3D non‐contrast‐enhanced MR angiography with balanced steady‐state free precession dixon method
Bibliographic record
Abstract
Balanced steady-state free precession (bSSFP) is capable of producing ample fat-water separation. In the case of the bSSFP Dixon method, the phase between fat and water can be manipulated by setting repetition time (TR) to an odd-half-multiple of the cycle time and adjusting the center frequency to acquire fat-water in in-phase and opposed-phase images. Adding an image collected when fat and water are in-phase to an image in which fat and water are opposed-phase produces a water-only image. Of the water signals, arterial blood has the highest T(2)/T(1) contrast, making the arterial signal appear brighter than both venous blood and muscle in the final image. In this study, the bSSFP Dixon method was used to collect coronal water-only three-dimensional (3D) volumes at multiple anatomical stations in the legs of five healthy volunteers. The image quality was quantified by region-of-interest (ROI) analysis of signal intensities between arterial blood, venous blood, muscle, and fat. The images were also assessed for diagnostic quality by a trained radiologist. The bSSFP Dixon method was successful in producing non-contrast-enhanced (NCE) images of the blood vessels in the lower limbs. The work presented here is a proof-of-concept for the use of the bSSFP Dixon method for 3D peripheral angiography.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".