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Record W2118763221 · doi:10.1109/ultsym.2005.1602874

A retrospective method for pulse-wave velocity measurement in the mouse

2006· article· en· W2118763221 on OpenAlexaff
R. Williams, A. Needles, Emmanuel Chérin, F. Stuart Foster, Yuqing Zhou, M. Henkelman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsHospital for Sick ChildrenHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsPulse wave velocityPulse (music)Flow (mathematics)Doppler effectMedicineNuclear medicineMathematicsPhysicsCardiologyInternal medicineGeometryOpticsBlood pressure

Abstract

fetched live from OpenAlex

The pulse-wave velocity (PWV) is inversely related to arterial compliance, and provides a useful measure of vascular function. In this study, the PWV was measured non-invasively in the mouse carotid artery using the time-delay (TD) and flow-area (QA) methods. The TD technique determines the distributed PWV from the time-delay between Doppler-derived upstrokes at two locations a known distance apart. The QA method estimates the local PWV as the ratio between the change in volume flow and the change in cross-sectional area during the reflection-free period of the cardiac cycle. Our new QA approach measures the cross-sectional area and flow through the vessel using a high- frame-rate retrospective colour flow imaging (RCFI) technique. The cross-sectional area is determined by integrating over the region of flow in each frame of the RCFI dataset, while the volume flow is calculated by averaging the velocities over the vessel in each frame and multiplying by the corresponding area. The TD method was compared with the flow-area method in the carotid artery of 7 young CD-1 mice, anesthetized with isoflurane. The average TD PWV was found to be 3.03±0.17 m/s. The average QA PWV was found to be 2.97±0.18 m/s. The TD method was found to correlate well with the QA method (r=0.91, p<0.001). The mean difference between the TD method and the QA method was 0.06±0.08 m/s, and 95% of the differences fell within ±0.41±0.20 m/s of the mean difference. These results indicate that the QA method should be capable of distinguishing between changes to PWV caused by vascular disease. It was found that the QA method permits the measurement of the local PWV. The TD method offered superior reliability to the QA method for PWV determination in the mouse carotid artery because it was affected by fewer contextual factors. However, the QA method is useful for situations in which the TD method is unsuitable due to the geometry of the vessel. In this study, we compared a QA method of measuring the PWV with an image-guided TD method in the carotid artery of seven CD-1 mice. The TD technique was used to measure a distributed PWV over the carotid artery from the aortic arch to the bifurcation. The QA method was applied to determine the local PWV at the midsection of the carotid. The objective of this study was to assess the potential of the QA method against the TD method and to demonstrate a simple image-based methodology for performing PWV measurements. Determination of the most reliable PWV estimation method will be useful in a future longitudinal study of vascular development in transgenic mice.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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
GenreMethods

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".

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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