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Record W2061871239 · doi:10.5430/jbgc.v3n4p75

Discrepancy between regional left ventricular regional circumferential strain assessed by MR-tagging and by speckle tracking echocardiography

2013· article· en· W2061871239 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Biomedical Graphics and Computing · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
FundersUniversité de LyonInstitut National des Sciences Appliquées de LyonVrije Universiteit AmsterdamIndian National Science Academy
KeywordsStrain (injury)Radial stressEjection fractionVentricular functionSpeckle tracking echocardiographyMedicineSpeckle patternNuclear medicineShort axisTracking (education)Internal medicineCardiologyRadiologyLong axisHeart failurePhysicsMathematicsComputer scienceArtificial intelligenceGeometryPsychology

Abstract

fetched live from OpenAlex

Background: In recent years, myocardial strain imaging has gained an important place for the evaluation of cardiac patients. Global longitudinal strain assessed by speckle tracking echocardiography (STE) is now commonly used but circumferential strain remains less extensively studied. MR-tagging is recognized as the reference method for circum- ferential strain analysis, however no validation study between regional MR-tagging and regional STE has been performed up to now. Objective: To compare segmental circumferential strain values (Ecc) obtained by speckle tracking and by MR-tagging in patient with normal systolic function in order to define if both methods are interchangeable or not. Patients and methods: patients without significant regional nor global systolic dysfunction (LVEF > 55%) were studied by MR-tagging ( n =82) and by STE ( n =35). Left ventricular mid-level short axis slice was obtained by both methods and paired data were available in 16 patients. Segmental Ecc values were computed in six equidistant sectors using GE EchoPac software for STE and InTag post processing software for MR-tagging. Results: 1) Comparison between regions: Overall results showed that regional peak Ecc magnitude |Eccpeak| was not uniform with both methods but in an opposite way. MR-tagging demonstrated significantly lower septal |Eccpeak| as compared with postero-lateral |Eccpeak| (-16.5±3.6 vs -23.4±4.4, p <10 -4 ). Conversely, STE showed significantly higher septal |Eccpeak| as compared with postero-lateral |Eccpeak| (-22.3±6.4 vs -13.9±6.2, p <10 -4 ). 2) Comparison between both methods: In the subgroup of patients studied by both methods, septal |Eccpeak| was 29% lower by MR-tagging as compared with STE (-14.9±2.4 vs -20.9±6.5, p <.006) and postero-lateral |Eccpeak| was 39% lower by STE as compared with MR-tagging (-12.9±5.9 vs -21.0±2.9, p <.0003). 3) Intra and interobserver coefficients of variation were homogeneous (in the range 10%-14%) for all sectors with MR-tagging but were dramatically variable with STE (15% to 20% in the anterior-septal region but three times higher, in the range 35%-40%, in the postero-lateral territory). Conclusion: Regional distributions of Ecc is not uniform but opposite results are provided by MR-tagging and by STE. This finding demonstrates that both methods cannot be considered as interchangeable. These conflicting results raise the question of the validity of either MR tagging or speckle tracking for the quantification of regional circumferential strain. Some arguments, developed in the discussion would rather let believe that MR-tagging results should be more reliable.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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