The potential of raman spectroscopy as a monitoring tool for thermal therapy
Bibliographic record
Abstract
Laser Interstitial thermal Therapy (LITT) is a minimally invasive technique for treating localized solid tumors through heating with light. LITT is not routinely employed in a clincal setting due to difficulties in real-time monitoring of tissue heating. This work investigates the feasibility of Raman Spectroscopy (RS) to monitor thermal therapies. RS has the ability to detect changes in the seconcary structure of proteins, and may prove useful as an indicator of tissue coagulation in real-time during thermal therapy. Tissue equivalent albumen phantoms were heated in a water bath and bovine muscle samples where heated in a water bath and through laser photocoagulation. Raman spectra were acquired after heating and increases in the overall Raman intensity and shifts in major band locations were observed after heating. Correlations between Raman intensity and thermal dose were also observed. These results indicate that RS may be employable as a real-time monitoring tool for LITT.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".