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Clinical Experience with SonoVue in Myocardial Perfusion Imaging

2000· review· en· W1998085367 on OpenAlex
Daniele Rovai, Maria‐Aurora Morales, R Amyot, A. L rsquo Abbate

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.

Bibliographic record

VenueEchocardiography · 2000
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicinePerfusionSecond-harmonic imaging microscopyUltrasoundRadiologyPerfusion scanningSubtractionMicrobubblesCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Ultrasound-enhancing agents have the potential to evaluate myocardial perfusion, adding a new dimension to echocardiography. This article summarizes the clinical studies involving SonoVue, a new intravenous ultrasound contrast agent, in assessing myocardial perfusion. Safe and well tolerated, SonoVue coupled with echocardiography has the capability to identify perfusion abnormalities, as confirmed by scintigraphic imaging. While the optimal modalities for ultrasound perfusion assessment are not yet determined, numerous technical advances have been introduced: continuous infusion or slow intravenous administration of the agent, harmonic intermittent imaging, pulse inversion, background subtraction, color coding, and others. SonoVue is a promising new agent in the booming field of myocardial contrast echocardiography.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.297
Teacher spread0.277 · 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