Investigations of hypoxia‐induced deoxyhemoglobin as a contrast agent for cerebral perfusion imaging
Bibliographic record
Abstract
The assessment of resting perfusion measures (mean transit time, cerebral blood flow, and cerebral blood volume) with magnetic resonance imaging currently requires the presence of a susceptibility contrast agent such as gadolinium. Here, we present an initial comparison between perfusion measures obtained using hypoxia-induced deoxyhemoglobin and gadolinium in healthy study participants. We hypothesize that resting cerebral perfusion measures obtained using precise changes of deoxyhemoglobin concentration will generate images comparable to those obtained using a clinical standard, gadolinium. Eight healthy study participants were recruited (6F; age 23-60). The study was performed using a 3-Tesla scanner with an eight-channel head coil. The experimental protocol consisted of a high-resolution T1-weighted scan followed by two BOLD sequence scans in which each participant underwent a controlled bolus of transient pulmonary hypoxia, and subsequently received an intravenous bolus of gadolinium. The resting perfusion measures calculated using hypoxia-induced deoxyhemoglobin and gadolinium yielded maps that looked spatially comparable. There was no statistical difference between methods in the average voxel-wise measures of mean transit time, relative cerebral blood flow and relative cerebral blood volume, in the gray matter or white matter within each participant. We conclude that perfusion measures generated with hypoxia-induced deoxyhemoglobin are spatially and quantitatively comparable to those generated from a gadolinium injection in the same healthy participant.
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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 | 0.001 | 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".