Non-invasive Brain Temperature Measurement in Acute Ischemic Stroke
Bibliographic record
Abstract
Selective therapeutic hypothermia in the setting of mechanical thrombectomy (MT) is promising to further improve the outcomes of large vessel occlusion stroke. A significant limitation in applying hypothermia in this setting is the lack of real-time non-invasive brain temperature monitoring mechanism. Non-invasive brain temperature monitoring would provide important information regarding the brain temperature changes during cooling, and the factors that might influence any fluctuations. This review aims to provide appraisal of brain temperature changes during stroke, and the currently available non-invasive modalities of brain temperature measurement that have been developed and tested over the past 20 years. We cover modalities including magnetic resonance spectroscopy imaging (MRSI), radiometric thermometry, and microwave radiometry, and the evidence for their accuracy from human and animal studies. We also evaluate the feasibility of using these modalities in the acute stroke setting and potential ways for incorporating brain temperature monitoring in the stroke workflow.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".