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Record W2097925909 · doi:10.1186/1532-429x-16-36

Native T1-mapping detects the location, extent and patterns of acute myocarditis without the need for gadolinium contrast agents

2014· article· en· W2097925909 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2014
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsUniversité de MontréalLibin Cardiovascular Institute of AlbertaMontreal Heart Institute
FundersClarendon FundMedical Research CouncilAlberta InnovatesUniversity of OxfordNational Institute for Health and Care ResearchBritish Heart FoundationWellcome Trust
KeywordsMedicineAngiologyMyocarditisAcute myocarditisMagnetic resonance imagingSteady-state free precession imagingCardiologyInternal medicineCardiac magnetic resonance imagingRadiologyContrast (vision)

Abstract

fetched live from OpenAlex

BACKGROUND: Acute myocarditis can be diagnosed on cardiovascular magnetic resonance (CMR) using multiple techniques, including late gadolinium enhancement (LGE) imaging, which requires contrast administration. Native T1-mapping is significantly more sensitive than LGE and conventional T2-weighted (T2W) imaging in detecting myocarditis. The aims of this study were to demonstrate how to display the non-ischemic patterns of injury and to quantify myocardial involvement in acute myocarditis without the need for contrast agents, using topographic T1-maps and incremental T1 thresholds. METHODS: We studied 60 patients with suspected acute myocarditis (median 3 days from presentation) and 50 controls using CMR (1.5 T), including: (1) dark-blood T2W imaging; >(2) native T1-mapping (ShMOLLI); (3) LGE. Analysis included: (1) global myocardial T2 signal intensity (SI) ratio compared to skeletal muscle; (2) myocardial T1 times; (3) areas of injury by T2W, T1-mapping and LGE. RESULTS: Compared to controls, patients had more edema (global myocardial T2 SI ratio 1.71 ± 0.27 vs.1.56 ± 0.15), higher mean myocardial T1 (1011 ± 64 ms vs. 946 ± 23 ms) and more areas of injury as detected by T2W (median 5% vs. 0%), T1 (median 32% vs. 0.7%) and LGE (median 11% vs. 0%); all p < 0.001. A threshold of T1 > 990 ms (sensitivity 90%, specificity 88%) detected significantly larger areas of involvement than T2W and LGE imaging in patients, and additional areas of injury when T2W and LGE were negative. T1-mapping significantly improved the diagnostic confidence in an additional 30% of cases when at least one of the conventional methods (T2W, LGE) failed to identify any areas of abnormality. Using incremental thresholds, T1-mapping can display the non-ischemic patterns of injury typical of myocarditis. CONCLUSION: Native T1-mapping can display the typical non-ischemic patterns in acute myocarditis, similar to LGE imaging but without the need for contrast agents. In addition, T1-mapping offers significant incremental diagnostic value, detecting additional areas of myocardial involvement beyond T2W and LGE imaging and identified extra cases when these conventional methods failed to identify abnormalities. In the future, it may be possible to perform gadolinium-free CMR using cine and T1-mapping for tissue characterization and may be particularly useful for patients in whom gadolinium contrast is contraindicated.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.000
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 head0.018
GPT teacher head0.272
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