Streamlined quantitative BOLD for detecting visual stimulus-induced changes in oxygen extraction fraction in healthy participants: toward clinical application in human glioma
Bibliographic record
Abstract
Abstract Objective Monitoring brain oxygenation is critical in brain tumors, as low oxygenation influences tumor growth, pathological angiogenesis, and treatment resistance. This study examined the ability of the streamlined quantitative (sq)BOLD MRI technique to detect oxygenation changes in healthy individuals, as well as its potential application in a clinical setting. Methods We used the asymmetric spin echo (ASE) technique with FLAIR preparation, along with model-based Bayesian inference to quantify the reversible transverse relaxation rate ( R 2 ' ) and oxygen extraction fraction (OEF) across the brain at baseline and during visual stimulation in eight healthy participants at 3T; and two patients with glioma at rest only. Results Comparing sqBOLD-derived parameters between baseline and visual stimulation revealed a decrease in OEF from 0.56 ± 0.09 at baseline to 0.54 ± 0.07 at the activated state ( p = 0.04, paired t test) within a functional localizer-defined volume of interest, and a decline in R 2 ' from 6.5 ± 1.3s −1 at baseline to 6.2 ± 1.4s −1 at the activated state ( p = 0.006, paired t test) in the visual cortex. Conclusion The sqBOLD technique is sensitive enough to detect and quantify changes in oxygenation in the healthy brain and shows potential for integration into clinical settings to provide valuable information on oxygenation in glioma.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".