Towards quantitative assessment of cerebrovascular autoregulation in human neonates using ultrafast ultrasound imaging
Bibliographic record
Abstract
Newborns with congenital heart diseases requiring cardiopulmonary bypass (CPB) are at risk of neurodevelopmental impairment. The impact of deep hypothermia cardiopulmonary bypass (DH-CPB) on cerebrovascular autoregulation (CAR) that controls brain perfusion in the presence of blood pressure variation is not well understood. Recently, ultrafast power Doppler (UPD) showed potential to study CAR in neonates based on cerebral blood volume (CBV). However, since CAR relies mainly on arterial vasoconstriction/vasodilation, monitoring of brain perfusion variation based on CBV requires the discrimination of arterial from venous CBV. This study aims to use UPD combined with an algorithm for the discrimination of arteries and veins to monitor CAR during DH-CPB in neonates. Transfontanellar ultrafast power Doppler was performed in two groups of newborns: those undergoing deep hypothermic cardiopulmonary bypass with circulatory arrest (18-20 °C, n = 6, "DH group") and those undergoing full-flow CPB at mild hypothermia (32-34 °C, n = 6, "non-DH group"). Blood flow directionality was used to differentiate arterial compartments of CBV from venous CBV in specific brain regions where arterial and venous flows exhibit opposite directions. To study CAR, a linear mixed effect model was used to find the association between arterial CBV and mean arterial blood pressure (MAP). In the "non-DH group", we found a negative association between arterial CBV and MAP, indicating that an increase in MAP is associated with a decrease in arterial CBV (slope = -0.020 [Formula: see text], p = 0.047). Conversely, in the "DH group" no significant association was found such that arterial CBV remained stable as MAP increased (p = 0.314). We interpret the reduction in arterial CBV with increasing MAP in the "non-DH group" as an active arterial vasoconstriction triggered by CAR, whereas the lack of variation of arterial CBV in the DH group suggests impaired CAR response. Our findings highlight the potential of ultrafast ultrasound imaging for intra-operative CAR monitoring, paving the way for a better understanding of the impact of different types of CPB on cerebral perfusion.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".