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Record W2032685404 · doi:10.1186/1532-429x-12-20

Oxygenation-sensitive CMR for assessing vasodilator-induced changes of myocardial oxygenation

2010· article· en· W2032685404 on OpenAlexaff
Matthias Vöhringer, Jacqueline Flewitt, Jordin D. Green, Rohan Dharmakumar, Jiun Wang, John V. Tyberg, Matthias G. Friedrich

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineOxygenationAngiologyCardiologyInternal medicineVasodilation

Abstract

fetched live from OpenAlex

BACKGROUND: As myocardial oxygenation may serve as a marker for ischemia and microvascular dysfunction, it could be clinically useful to have a non-invasive measure of changes in myocardial oxygenation. However, the impact of induced blood flow changes on oxygenation is not well understood. We used oxygenation-sensitive CMR to assess the relations between myocardial oxygenation and coronary sinus blood oxygen saturation (SvO2) and coronary blood flow in a dog model in which hyperemia was induced by intracoronary administration of vasodilators. RESULTS: During administration of acetylcholine and adenosine, CMR signal intensity correlated linearly with simultaneously measured SvO2 (r2 = 0.74, P < 0.001). Both SvO2 and CMR signal intensity were exponentially related to coronary blood flow, with SvO2 approaching 87%. CONCLUSIONS: Myocardial oxygenation as assessed with oxygenation-sensitive CMR imaging is linearly related to SvO2 and is exponentially related to vasodilator-induced increases of blood flow. Oxygenation-sensitive CMR may be useful to assess ischemia and microvascular function in patients. Its clinical utility should be evaluated.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.269
Teacher spread0.254 · 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 designBench or experimental
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

Citations47
Published2010
Admission routes1
Has abstractyes

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