Comparison of thermal damage calculated using magnetic resonance thermometry, with magnetic resonance imaging post-treatment and histology, after interstitial microwave thermal therapy of rabbit brain
Bibliographic record
Abstract
Clinical application of high-temperature thermal therapy as a treatment for solid tumours requires an accurate and close to real-time method for assessing tissue damage. Imaging methods that detect structural changes during heating may underestimate the extent of thermal damage. This is due to the occurrence of delayed damage manifested at tissue locations exposed to temperatures lower than those required to cause immediate structural changes. An alternative approach is to measure temperature and then calculate the expected damage based on the temperature history at each tissue location. Magnetic resonance (MR) imaging methods now allow temperature maps of the target and surrounding tissues to be generated in almost real-time. The aim of this work was to evaluate whether thermal damage zones calculated on the basis of MR thermometry maps measured during heating correspond to actual tissue damage as measured after treatment by histological methods and MR imaging. Four male rabbits were treated with high-temperature thermal therapy delivered in the brain by a single microwave antenna operating at 915 MHz. MR scanning was performed before, during and after treatment in a 1.5 T whole-body scanner. Temperature maps were produced using the proton resonance frequency (PRF) shift method of MR thermometry. In addition, conventional T1-weighted and T2-weighted spin-echo images were acquired after treatment. Thermal damage zones corresponding to cell death, microvascular blood flow stasis and protein coagulation were calculated using an Arrhenius analysis of the MR temperature/time course data. The calculated zones were compared with the lesions seen on histopathological examination of the brains which were removed within 6-8 h of treatment. The results showed that calculated damage zones based on MR thermometry agreed well with areas of damage as assessed using histology after heating was completed. The data suggest that real-time calculations of final expected thermal damage based on an Arrhenius analysis of MR temperature data may provide a useful method of real-time monitoring of thermal therapy when combined with conventional T2-weighted images taken after treatment.
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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 | 0.001 |
| 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".