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Record W2192009577 · doi:10.1148/radiol.2015150341

Quantification of Myocardial Extracellular Volume Fraction with Cardiac MR Imaging in Thalassemia Major

2015· article· en· W2192009577 on OpenAlexaff
Kate Hanneman, Elsie T. Nguyen, Paaladinesh Thavendiranathan, R. Parker Ward, Andreas Greiser, Marie‐Pierre Jolly, Jagdish Butany, Issac Y. Yang, Marshall S. Sussman, Bernd J. Wintersperger

Bibliographic record

VenueRadiology · 2015
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineThalassemiaCardiologyInternal medicineMagnetic resonance imagingCardiac magnetic resonance imagingHematocritEjection fractionVolume overloadFeature trackingCardiac magnetic resonanceNuclear medicineHeart failureRadiology

Abstract

fetched live from OpenAlex

Purpose To quantify myocardial extracellular volume (ECV) by using cardiac magnetic resonance (MR) imaging in thalassemia major and to investigate the relationship between ECV and myocardial iron overload. Materials and Methods With institutional review board approval and informed consent, 30 patients with thalassemia major (mean age ± standard deviation, 34.6 years ± 9.5) and 10 healthy control subjects (mean age, 31.5 years ± 4.4) were prospectively recruited (clinicaltrials.gov identification number NCT02090699). Nineteen patients (63.3%) had prior myocardial iron overload (defined as midseptal T2* < 20 msec on any prior cardiac MR images). Cardiac MR imaging at 1.5 T included cine steady-state free precession for ventricular function, T2* for myocardial iron quantification, and unenhanced and contrast material-enhanced T1 mapping. ECV was calculated with input of the patient's hematocrit level. Peak systolic global longitudinal strain by means of speckle tracking was assessed with same-day transthoracic echocardiography. Statistical analysis included use of the two-sample t test, Fisher exact test, and Spearman correlation. Results Unenhanced T1 values were significantly lower in patients with prior myocardial iron overload than in control subjects (850.3 ± 115.1 vs 1006.3 ± 35.4, P < .001) and correlated strongly with T2* values (r = 0.874, P < .001). Patients with prior myocardial iron overload had higher ECV than did patients without iron overload (31.3% ± 2.8 vs 28.2% ± 3.4, P = .030) and healthy control subjects (27.0% ± 3.1, P = .003). There was no difference in ECV between patients without iron overload and control subjects (P = .647). ECV correlated with lowest historical T2* (r = -0.469, P = .010) but did not correlate significantly with left ventricular ejection fraction (r = -0.216, P = .252) or global longitudinal strain (r = -0.164, P = .423). Conclusion ECV is significantly increased in thalassemia major and is associated with myocardial iron overload. These abnormalities may potentially reflect diffuse interstitial myocardial fibrosis. (©) RSNA, 2015 Online supplemental material is available for this article.

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)0.000
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 score0.059
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.246
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

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

Citations54
Published2015
Admission routes1
Has abstractyes

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