CEUS cardiac exam protocols International Contrast Ultrasound Society (ICUS) recommendations
Bibliographic record
Abstract
The present CEUS Cardiac Exam Protocols represent the first effort to promulgate a standard set of protocols for optimal administration of ultrasound enhancing agents (UEAs) in echocardiography, based on more than two decades of experience in the use of UEAs for cardiac imaging. The protocols reflect current clinical CEUS practice in many modern echocardiography laboratories throughout the world. Specific attention is given to preparation and dosing of three UEAs that have been approved by the United States Food and Drug Administration (FDA) and additional regulatory bodies in Europe, the Americas and Asia-Pacific. Consistent with professional society guidelines (J Am Soc Echocardiogr 31:241-274, 2018; J Am Soc Echocardiogr 27:797-810, 2014; Eur Heart J Cardiovasc Imaging 18:1205, 2017), these protocols cover unapproved "off-label" uses of UEAs-including stress echocardiography and myocardial perfusion imaging-in addition to approved uses. Accordingly, these protocols may differ from information provided in product labels, which are generally based on studies performed prior to product approval and may not always reflect state of the art clinical practice or guidelines.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".