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Record W2990009294 · doi:10.1186/s12968-019-0586-8

Quantification of blood flow in the fetus with cardiovascular magnetic resonance imaging using Doppler ultrasound gating: validation against metric optimized gating

2019· article· en· W2990009294 on OpenAlexaff
Daniel Ryd, Liqun Sun, Katarina Steding‐Ehrenborg, Sebastian Bidhult, Fabian Kording, Christian Ruprecht, Christopher K. Macgowan, Anthony H. Aletras, Håkan Arheden, Erik Hedström

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2019
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersMedicinska Fakulteten, Lunds UniversitetSkånes universitetssjukhusRegion SkåneHjärt-LungfondenLunds Universitet
KeywordsGatingMedicineMagnetic resonance imagingUltrasoundBlood flowAngiologyDoppler ultrasoundBiomedical engineeringRadiologyCardiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Fetal cardiovascular magnetic resonance (CMR) imaging is used clinically and for research, but has been previously limited due to lack of direct gating methods. A CMR-compatible Doppler ultrasound (DUS) gating device has resolved this. However, the DUS-gating method is not validated against the current reference method for fetal phase-contrast blood flow measurements, metric optimized gating (MOG). Further, we investigated how different methods for vessel delineation affect flow volumes and observer variability in fetal flow acquisitions. AIMS: To 1) validate DUS gating versus MOG for quantifying fetal blood flow; 2) assess repeatability of DUS gating; 3) assess impact of region of interest (ROI) size on flow volume; and 4) compare time-resolved and static delineations for flow volume and observer variability. METHODS: ) with repeated scans in six fetuses. Impact of ROI size on measured flow was assessed for ROI:s 50-150% of the vessel diameter. Four observers from two centers provided time-resolved and static delineations. Bland-Altman analysis was used to determine agreement between both observers and methods. RESULTS: DAo flow was 726 (348-1130) ml/min and umbilical vein flow 366 (150-782) ml/min by DUS gating. Bias±SD for DUS-gating versus MOG were - 45 ± 122 ml/min (-6 ± 15%) for DAo and 19 ± 136 ml/min (2 ± 24%) for umbilical vein flow. Repeated flow measurements in the same fetus showed similar volumes (median CoV = 11% (DAo) and 23% (umbilical vein)). Region of interest 50-150% of vessel diameter yielded flow 35-120%. Bias±SD for time-resolved versus static DUS-gated flow was 33 ± 39 ml/min (4 ± 6%) for DAo and 11 ± 84 ml/min (2 ± 15%) for umbilical vein flow. CONCLUSIONS: Quantification of blood flow in the fetal DAo and umbilical vein using DUS-gated phase-contrast CMR is feasible and agrees with the current reference method. Repeatability was generally high for CMR fetal blood flow assessment. An ROI similar to the vessel area or slightly larger is recommended. A static ROI is sufficient for fetal flow quantification using currently available CMR sequences.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.683
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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 teacher head, 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

Citations29
Published2019
Admission routes1
Has abstractyes

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