Ex-Vivo and In-Vivo Studies in a Porcine Model for Experimental Validation of an Embedded System Designed for Radiofrequency Ablation of Hepatocellular Carcinoma
Bibliographic record
Abstract
The Hepatocellular Carcinoma is the main cause of morbidity and mortality in the world related to primary liver cancer. One of the principal treatment for hepatocellular cancer and effective clinical outcomes is Radiofrequency Ablation (RFA). In Brazil, the commercial equipments used in RFA are expensive and it isn't open technology. One problem during the RFA procedure is the thermal lesion volume estimation because parameters such as temperature or impedance are not fully controlled in the ablation zone, generating an uncertainty in the surgical procedure. This paper presents prototype validation based on experimental ablation protocol applied in exvivo and in-vivo tests on porcine liver of an RFA embedded system for the treatment of primary liver cancer, based on experimental results, calculating area and volume in the ablation zone. Using the signals of temperature and bioimpedance on porcine liver and the data processing in a microcontroller, it controls the power of a custom radiofrequency generator designed up to 50 W and frequency of 400 kHz, this energy is applied across an umbrella-shaped RF electrode. The data are sent by RS232 protocol, showed on LCD screen and sent to a computer for later analysis. Finally, it was possible to validate a hardware prototype with low-cost and low-power applied to thermal ablation of liver tumors.
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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".