Noninvasive vascular elastography for carotid artery characterization on subjects without previous history of atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Noninvasive vascular ultrasound elastography (NIVE) was recently introduced to assess mechanical properties (strain or elasticity) of peripheral vessel walls. The goal of this study was to determine strain values in subjects with normal carotid arteries and the reproducibility of these measurements. METHODS: Sixteen individuals without previous history of carotid atherosclerosis were recruited in four age categories [40-49], [50-59], [60-69], and [70-79] years old. The left and right common and internal carotids (LCC, LIC, RCC, and RIC, respectively) were independently scanned by two radiologists (RAD-A and RAD-B). The axial strain elastograms were computed with the Lagrangian speckle model estimator. RESULTS: Supported by Bland-Altman analyses, strain values between LCC and RCC were found similar with a Pearson correlation coefficient (r) of 0.83 (p < 0.0001). Equivalently, a good correlation was found between RAD-A and RAD-B for common carotids with r=0.80 (p < 0.0001). Lower strain values (p < 0.001) were measured for male common carotids (1.62 +/- 0.32%) than females (2.21 +/- 0.76%). Regarding the internal carotid strain measurements, the correlation was lower between RAD-A and RAD-B with r=0.52 (p=0.01), but drastically decreased between LIC and RIC (r=0.16, nonsignificant). Male internal carotid strain estimates (p=0.03) were lower (1.48 +/- 0.44%) than in females (1.84 +/- 0.64%). Additionally, male common and internal carotid mean elastic moduli varied from 33-106 kPa, whereas it covered a range of 25-67 kPa for females. Female carotids were more elastic (44 +/- 17 kPa) than males (58 +/- 17 kPa, p <0.001). CONCLUSION: Strain measurements in common carotids were found reproducible. However, less consistency was observed for the deeper internal carotids. The NIVE imaging method still remains to be validated with pathological cases, but it might provide a unique approach for stroke prevention and characterization of vascular stiffness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".