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Record W1971083446 · doi:10.1002/mrm.21075

Cardiorespiratory‐resolved magnetic resonance imaging: Measuring respiratory modulation of cardiac function

2006· article· en· W1971083446 on OpenAlexaff
Richard B. Thompson, Elliot R. McVeigh

Bibliographic record

VenueMagnetic Resonance in Medicine · 2006
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNational Institutes of Health
KeywordsSteady-state free precession imagingCardiac cycleMagnetic resonance imagingRespiratory systemMedicineCardiac outputCardiac function curveInferior vena cavaNuclear medicineCardiologyInternal medicineHemodynamicsRadiologyHeart failure

Abstract

fetched live from OpenAlex

A technique for cardiac- and respiratory-resolved MRI is described. A retrospectively gated-segmented acquisition scheme similar to that used in conventional cine cardiac imaging was used to collect image data that spanned both the cardiac and respiratory cycles. Raw k-space data were regridded in a cardiorespiratory phase space to allow image reconstruction at target cardiac and respiratory phases. The approach can be applied with various k-space trajectories and pulse sequences, and was implemented in this study with both a Cartesian steady-state free precession (SSFP) sequence and a radial phase-contrast (PC) pulse sequence. Free-breathing short-axis SSFP images of the heart were reconstructed at multiple respiratory and cardiac phases to illustrate separation of cardiac and respiratory motion without artifacts. A respiratory-resolved radial PC experiment was used to quantify the volumetric flow rates in the inferior vena cava (IVC), pulmonary artery (PA), and aorta (Ao) in five free-breathing normal volunteers and a positive-pressure ventilated dog. Total flow (ml/min) in each vessel was quantified as a function of respiratory phase (peak/minimum output = 1.85 +/- 0.29 (IVC), 1.36 +/- 0.15 (PA), 1.24 +/- 0.09 (Ao)). Peak flow occurred during inspiration for the IVC and PA, and during expiration for the Ao, and there was a complete pattern reversal for the positive-pressure ventilated dog.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.675
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.275
Teacher spread0.253 · 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.

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

Citations37
Published2006
Admission routes1
Has abstractyes

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