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Record W2003131697 · doi:10.1002/mrm.21758

On the overestimation of early wall thickening at the carotid bulb by black blood MRI, with implications for coronary and vulnerable plaque imaging

2008· article· en· W2003131697 on OpenAlexafffund
Luca Antiga, Bruce A. Wasserman, David A. Steinman

Bibliographic record

VenueMagnetic Resonance in Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Toronto
FundersHeart and Stroke Foundation of Canada
KeywordsCoronal planeMaterials scienceImaging phantomCarotid arteriesThickeningCylinderIsotropyMedicineBiomedical engineeringRadiologyOpticsCardiologyGeometryPhysicsMathematics

Abstract

fetched live from OpenAlex

Black blood MRI is an attractive tool for monitoring normal and pathological wall thickening; however, limited spatial resolutions can conspire with complex vascular geometries to distort the appearance of the wall in ways hitherto unclear. To elucidate this, a thin-walled cylinder model was developed to predict the composite effects of obliqueness, in-plane resolution and voxel anisotropy on the accuracy of MRI-derived wall thickness measurements. These predictions were validated by means of imaging of a thin-walled carotid bifurcation phantom. Typical thick-slice axial acquisitions were found to result in artifactual wall thickening at the carotid bulb, owing to its obliqueness to the nominal imaging plane. Obliqueness was less problematic for near-isotropic resolutions; however, the obligatory reduction of in-plane resolution served to inflate wall thicknesses uniformly by up to 50%. Moreover, the nonlinear relationship between wall thickness and its overestimation served to mask genuine differences in wall thickness, an effect predicted to be worse for thinner coronary artery walls and plaque caps. Therefore, care must be taken when interpreting black blood MRI wall thickness measurements in the presence-or absence-of observed differences within or between individuals.

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 score0.024
Threshold uncertainty score0.318

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 studies0.0000.001
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 head0.012
GPT teacher head0.242
Teacher spread0.229 · 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

Citations89
Published2008
Admission routes2
Has abstractyes

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