Models and measurements of light intensity changes during laser interstitial thermal therapy: implications for optical monitoring of the coagulation boundary location
Bibliographic record
Abstract
We have developed a multi-region spherical Monte Carlo (MC) model to simulate the dynamic changes in light intensity measured during laser interstitial thermal therapy (LITT). Model predictions were validated experimentally in tissue-simulating albumen phantoms with well-characterized optical properties that vary dynamically with LITT in a way similar to tissue. For long treatments (2.5 W, approximately 1800 s), the transient light intensity changes demonstrated better qualitative agreement with a three-region MC model (with an inner layer of fully coagulated optical properties, a middle layer of partially coagulated properties and an outer region of native properties); for short treatments (4 W, approximately 240 s), better qualitative agreement was seen with a two-region MC model (with an inner layer of fully coagulated properties and outer region of native properties). These differences were attributed to differences in coagulation formation during low- and high-powered heating regimes, respectively. At the end of heating, a three-region coagulation zone was observed for both heating schemes. Quantitatively, final light intensity changes at the end of heating were compared with changes predicted by both two- and three-region MC for the same experimentally measured coagulation size and found to agree within approximately 30% for both models. The developed MC model helps lend insight into the nature of thermal coagulation events occurring for low and high power LITT irradiation schemes.
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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".