Visualization of coronary venous anatomy by cardiovascular magnetic resonance
Bibliographic record
Abstract
BACKGROUND: Coronary venous imaging with whole-heart cardiovascular magnetic resonance (CMR) angiography has recently been described using developmental pulse sequences and intravascular contrast agents. However, the practical utility of coronary venous imaging will be for patients with heart failure in whom cardiac resynchronisation therapy (CRT) is being considered. As such complementary information on ventricular function and myocardial viability will be required. The aim of this study was to determine if the coronary venous anatomy could be depicted as part of a comprehensive CMR protocol and using a standard extracellular contrast agent. METHODS AND RESULTS: Thirty-one 3D whole heart CMR studies, performed after intravenous administration of 0.05 mmol/kg gadolinium DTPA, were reviewed. The cardiac venous system was visualized in all patients. The lateral vein of the left ventricle was present in 74%, the anterior interventricular vein in 65%, and the posterior interventricular vein in 74% of patients. The mean maximum distance of demonstrable cardiac vein on the 3D images was 81.5 mm and was dependent on the quality of the 3D data set. Five patients showed evidence of myocardial infarction on late gadolinium enhancement (LGE) images. CONCLUSION: Coronary venous anatomy can be reliably demonstrated using a comprehensive CMR protocol and a standard extracellular contrast agent. The combination of coronary venous imaging, assessment of ventricular function and LGE may be useful in the management of patients with LV dysfunction being considered for CRT.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".