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Record W4399143060 · doi:10.1016/j.chest.2024.04.026

Quantifying Diaphragm Blood Flow With Contrast-Enhanced Ultrasound in Humans

2024· article· en· W4399143060 on OpenAlexafffund
Jordan D. Bird, Megan L. Lance, Ty R W Banser, Scott F. Thrall, Paul D. Cotton, Jonathan R. Lindner, Neil D. Eves, Paolo B. Dominelli, Glen E. Foster

Bibliographic record

VenueCHEST Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsInterior HealthUniversity of WaterlooUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsContrast (vision)Diaphragm (acoustics)Blood flowUltrasoundContrast-enhanced ultrasoundMedicineBiomedical engineeringComputer scienceRadiologyArtificial intelligenceAcousticsPhysics

Abstract

fetched live from OpenAlex

Background Despite the known interplay between blood flow and function, to our knowledge, there is currently no minimally invasive method to monitor diaphragm hemodynamics. We used contrast-enhanced ultrasound to quantify relative diaphragm blood flow ( Q ˙ DIA ) in humans and assessed the technique's efficacy and reliability during graded inspiratory pressure threshold loading. We hypothesized that: (1) Q ˙ DIA would linearly increase with pressure generation, and (2) that there would be good test-retest reliability and interanalyzer reproducibility. Research Question Can we validate what is, to our knowledge, the first minimally invasive method to measure relative diaphragm blood flow in humans? Study Design and Methods Quantitative contrast-enhanced ultrasound of the costal diaphragm was performed in healthy participants (10 male participants, 6 female participants; mean age 28 ± 5 years; BMI 22.8 ± 2.0 kg/m) during unloaded breathing and three stages of loaded breathing on two separate days. Gastric and esophageal balloon catheters measured transdiaphragmatic pressure. Ultrasonography was performed during a constant-rate IV infusion of lipid-stabilized microbubbles following each stage. Ultrasound images were acquired after a destruction-replenishment sequence and diaphragm specific time-intensity data were used to determine Q ˙ DIA by two individuals. Results Transdiaphragmatic pressure for unloaded and each loading stage were 15.2 ± 0.8, 26.1 ± 0.8, 34.6 ± 0.8, and 40.0 ± 0.8 percentage of the maximum, respectively. Q ˙ DIA increased with each stage of loading (3.1 ± 3.1, 6.9 ± 3.6, 11.0 ± 4.9, and 13.5 ± 5.4 acoustic units/s; P < .0001). The linear relationship between diaphragmatic flow and pressure was reproducible from day to day. Q ˙ DIA had good to excellent test-retest reliability (0.86 [0.77, 0.92]; P < .0001) and excellent interanalyzer reproducibility (0.93 [0.90, 0.95]; P < .0001) with minimal bias. Interpretation Relative Q ˙ DIA measurements had valid physiological underpinnings, were reliable day-to-day, and were reproducible analyzer-to-analyzer. This study indicated that contrast-enhanced ultrasound is a viable, minimally invasive method for assessing costal Q ˙ DIA in humans and may provide a tool to monitor diaphragm hemodynamics in clinical settings.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.033
GPT teacher head0.294
Teacher spread0.261 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2024
Admission routes2
Has abstractyes

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