Assessment of cerebral blood flow with magnetic resonance imaging in children with sickle cell disease: A quantitative comparison with transcranial Doppler ultrasonography
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Bibliographic record
Abstract
Abstract Introduction Transcranial Doppler ultrasonography ( TCD ) is a clinical tool for stratifying ischemic stroke risk by identifying abnormal elevations in blood flow velocity ( BFV ) in the middle cerebral artery ( MCA ). However, TCD is not effective at screening for subtle neurologic injury such as silent cerebral infarcts. To better understand this disparity, we compared TCD measures of BFV with tissue‐level cerebral blood flow ( CBF ) using arterial spin‐labeling MRI in children with and without sickle cell disease, and correlated these measurements against clinical hematologic measures of disease severity. Methods TCD and MRI assessment were performed in 13 pediatric sickle cell disease patients and eight age‐matched controls. Using MRI measures of MCA diameter and territory weight, TCD measures of BFV in the MCA [cm/s] were converted into units of CBF [ml min −1 100 g −1 ] for comparison. Results There was no significant association between TCD measures of BFV in the MCA and corresponding MRI measures of CBF in patients ( r = .28, p = .39) or controls ( r = .10, p = .81). After conversion from BFV into units of CBF , a strong association was observed between TCD and MRI measures ( r = .67, p = .017 in patients, r = .86, p = .006 in controls). While BFV in the MCA showed a lack of correlation with arterial oxygen content, an inverse association was observed for CBF measurements. Conclusions This study demonstrates that BFV in the MCA cannot be used as a surrogate marker for tissue‐level CBF in children with sickle cell disease. Therefore, TCD alone may not be sufficient for understanding and predicting subtle pathophysiology in this population, highlighting the potential clinical value of tissue‐level CBF .
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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 | 0.000 | 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 it