Optimization of Computed Tomography Coronary Angiography for Improved Plaque Detection
Bibliographic record
Abstract
OBJECTIVE: The study aims to optimize visualization of the coronary wall during computed tomography coronary angiography. METHODS: A coronary plaque phantom was scanned on a wide-volume computed tomography scanner. Spatial resolution, contrast resolution, and vessel wall thickness were measured at different x-ray tube currents and voltages. RESULTS: Spatial resolution ranged from 0.385 to 0.625 mm and was significantly lower at higher currents. Contrast-to-noise ratio was significantly higher at higher currents. The most accurate wall thickness measurements were quantified at 300 and 400 mA for 80 and 100 kVp and 300 mA for 120 and 135 kVp. CONCLUSIONS: Lower spatial resolution at higher currents was due to added blur from increased focal spot size. Contrast-to-noise ratio was higher at higher currents owing to decreased quantum noise. Wall thickness was measured more accurately at intermediate currents with midrange contrast-to-noise ratio but optimal spatial resolution. For accurate coronary wall thickness measurement, contrast-to-noise ratio is compromised to achieve optimal spatial resolution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".