Quantification of arterial plaque and lumen density with MDCT
Bibliographic record
Abstract
PURPOSE: This study aimed to derive a mathematical correction function in order to normalize the CT number measurements for small volume arterial plaque and small vessel mimicking objects, imaged with multidetector CT (MDCT). METHODS: A commercially available calcium plaque phantom (QRM GmbH, Moehrendorf, Germany) and a custom built cardiovascular phantom were scanned with 320 and 64 MDCT scanners. The calcium hydroxyapatite plaque phantom contained objects 0.5-5.0 mm in diameter with known CT attenuation nominal values ranging 50-800 HU. The cardiovascular phantom contained vessel mimicking objects 1.0-5.0 mm in diameter with different contrast media. Both phantoms were scanned using clinical protocols for CT angiography and images were reconstructed with different filter kernels. The measured CT number (HU) and diameter of each object were analyzed on three clinical postprocessing workstations. From the resultant data, a mathematical formula was derived based on absorption function exp(--micro.-d) to demonstrate the relation between measured CT numbers and object diameters. RESULTS: The percentage reduction in measured CT number (HU) for the group of selected filter kernels, apparent during CT angiography, is dependent only on the object size (plaque or vessel diameter). The derived formula of the form 1-c.-exp(-a.-d--b) showed reduction in CT number for objects between 0.5 and 5 mm in diameter, with asymptote reaching background noise for small objects with diameters nearing the CT in-plane resolution (0.35 mm). No reduction was observed for the objects with diameters equal or larger than 5 mm. CONCLUSIONS: A clear mathematical relationship exists between object diameter and reduction in measured CT number in HU. This function is independent of exposure parameters and inherent attenuation properties of the objects studied. Future developments include the incorporation of this mathematical model function into quantification software in order to automatically generate a true assessment of measured CT number (HU) corresponding to plaque physical density rho (g/cm(3)). This is a significant development for the accurate, noninvasive classification of noncalcified arterial plaque.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".