Whole-Heart Coronary Magnetic Resonance Angiography at 1.5 Tesla
Bibliographic record
Abstract
OBJECTIVES: To evaluate the impact of the blood-pool contrast agent gadofosveset trisodium on diagnostic accuracy of whole-heart coronary magnetic resonance angiography (CMRA) at 1.5 Tesla. MATERIALS AND METHODS: Thirty consecutive patients with suspected coronary artery disease underwent free-breathing whole-heart CMRA at 1.5 Tesla. CMRA was performed with a T2-prepared steady-state free precession sequence (unenhanced CMRA) and an inversion-recovery-prepared steady-state free precession sequence after administration of gadofosveset trisodium (contrast-enhanced CMRA). Two readers independently performed a per-segment evaluation of CMRA (8 proximal and mid coronary segments) for detection of significant stenosis (≥50%) using invasive coronary angiography as reference. Disagreement was settled by consensus reading and interobserver variability was assessed using an unweighted kappa statistic. RESULTS: Whole-heart CMRA was successfully performed in 27 patients. The percentage of assessable segments was significantly lower on unenhanced CMRA compared with contrast-enhanced CMRA (Reader 1: 79% [170/216] vs. 89% [192/216], respectively; Reader 2: 73% [157/216] vs. 87% [188/216], respectively; P < 0.001). Intention-to-diagnose analysis of the consensus reading yielded sensitivity, specificity, and diagnostic accuracy of unenhanced versus contrast-enhanced CMRA as follows: 73.1% versus 73.1% (P = 1.0), 68.3% versus 80.2% (P = 0.002), and 68.9% versus 79.3% (P = 0.004), respectively. The kappa value for interobserver agreement was 0.61 (95% confidence interval = 0.50-0.72) for unenhanced CMRA and 0.72 (95% confidence interval = 0.62-0.82) for contrast-enhanced CMRA. CONCLUSIONS: The blood-pool contrast agent gadofosveset trisodium increased the number of assessable coronary segments on whole-heart CMRA in comparison to unenhanced whole-heart CMRA. The impact of gadofosveset trisodium on diagnostic accuracy, however, was only minor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".