Noninvasive vascular ultrasound elastography of carotid arteries for stroke prevention
Bibliographic record
Abstract
Carotid plaque rupture leading to stroke involves alteration of arterial wall mechanical properties. This paper addresses reproducibility and potential clinical impact of non-invasive vascular elastography. Fifteen symptomatic and 15 asymptomatic patients with greater than 50% stenoses of their internal carotids, and 15 control subjects were scanned independently by two radiologists. Radio-frequency cine-loops were acquired on left and right common and proximal internal carotids. For control subjects, homogeneous strains with successive compression and dilatation of the vascular wall from systole to diastole and few shear patterns were observed. The axial strain did not differ between recording sites, sides and radiologists (ANOVA, p > 0.19). For patients, heterogeneous axial strain patterns with both compression and dilatation of tissues within plaques were noted along with shear concentrations at interfaces of tissue structures. Despite similar blood pressures, larger mean instantaneous axial strains were measured in symptomatic (1.5 ± 0.6%) versus asymptomatic (1.2 ± 0.5%) patients in systole for common carotids (t-test, p < 0.02). To conclude, reproducible results were obtained for control subjects and in patients, larger axial strains in common carotids may be associated with plaque rupture. This new imaging method may become a unique approach to characterize vulnerable plaques for stroke prevention.
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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 | 0.005 |
| 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 | 0.000 | 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".