Assessment of Cerebrovascular Reactivity Using <scp>CO<sub>2</sub>‐BOLD MRI</scp>: A 15‐Year, Single Center Experience
Bibliographic record
Abstract
Background Cerebrovascular reactivity (CVR) is a measure of the change in cerebral blood flow (CBF) in response to a vasoactive challenge. It is a useful indicator of the brain's vascular health. Purpose To evaluate the factors that influence successful and unsuccessful CVR examinations using precise arterial and end‐tidal partial pressure of CO 2 control during blood oxygen level–dependent (BOLD) MRI. Study Type Retrospective. Subjects Patients that underwent a CVR between October 2005 and May 2021 were studied (total of 1162 CVR examinations). The mean (±SD) age was 46.1 (±18.8) years, and 352 patients (43%) were female. Field Strength/Sequence 3 T; T1‐weighted images, T2*‐weighed two‐dimensional gradient‐echo sequence with standard echo‐planar readout. Assessment Measurements were obtained following precise hypercapnic stimuli using BOLD MRI as a surrogate of CBF. Successful CVR examinations were defined as those where: 1) patients were able to complete CVR testing, and 2) a clinically useful CVR map was generated. Unsuccessful examinations were defined as those where patients were not able to complete the CVR examination or the CVR maps were judged to be unreliable due to, for example, excessive head motion, and poor P ET CO 2 targeting. Statistical Analysis Successful and unsuccessful CVR examinations between hypercapnic stimuli, and between different patterns of stimulus were compared with Chi‐Square tests. Interobserver variability was determined by using the intraclass correlation coefficient ( P < 0.05 is significant). Results In total 1115 CVR tests in 662 patients were included in the final analysis. The success rate of generating CVR maps was 90.8% (1012 of 1115). Among the different hypercapnic stimuli, those containing a step plus a ramp protocol was the most successful (95.18%). Among the unsuccessful examinations (9.23%), most were patient related (89.3%), the most common of which was difficulty breathing. Data Conclusion CO 2 ‐BOLD MRI CVR studies are well tolerated with a high success rate. Evidence Level 4 Technical Efficacy Stage 3
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".