Non-Invasive Vascular Elastography as a One-Step Imaging Technique to Evaluate Early Vascular Changes in Children Compared to B-Mode-Based Intima-Media Thickness Technique : A Validation Study Using Inter- and Intra-Rater Reliability
Bibliographic record
Abstract
Background: Childhood obesity is linked to higher adult mortality and morbidity from atherosclerosis. It is primordial to detect at-risk children earlier-on to prevent disease progression. Carotid intima-media thickness (IMT) is a subclinical radiological marker for early atherosclerosis. B-mode ultrasound is a known technique to assess IMT, but no gold standard technique exists in children. Non-invasive vascular elastography (NIVE) using speckle statistics is an innovative alternative to evaluate IMT and adds by providing translation, strain and shear strain measurements. Validation studies for both techniques lack in children. Purpose: Validate the reproducibility of the 2 techniques in Canadian children. Methods: We conducted a prospective study where anthropometry, blood pressure, IMT and elastography were measured. Six operators obtained 2 measurements for both carotid arteries using both techniques, for a total of 720 measurements. Inter- and intra-class correlation coefficients (ICC) were calculated for each measurement technique and elastography parameters. Results: 30 participants (13.0 ± 1.26 years, 17 girls) were recruited. Twelve were overweight. No significant difference was found in mean IMT between weight groups for either technique ( P = .15 and P = .60). We found excellent inter- (ICC = .98 [95% Confidence Interval (CI): .97; .99]) and intra- (ICC = .90-.93) operator reliability for the B-mode technique, and good inter (ICC = .70 [95% CI: .47; .85]) and intra- (ICC = .71-.91) operator reliability for the NIVE-based technique. Poor reliability was found between techniques (ICC = .30 [95% CI: −.31; .65). For elastography parameters, translation was the most reliable (ICC = .94-.95). Conclusion: IMT measurement is reproducible in children but not between techniques. NIVE gives the advantage of evaluating elastography.
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 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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".