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Abstract 4136290: Toward Quantitative Assessment of Cerebrovascular Autoregulation in Neonates using Ultrafast Ultrasound Power Doppler

2024· article· en· W4404302501 on OpenAlexaff
Nikan Fakhari, Julien Aguet, Minh Nguyen, Luc Mertens, Lynn Crawford Lean, Christoph Haller, David Barron, John G. Sled, Jérôme Baranger, Olivier Villemain

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineAutoregulationDoppler effectCerebral autoregulationCardiologyDoppler ultrasoundTranscranial DopplerInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

Introduction: Newborns with congenital heart diseases requiring cardiopulmonary bypass are at risk of neurodevelopmental impairment. The impact of deep hypothermia during cardiopulmonary bypass (DH-CPB) on cerebrovascular autoregulation (CAR) that controls brain perfusion in the presence of variable blood pressure is not well understood. Recently, Ultrafast Power Doppler (UPD) showed potential to study CAR in neonates based on the measurement of cerebral blood volume (CBV). However, since CAR relies mainly on the arterial vasoconstriction/vasodilation, the interpretation of brain perfusion based on CBV requires further separation of arterial CBV from total CBV. This study aims to use UPD to monitor CAR during DH-CPB in neonates. Methods: An ultrasonic probe (5.7 MHz) was placed on the anterior fontanel of 6 newborns before, during and after DH-CPB. Using ultrafast sequences generated by a Verasonic Vantage research system, mid-coronal plane images were acquired (PRF of 9 kHz, 5 compounded diverging waves). An adaptive spatiotemporal singular value decomposition was used to separate the blood signal from tissue signal and obtain UPD. CBV was computed in the deep gray matter (DGM). This region was chosen due to its higher susceptibility to hypoxic-ischemic injury. Arterial CBV was isolated from total CBV based on the upward arterial flow obtained using signed-power Doppler (See Fig A). Pearson correlation ® was computed between mean arterial blood pressure (MAP) and arterial CBV to study CAR. Results: Before and after DH-CPB, negative correlations were found between arterial CBV and MAP: -0.30 and -0.43 respectively. This indicates that an increase in MAP is associated with a decrease in cerebral arterial blood volume. This decrease in arterial CBV likely arises from arterial vasoconstriction, suggesting an active CAR response. Conversely, during DH-CPB, no correlation was found (r = -0.02). This means that despite the increase in MAP, arterial CBV remains unchanged. This lack of variation of arterial CBV is likely due to absent arterial vasoconstriction, suggesting an impaired CAR response. Conclusion: Our findings highlight the potential of UPD for continuous monitoring of CAR, paving the way for improving neurovascular management strategies during DH- CPB.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.326
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreOther

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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