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Record W2057100016 · doi:10.1097/rli.0b013e31827f1b68

Free Breathing Real-Time Cardiac Cine Imaging With Improved Spatial Resolution at 3 T

2013· article· en· W2057100016 on OpenAlexaff
Félix Schwab, Florian Schwarz, Olaf Dietrich, Titus Lanz, Frank Resmer, Tobias Wichmann, Bernd J. Wintersperger, Fabian Bamberg, Konstantin Nikolaou, Maximilian F. Reiser, Daniel Theisen

Bibliographic record

VenueInvestigative Radiology · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Toronto
FundersBayerische ForschungsstiftungBundesministerium für Bildung und ForschungDeutsches Zentrum für Herz-Kreislaufforschung
KeywordsVoxelImaging phantomNuclear medicineImage qualityImage resolutionTemporal resolutionBreathingCardiac imagingIterative reconstructionVentriclePartial volumeEjection fractionBiomedical engineeringComputer scienceMedicineArtificial intelligencePhysicsRadiologyImage (mathematics)Cardiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study was to evaluate free-breathing single-shot real-time cine imaging for functional cardiac imaging at 3 T with increased spatial resolution. Special emphasis of this study was placed on the influence of parallel imaging techniques. MATERIALS AND METHODS: Gradient echo phantom images were acquired with GRAPPA and modified SENSE reconstruction using both integrated and separate reference scans as well as TGRAPPA and TSENSE. In vivo measurements were performed for GRAPPA reconstruction with an integrated and a separate reference scan, as well as TGRAPPA using balanced steady-state free precession protocols. Three clinical protocols, rtLRInt (Tres = 51.3 milliseconds; voxel, 2.5 × 5.0 × 10 mm³), rtMRSep (Tres = 48.8 milliseconds; voxel, 1.9 × 3.1 × 10 mm³), and rtHRSep (Tres = 48.3 milliseconds; voxel, 1.6 × 2.6 × 10 mm), were investigated on 20 volunteers using GRAPPA reconstruction with internal as well as separate reference scans. End-diastolic volume, end-systolic volume, ejection fraction, peak ejection rate, peak filling rate, and myocardial mass were evaluated for the left ventricle and compared with an electrocardiogram-triggered segmented readout cine protocol used as standard of reference. All studies were performed at 3 T. RESULTS: Phantom and in vivo data demonstrate that the combination of GRAPPA reconstruction with a separate reference scan provides an optimal compromise of image quality as well as spatial and temporal resolution. Functional values (P values) for the standard of reference, rtLRInt, rtMRSep, and rtHRSep end-diastolic volume were 141 ± 24 mL, 138 ± 21 mL, 138 ± 19 mL, and 128 ± 33 mL, respectively (P = 0.7, 0.7, 0.4); end-systolic volume, 55 ± 15 mL, 61 ± 14 mL, 58 ± 12 mL, and 55 ± 20 mL, respectively (P = 0.23, 0.43, 0.62); ejection fraction, 61% ± 5%, 57% ± 5%, 58% ± 4%, and 56% ± 8%, respectively (P = 0.01, 0.11, 0.06); peak ejection rate, 481 ± 73 mL/s, 425 ± 62 mL/s, 434 ± 67 mL/s, and 381 ± 86 mL/s, respectively (P = 0.03, 0.04, 0.01); peak filling rate, 555 ± 80 mL/s, 480 ± 70 mL/s, 500 ± 70 mL/s, and 438 ± 108 mL/s, respectively (P= 0.007, 0.05, 0.004); and myocardial mass, 137 ± 26 g, 141 ± 25 g, 141 ± 23 g, and 130 ± 31 g, respectively (P = 0.62, 0.54, 0.99). CONCLUSIONS: Using a separate reference scan and high acceleration factors up to R = 6, single-shot real-time cardiac imaging offers adequate temporal and spatial resolution for accurate assessment of global left ventricular function in free breathing with short examination times.

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)0.000
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 score0.573
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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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Citations15
Published2013
Admission routes1
Has abstractyes

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