Comparison of Two Blood Pool Contrast Agents for 0.5-T MR Angiography: Experimental Study in Rabbits
Bibliographic record
Abstract
PURPOSE: To evaluate two experimental blood pool agents for potential use in equilibrium phase abdominal magnetic resonance (MR) angiography. MATERIALS AND METHODS: MR imaging at 0.5 T was performed in 37 rabbits before and after intravenous injection of a gadolinium-based blood pool contrast agent (SH L 643 A), superparamagnetic iron oxide blood pool agent (SH U 555 C), or gadopentetate dimeglumine. T1-weighted fast spoiled gradient-echo images from the renal arteries to below the iliac bifurcation were obtained. The aorta-to-tissue signal difference-to-noise ratio (SDNR) was measured over time. RESULTS: Both blood pool agents yielded excellent demonstration of the rabbit abdominal aorta. At a dose of 0.1 mmol/kg, both provided a statistically significant increase in aorta-to-tissue SDNR in comparison with that achieved with gadopentetate dimeglumine (200% increase for SH L 643 A, 95% increase for SH U 555 C; P < .05). A 0.1 mmol/kg dose of SH L 643 A provided a 24% increase in SDNR relative to the increase with a 0.37 mmol/kg dose of gadopentetate dimeglumine. Time-dependent enhancement properties of the blood pool agents differed due to differences in elimination method. CONCLUSION: Both blood pool agents were found to be promising contrast agents for 0.5-T MR angiography; however, their clinical applicability warrants further investigation. The gadolinium-based agent had several advantages over the iron oxide compound, including less T2* dephasing, lack of susceptibility artifacts, and fast renal elimination.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".