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Record W4400122293 · doi:10.1002/jmri.29496

Post‐Myocardial Infarction Remodeling and Hyperkinetic Remote Myocardium in Sheep Measured by Cardiac <scp>MRI</scp> Feature Tracking

2024· article· en· W4400122293 on OpenAlexaff
Steven K. S. Cho, Jack R. T. Darby, Georgia Williams, Stacey L. Holman, Archana Rai, Joshua van Amerom, Chun‐Po Steve Fan, Christopher K. Macgowan, Joseph B. Selvanayagam, Janna L. Morrison, Mike Seed

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsToronto General HospitalHospital for Sick ChildrenTed Rogers Centre for Heart ResearchUniversity Health NetworkUniversity of Toronto
FundersNational Health and Medical Research CouncilAustralian Research CouncilNational Imaging FacilitySouth Australian Health and Medical Research Institute
KeywordsMyocardial infarctionFeature trackingCardiologyTracking (education)Internal medicineMedicineFeature (linguistics)Computer scienceArtificial intelligencePsychologyPattern recognition (psychology)

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiac MRI feature tracking (FT) allows objective assessment of segmental left ventricular (LV) function following a myocardial infarction (MI), but its utilization in sheep, where interventions can be tested, is lacking. PURPOSE: To apply and validate FT in a sheep model of MI and describe post-MI LV remodeling. STUDY TYPE: Animal model, longitudinal. ANIMAL MODEL: Eighteen lambs (6 months, male, n = 14; female, n = 4; 25.2 ± 4.5 kg). FIELD STRENGTH/SEQUENCE: Two-dimensional balanced steady-state free precession (bSSFP) and 3D inversion recovery fast low angle shot (IR-FLASH) sequences at 3 T. ASSESSMENT: Seven lambs underwent test-retest imaging to assess FT interstudy reproducibility. MI was induced in the remaining 11 by coronary ligation with MRI being undertaken before and 15 days post-MI. Injury size was measured by late gadolinium enhancement (LGE) and LV volumes, LV mass, ejection fraction (LVEF), and wall thickness (LVWT) were measured, with FT measures of global and segmental radial, circumferential, and longitudinal strain. STATISTICAL TESTS: Sampling variability, inter-study, intra and interobserver reproducibility were assessed using Pearson's correlation, Bland-Altman analyses, and intra-class correlation coefficients (ICC). Diagnostic performance of segmental strain to predict LGE was assessed using receiver operating characteristic curve analysis. Significant differences were considered P < 0.05. RESULTS: Inter-study reproducibility of FT was overall good to excellent, with global strain being more reproducible than segmental strain (ICC = 0.89-0.98 vs. 0.77-0.96). MI (4.0 ± 3.7% LV mass) led to LV remodeling, as evident by significantly increased LV volumes and LV mass, and significantly decreased LVWT in injured regions, while LVEF was preserved (54.9 ± 6.9% vs. 55.6 ± 5.7%; P = 0.778). Segmental circumferential strain (CS) correlated most strongly with LGE. Basal and mid- CS increased significantly, while apical CS significantly decreased post-MI. DATA CONCLUSION: FT is reproducible and compensation by hyperkinetic remote myocardium may manifest as overall preserved global LV function. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 2.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.244
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2024
Admission routes1
Has abstractyes

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