Study of flow effects on temperature-controlled radio-frequency ablation using phantom experiments and forward simulations
Bibliographic record
Abstract
Abstract Purpose Blood perfusion is known to add variability to hepatic radiofrequency ablation (RFA) treatment outcomes. Simulation-assisted treatment planning taking into account blood perfusion may solve this problem in the future. Hence, this study aims to study perfusion effects on RFA in a controlled environment and to compare the outcome to a prediction made using finite volume simulations. Methods Ablation zones were induced in tissue-mimicking, thermochromic ablation phantoms with a single flow channel, using a RF generator with needle temperature controlled power delivery and a monopolar needle electrode. Channel radius and saline flow rate were varied and the impact of saline flow on the ablated cross-sectional area, on a potential occurrence of directional effects as well as on the delivered generator power input was studied. Finite-volume simulations reproducing the experimental geometry, flow conditions and generator power input were conducted in a second step and compared to the experimental ablation outcomes. Results Vessels of different radii affected the ablation result in different manners. For the channel radius of 0.275 mm both the ablated area and energy input reduced with increasing flow rate. For radius 0.9 mm the ablated area reduced with increasing flow rate but the energy input increased. An increasing area and energy input were observed towards larger flow rates for the channel radius of 2.3 mm. Directional effects, i.e., shrinking of the lesion upstream of the needle and an extension thereof downstream, were observed only for the smallest channel radius. The simulations qualitatively confirmed these observations. When using the simulations to make a prediction of ablation outcomes with flow, the mean absolute error between experimental and predicted ablation outcomes was reduced from 23% to 12% as compared to neglecting flow effects. Conclusion Simulations can improve the prediction of RFA ablation regions in the presence of various blood flow effects. Our findings therefore underline the potential of simulation-assisted, patient-individual RFA treatment planning and guidance for the prediction of RFA outcomes in the presence of blood flow. Additional comments -Teresa Nolte and Nikhil Vaidya contributed equally to this work. -Volkmar Schulz and Karen Veroy contributed equally to this work. -A single reference experiment, i.e., not using a flow channel, and the image in the upper left corner of Figure 4 were included into a publication submitted to Int. J. Hyperthermia for model validation purposes.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".