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Record W2948779516 · doi:10.1093/ehjci/jez118.004

P4167-Tesla Cardiac MRI with vector-ECG gating despite the magnetohydrodynamic effect in healthy volunteers

2019· article· en· W2948779516 on OpenAlexaboutno aff
Christian Hamilton‐Craig, Daniel Stäeb, Graham J. Galloway, Markus Barth

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2019
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGatingMagnetohydrodynamic driveCardiologyMedicineInternal medicinePhysicsNuclear magnetic resonanceMagnetohydrodynamicsNuclear physicsPhysiology

Abstract

fetched live from OpenAlex

Background: Ultra-high-field (B0 ≥ 7 Tesla) cardiovascular magnetic resonance (CMR) offers increased resolution. However cardiac imaging requiring ECG gating is significantly impacted by the magneto-hydrodynamic (MHD) effect, which distorts the ECG trace. Previously, 7T CMR was often constrained to using pulse oximetry for triggering. We explored the technical feasbility of a 7T research MR scanner using of-the-art ECG trigger algorithm to assess left and right ventricular volumes, aortic and pulmonary valve flow. Methods: 7T CMR scans were performed on 10 healthy volunteers on whole-body research MRI scanner (Siemens Healthcare, Erlangen, Germany) with 8 channel Tx/32 channel Rx cardiac coil (MRI Tools GmbH, Berlin, Germany) under institutional review board approval. Vectorcardiogram ECG was successfully performed using a learning phase outside of the magnetic field, with a trigger algorithm with sufficient accuracy for CMR despite severe ECG signal distortions from the 7T field. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented two-dimensional spoiled gradient echo sequence, and 2-dimensional phase contrast flow imaging. Analysis was performed using CMR42 software (Circle CVi, Calgary). Results: Successful 7T CMR scans were acquired in all patients (100%) using the Vectorcardiogram 3-lead ECG method. Image quality was sufficient to quantitate both left and right ventricular volumes, ejection fraction, aortic and pulmonary blood flow and regurgitant fractions in 9/10 (90%) of volunteers (figure 1), with one volunteer having difficulty with breath-holding and ventricular ectopy causing gating artefacts. Conclusion: Reliable cardiac ECG triggering is feasible in healthy volunteers at ultra-high field utilizing a state-of-the-art 3-lead trigger device despite signal distortion from the MHD effect, and provides sufficient image quality for quantitative analysis. Other ultra-high-field imaging applications such as human brain functional MRI with physiologic noise correction may benefit from this method of ECG triggering Abstract P416 Figure: 7T ECG triggered CMR

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)0.000
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 score0.417
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.263
Teacher spread0.255 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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