The use of a dispersive ground electrode with a loosely wound helical coil for interstitial radiofrequency thermal therapy
Bibliographic record
Abstract
We have developed a novel, thermal therapy device designed to improve local control of large solid tumours using heat in the range 55-90 degrees C. The device is a helical coil designed to be loosely wound inside a tumour and excited with radiofrequency energy at 27.12 MHz. This design exploits the size and uniformity of the electric fields generated by magnetic induction inside this solenoidal geometry for heating and coagulating a large target volume. The use of the electrically conductive shape memory alloy Nitinol for the coil and an external ground plane permit the minimally invasive percutaneous insertion of the coil through a single cannulating delivery needle. To demonstrate the feasibility of this device, phantom models and finite-element models using COMSOL 3.2 were used to characterize uniformity of the radial and axial ARD (absorption rate density) profiles of different monopolar coil geometries. COMSOL 3.2 was also used to calculate temperature profiles and distributions produced by these coils in a non-perfused tissue-mimicking domain following a 10 min heating period. ARD results showed that optimum radial and axial uniformities were achieved with a 0.75 cm pitch and 3 cm length for a 1.5 cm diameter coil, and a 1.4 cm pitch and 4.2 cm length for a 2 cm diameter coil. These coils were able to produce lesions in excised bovine liver of 4 cm x 4.5 cm and 3.5 cm x 6.5 cm, respectively. Predicted temperature profiles showed similar profile sizes and shapes in a non-perfused domain, with the absolute temperature rise determined by the source input to the coil. These results demonstrate the potential of this interstitial, monopolar induction coil device for heating large tumours using a single applicator delivered through a single needle insertion.
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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 | 0.000 | 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 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".