c (p < 0.0001), the largest coagulation zone (1066.7 ± 36.1 mm2) was achieved by controlling the temperature of the tissue area surrounding the middle part of the active tip (i.e. Point b) at 90 ^ C.Conclusion: The judicious selection of the control area within the biological tissue for temperature monitoring and the set-point temperature for feedback control is critical in increasing the size of the coagulation zone in the treatment of RFA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".