Automated ultrasound edge‐tracking software comparable to established semi‐automated reference software for carotid intima‐media thickness analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many commercial ultrasound systems are now including automated analysis packages for the determination of carotid intima-media thickness (cIMT); however, details regarding their algorithms and methodology are not published. Few studies have compared their accuracy and reliability with previously established automated software, and those that have were in asymptomatic adults. Therefore, this study compared cIMT measures from a fully automated ultrasound edge-tracking software (EchoPAC PC, Version 110.0.2; GE Medical Systems, Horten, Norway) to an established semi-automated reference software (Artery Measurement System (AMS) II, Version 1.141; Gothenburg, Sweden) in 30 healthy preschool children (ages 3-5 years) and 27 adults with coronary artery disease (CAD; ages 48-81 years). For both groups, Bland-Altman plots revealed good agreement with a negligible mean cIMT difference of -0·03 mm. Software differences were statistically, but not clinically, significant for preschool images (P = 0·001) and were not significant for CAD images (P = 0·09). Intra- and interoperator repeatability was high and comparable between software for preschool images (ICC, 0·90-0·96; CV, 1·3-2·5%), but slightly higher with the automated ultrasound than the semi-automated reference software for CAD images (ICC, 0·98-0·99; CV, 1·4-2·0% versus ICC, 0·84-0·89; CV, 5·6-6·8%). These findings suggest that the automated ultrasound software produces valid cIMT values in healthy preschool children and adults with CAD. Automated ultrasound software may be useful for ensuring consistency among multisite research initiatives or large cohort studies involving repeated cIMT measures, particularly in adults with documented CAD.
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.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it