Dynamic and Static Magnetic Resonance Angiography of the Supra-aortic Vessels at 3.0 T
Bibliographic record
Abstract
PURPOSE: The purpose of this study was the intraindividual comparison of a 1.0 M and two 0.5 M gadolinium-based contrast agents (GBCA) using equimolar dosing in dynamic and static magnetic resonance angiography (MRA) of the supra-aortic vessels. MATERIALS AND METHODS: In this institutional review board-approved study, a total of 20 healthy volunteers (mean ± SD age, 29 ± 6 years) underwent 3 consecutive supra-aortic MRA examinations on a 3.0 T magnetic resonance system. The order of GBCA (Gadobutrol, Gadobenate dimeglumine, and Gadoterate meglumine) was randomized with a minimum interval of 48 hours between the examinations. Before each examination and 45 minutes after each examination, circulatory parameters were recorded. Total GBCA dose per MRA examination was 0.1 mmol/kg with a 0.03 mmol/kg and 0.07 mmol/kg split for dynamic and static MRA, respectively, injected at a rate of 2 mL/s. Two blinded readers qualitatively assessed static MRA data sets independently using pairwise rankings (superior, inferior, and equal). In addition, quantitative analysis was performed with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) evaluation as well as vessel sharpness analysis of static MRA using an in-house-developed semiautomated tool. Dynamic MRA was evaluated for maximal SNR. Statistical analysis was performed using the Cohen κ, the Wilcoxon rank sum tests, and mixed effects models. RESULTS: No significant differences of hemodynamic parameters were observed. In static MRA, Gadobutrol was rated superior to Gadoterate meglumine (P < 0.05) and equal to Gadobenate dimeglumine (P = 0.06) with good to excellent reader agreement (κ, 0.66-0.83). In static MRA, SNR was significantly higher using 1.0 M Gadobutrol as compared with either 0.5 M agent (P < 0.05 and P < 0.05) and CNR was significantly higher as compared with Gadoterate meglumine (P < 0.05), whereas CNR values of Gadobutrol data sets were not significantly different as compared with Gadobenate dimeglumine (P = 0.13). Differences in CNR between Gadobenate dimeglumine and Gadoterate meglumine were not significant (P = 0.78). Differences in vessel sharpness between the different GBCAs were also not significant (P > 0.05). Maximal SNR in dynamic MRA using Gadobutrol was significantly higher than both comparators at the level of the proximal and distal internal carotid artery (P < 0.05 and P < 0.05; P < 0.05 and P < 0.05). CONCLUSIONS: At equimolar doses, 1.0 M Gadobutrol demonstrates higher SNR/CNR than do Gadobenate dimeglumine and Gadoterate meglumine, with superior image quality as compared with Gadoterate meglumine for dynamic and static carotid MRA. Despite the shortened bolus with Gadobutrol, no blurring of vessel edges was observed.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".