Time-resolved near-infrared technique for bedside monitoring of absolute cerebral blood flow
Bibliographic record
Abstract
A primary focus of neurointensive care is monitoring the injured brain to detect harmful events that can impair cerebral blood flow (CBF). Since current non-invasive bedside methods can only indirectly assess blood flow, the goal of this research was to develop an optical technique for measuring absolute CBF. A time-resolved near-infrared (NIR) apparatus was built and its ability to accurately measure changes in optical properties was demonstrated in tissue-mimicking phantoms. The time-resolved system was combined with a bolus-tracking method for measuring CBF using the dye indocyanine green (ICG) as an intravascular flow tracer. Cerebral blood flow was measured in newborn piglets and for comparison, CBF was concurrently measured using a previously developed continuous-wave NIR method. Measurements were acquired with both techniques under three conditions: normocapnia, hypercapnia and following occlusion of the carotid arteries. Mean CBF values (N = 3) acquired with the TR-NIR system were 31.9 ± 11.7 ml/100g/min during occlusion, 39.7 ± 1.6 ml/100g/min at normocapnia, and 58.8 ± 9.9 ml/100g/min at hypercapnia. Results demonstrate that the developed TR-NIR technique has the sensitivity to measure changes in CBF; however, the CBF measurements were approximately 25% lower than the values obtained with the CW-NIRS technique.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".