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Record W2801125391 · doi:10.1093/ehjci/jew093.132

1614not just 2d but also 4d flow measurements in pulsatile phantom are accurate and reproducible

2016· article· en· W2801125391 on OpenAlexaboutno aff
Ana Beatriz Solana, Fatih Hafalir, Piero Ghedin, Peng Lai, Ann Shimakawa, C. Anja, Sohrab Fratz

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2016
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIsocenterImaging phantomReproducibilityPulsatile flowMedicineScannerIntraclass correlationNuclear medicineFlow measurementFlow (mathematics)Biomedical engineeringFlow velocityPhysicsOpticsMechanicsMathematics

Abstract

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Introduction: 4DFlow is an emerging technique with high potential in the evaluation of congenital and acquired heart diseases. The validation of accuracy and reproducibility of flow measurements in 4DFlow is of key importance for the clinical use of this technique. Here, we compare 2D and 4DFlow using a robust pulsatile flow phantom setup with different tube configurations and heart rates. Methods:Acquisition: A closed-circuit pulsatile flow phantom was built; composed by an industrial membrane flow pump, two counter-flow parallel silicone tubes (inflow tube at isocenter and center of FoV and outflow tube out of isocenter) and a Coriolis flow meter (Endress + Hauser), to measure a ground-truth net flow measure with a precision of about ±1ml/s. Two configurations were tested: 1) with tubes parallel to the z axis of the scanner (axial), and 2) with tubes placed in a double oblique. Flow phantom scans were performed on a GE 3T MR750w MR scanner (Waukesha, WI). Retrospectively gated PC; “breathhold” and “free-breathing” (with 3 averages) 2D through-plane FastCINE and kat ARC 4D Flow were scanned [1]. Table 1 summarizes the flow phantom configuration setups and the main MRI protocol parameters. Analysis: PC net flow measurements were evaluated using CVI42 software (Calgary, Canada) for 2D and Arterys (San Francisco, CA) for 4DFlow. For both, background phase correction (BPC) using static phantom correction [2] and image-based correction [3] was applied. Statistical analyses were performed in Microsoft Excel. Intraclass Correlation Coefficients (ICC) was used to evaluate reproducibility. The Bland-Altmann plot was used to compare the obtained net flow results using MR to the ground-truth value measured by the flow meter in percentage difference as a measure of accuracy. Results: At the position of the outflow tube (>8cm from isocenter) before BPC the highest background phase error of 13% for the lower VENC was found. However, Figure 1 shows a mean percentage error of less than 8% (less than 6% for 4DFlow) with respect to the ground-truth flow for both tubes and for all configurations after BPC. Reproducibility was excellent obtaining ICC = 0.97 for 20 datasets. Discussion: 2D PC and 4DFlow across multiple imaging conditions and setup configurations for a pulsatile flow phantom setup are reliable and accurate. References: 1. Lai P et al. ISMRM 2015. 2. Chernobelsky et al. 2007. 3. Tan et al. ISMRM 2014. JOURNAL/ehjci/04.02/01619449-201605001-00214/math_214MM1/v/2017-10-13T061416Z/r/image-png JOURNAL/ehjci/04.02/01619449-201605001-00214/math_214MM2/v/2017-10-13T061416Z/r/image-png JOURNAL/ehjci/04.02/01619449-201605001-00214/math_214MM3/v/2017-10-13T061416Z/r/image-png

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.310
Teacher spread0.226 · 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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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