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Record W1545625732 · doi:10.5772/27945

Role of Advanced Cardiac Magnetic Resonance Imaging in Atypical Cardiomyopathies such as Stress-Induced Cardiomyopathie and Left-Ventricular Non-Compaction Cardiomyopathy

2012· book-chapter· en· W1545625732 on OpenAlexaff
Oliver Strohm, Abdullah Shehab, Anwer Qureshi

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCardiomyopathyCardiac magnetic resonanceMagnetic resonance imagingMedicineCardiologyInternal medicineCardiac magnetic resonance imagingHeart failureRadiology

Abstract

fetched live from OpenAlex

Cardiomyopathies -From Basic Research to Clinical Management 426 Contrast-enhanced cardiac magnetic resonance imaging (CMR) allows for a non-invasive assessment of the tissue composition using contrast-free (T2, e.g.STIR) and contrastenhanced techniques (early and late Gadolinium enhancement).Together with a functional assessment, it can be used to determine the acuity of e.g.inflammatory diseases and provide a non-invasive follow-up tool. CMR techniques usedFunctional imaging with high-resolution sequences such as SSFP cines allow to assess the whole left and right ventricles and calculate volumes, ejection fraction and mass.Myocardial wall stress can be calculated from these.Assessment of valvular function is needed and may require additional flow studies for the calculation of regurgitation fraction of aor t i c a n d m i t r a l v a l v e .A s s e s s m e n t o f t h e pericardium can be done on the functional images, too.T2-weighted images with fat suppression allow assessing myocardial water content, thus allowing to assess the stage of disease.To provide an "internal standard", skeletal muscle is used as control; an SI-ratio of more than 2.0 is considered abnormal.T1-weighted images allow to demonstrate acute inflammatory changes including increased extracellular volume and membrane integrity.As in T2-weighted imaging a skeletal muscle is used as "internal standard"; an enhancement -ratio (myocardial enhancement / muscle enhancement) of more than 4.0 is considered abnormal.The body-coil is used to obtain homogenous SI through the images, short axis or axial images are selected to optimize image quality.Newer sequences may improve image quality and allow for the use of multi-element coils.Late Gadolinium enhancement allows to non-invasively diagnose irreversible damage in the myocardium (e.g.fibrosis, infarcts).Due to the specific location in ischemic damages (starts at the subendocardial layer), it is easy to distinguish non-ischemic damages (as in myocarditis) from ischemic problems.Combining T2-information, early and late enhancement, CMR is able to safely assess the acuity and reversibility of the disease process in non-ischemic Cardiomyopathies and inflammatory processes (16). How to referenceIn order to correctly reference this scholarly work, feel free to copy and paste the following:

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.004

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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 designNot applicable
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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Citations0
Published2012
Admission routes1
Has abstractyes

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