Approaches to Brain Stress Testing: BOLD Magnetic Resonance Imaging with Computer-Controlled Delivery of Carbon Dioxide
Bibliographic record
Abstract
BACKGROUND: An impaired vascular response in the brain regionally may indicate reduced vascular reserve and vulnerability to ischemic injury. Changing the carbon dioxide (CO(2)) tension in arterial blood is commonly used as a cerebral vasoactive stimulus to assess the cerebral vascular response, changing cerebral blood flow (CBF) by up to 5-11 percent/mmHg in normal adults. Here we describe two approaches to generating the CO(2) challenge using a computer-controlled gas blender to administer: i) a square wave change in CO(2) and, ii) a ramp stimulus, consisting of a continuously graded change in CO(2) over a range. Responses were assessed regionally by blood oxygen level dependent (BOLD) magnetic resonance imaging (MRI). METHODOLOGY/PRINCIPAL FINDINGS: We studied 8 patients with known cerebrovascular disease (carotid stenosis or occlusion) and 2 healthy subjects. The square wave stimulus was used to study the dynamics of the vascular response, while the ramp stimulus assessed the steady-state response to CO(2). Cerebrovascular reactivity (CVR) maps were registered by color coding and overlaid on the anatomical scans generated with 3 Tesla MRI to assess the corresponding BOLD signal change/mmHg change in CO(2), voxel-by-voxel. Using a fractal temporal approach, detrended fluctuation analysis (DFA) maps of the processed raw BOLD signal per voxel over the same CO(2) range were generated. Regions of BOLD signal decrease with increased CO(2) (coded blue) were seen in all of these high-risk patients, indicating regions of impaired CVR. All patients also demonstrated regions of altered signal structure on DFA maps (Hurst exponents less than 0.5; coded blue) indicative of anti-persistent noise. While 'blue' CVR maps remained essentially stable over the time of analysis, 'blue' DFA maps improved. CONCLUSIONS/SIGNIFICANCE: This combined dual stimulus and dual analysis approach may be complementary in identifying vulnerable brain regions and thus constitute a regional as well as global brain stress test.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".