High Resolution Shear Wave Elastography for Assessment of Liver Stiffness in a Murine Model of Metabolic Dysfunction-Associated Steatotic Liver Disease
Bibliographic record
Abstract
In the clinical management of liver disease, early diagnosis is paramount. If identified at the stage of steatosis or early fibrosis, liver damage is reversible, and patients can recover. As disease progresses to cirrhosis, the damage to the liver is permanent and patients are at risk for liver failure and hepatocellular carcinoma. Elastography is one imaging tool that is used to assess fibrosis in the liver by measuring tissue stiffness. In this study we set out to validate a novel implementation of shear wave elastography on a commercially available high frequency linear array ultrasound transducer (UHF29x, Vevo F2, FUJIFILM VisualSonics Inc.). It was hypothesized that performing elastography using a high-frequency linear array transducer would enable the assessment of liver stiffness throughout the entire liver, as well as regionally, due to the high anatomical resolution. High-frequency shear wave elastography was performed on diet-induced, Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) mice to assess liver stiffness longitudinally. High resolution ultrasound imaging allowed for superior anatomical identification and when combined with elastography mode, the assessment of stiffness in specific regions of the liver. Increased stiffness (p<0.05) was seen as early as 4 weeks after diet-commencement. Specifically, the median lobe was more greatly affected, compared to other regions of the liver, and the left lobe was least affected. Combining elastography with higher resolution anatomical ultrasound is expected to contribute to advancements in the development of MASLD therapeutics and the study of liver disease in preclinical animal models. Disclosure of funding sources: Authors are employed by, and research was funded by FUJIFILM VisualSonics Inc. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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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) | 0.001 | 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".