Between‐Visit Reproducibility of Shear Wave Viscoelastography in Volunteers and Patients With Metabolic Dysfunction‐Associated Steatotic Liver Disease
Bibliographic record
Abstract
OBJECTIVE: To assess the reproducibility of six ultrasound (US)-determined shear wave (SW) viscoelastography parameters for assessment of mechanical properties of the liver in volunteers and patients with biopsy-proven metabolic dysfunction-associated steatotic liver disease (MASLD) or metabolic dysfunction-associated steatohepatitis (MASH). METHODS: This prospective, cross-sectional, institutional review board-approved study included 10 volunteers and 20 patients with MASLD or MASH who underwent liver US elastography twice, at least 2 weeks apart. SW speed (SWS), Young's modulus (E), shear modulus (G), SW attenuation (SWA), SW dispersion (SWD), and viscosity were computed from radiofrequency data recorded on a research US scanner. Linear mixed models were used to consider the sonographer on duty as a confounder. The reproducibility of measurements was assessed by intraclass correlation coefficient (ICC), coefficient of variation (CV), reproducibility coefficient (RDC), and Bland-Altman analyses. RESULTS: The sonographer performing the exam had no impact on viscoelastic parameters (P > .05). ICCs of SWS, E, G, SWA, SWD, and viscosity were, respectively, 0.89 (95% confidence intervals [CI]: 0.79-0.95), 0.81 (95% CI: 0.79-0.95), 0.90 (95% CI: 0.80-0.95), 0.96 (95% CI: 0.93-0.98), 0.78 (95% CI: 0.60-0.89), and 0.90 (95% CI: 0.80-0.95); CVs were 11.9, 23.3, 24.2, 10.1, 29.0, and 32.2%; RDCs were 33.0, 64.5, 66.9, 27.7, 80.3, and 89.2%, and Bland-Altman mean biases and 95% limits of agreement were -0.05 (-0.45, 0.35) m/s, -0.61 (-5.33, 4.10) kPa, -0.25 (-2.06, 1.56) kPa, -0.01 (-0.27, 0.26) Np/m/Hz, -0.09 (-7.09, 6.91) m/s/kHz, and -0.33 (-2.60, 1.94) Pa/s, between the two visits. CONCLUSION: US-determined viscoelastography parameters can be measured with high reproducibility and consistency between two visits 2 weeks apart on the same ultrasound machine.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".