Effect of <i>b</i> value on contrast during diffusion‐weighted magnetic resonance imaging assessment of acute ischemic stroke
Bibliographic record
Abstract
PURPOSE: To examine the effect of varying the diffusion encoding strength (b value) on the contrast (signal difference, Delta S) between damaged and normal tissue during diffusion-weighted magnetic resonance imaging (DWI) assessment of acute ischemic stroke. MATERIALS AND METHODS: Phantoms with diffusion values approximating those expected in acutely infarcted and normal tissue were constructed from a mixture of agar and formaldehyde and imaged at varying b values (0-3000 mm(-2) second). Ten patients were imaged with multiple b values (500-2500 mm(-2) second) within 12 hours of stroke onset. RESULTS: Theoretical calculations showed that for any combination of diffusion coefficients there existed an optimal b value that was higher than the standard setting of 1000 mm(-2) second, and this was confirmed by the phantom studies. In the patients, increasing b from 1000 to 1500 mm(-2) second increased Delta S (average, 22.4%; P = 0.001), but no consistent benefit was seen at b = 2000 mm(-2) second (P = 0.408). This compared favorably with the average optimal b value of 1662 mm(- 2) second calculated from the patients. CONCLUSION: These results suggest that increasing the b value from 1000 to 1500 mm(-2) second would increase contrast between infarcted and normal tissue in the setting of acute ischemic stroke.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".