Fast spin echo imaging of carotid artery dynamics
Bibliographic record
Abstract
PURPOSE: We propose the use of a retrospectively gated cine fast spin echo (FSE) sequence for characterization of carotid artery dynamics. The aim of this study was to compare cine FSE measures of carotid dynamics with measures obtained on prospectively gated FSE images. METHODS: The common carotid arteries in 10 volunteers were imaged using two temporally resolved sequences: (i) cine FSE and (ii) prospectively gated FSE. Three raters manually traced a common carotid artery area for all cardiac phases on both sequences. Measured areas and systolic-diastolic area changes were calculated and compared. Inter- and intra-rater reliability were assessed for both sequences. RESULTS: No significant difference between cine FSE and prospectively gated FSE areas were observed (P = 0.36). Both sequences produced repeatable cross-sectional area measurements: inter-rater intraclass correlation coefficient (ICC) = 0.88 on cine FSE images and 0.87 on prospectively gated FSE images. Minimum detectable difference (MDD) in systolic-diastolic area was 4.9 mm(2) with cine FSE and 6.4 mm(2) with prospectively gated FSE. CONCLUSION: This cine FSE method produced repeatable dynamic carotid artery measurements with less artifact and greater temporal efficiency compared with prospectively gated FSE.
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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 | 0.004 |
| 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 | 0.001 | 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".