3D Liver Shear Wave Absolute Vibro-Elastography with an xMATRIX Array - A Healthy Volunteer Study
Bibliographic record
Abstract
Magnetic resonance elastography (MRE), which quantitatively measures shear modulus over a volume, provides an accurate imaging-based fibrosis staging comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. We present a novel matrix array implementation of the 3D Shear Wave Absolute Vibro-Elastography (S-WAVE)and validate its performance. We use an EPIQ 7G ultrasound machine with an X6-1 xMATRIX transducer (Philips Healthcare, Bothell, WA)to sample tissue motion and reconstruct the elasticity map in 3D. The system was validated for a liver tissue phantom against measurements obtained with transient elastography (FibroScan, Echosens), ultrasound point quantification shear wave elastography (ElastPQ, Philips), 2D shear wave imaging (ElastQ, Philips)and MRE. With ethics approval, five healthy volunteers were imaged with MRE and S-WAVE, and the results indicate that S-WAVE with xMATRIX produces comparable results with MRE.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".