Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH

Morin, Jeffrey; Swanson, Terri A.; Rinaldi, Anthony; Boucher, Magalie; Ross, Trenton T.; Hirenallur-Shanthappa, Dinesh

doi:10.3791/62403-v

Cited by 4 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, previous studies have indicated that 72% of NASH patients exhibit lipid abnormalities (22)(23).Furthermore, this study highlights the signi cant value of point shear wave elastography (P-SWE) in the non-invasive assessment of NASH. Recent research has also indicated that measuring liver stiffness using ultrasound elastography may serve as a biomarker for non-invasive diagnosis of fatty liver disease, aligning with the ndings presented in this study (24)(25)(26).Based on these clinical factors, we established a clinical model, which had an AUC of 0.900 in the training set and an AUC of 0.759 in the validation set.…”

Section: Discussionsupporting

confidence: 76%

Machine Learning Model for Non-Alcoholic Steatohepatitis Diagnosis Based on Ultrasound Radiomics

xia,

wei,

wang

et al. 2024

Preprint

View full text Add to dashboard Cite

Background Non-Alcoholic Steatohepatitis(NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predicting the diagnosis of Non-Alcoholic Steatohepatitis. Method An SD rat model of hepatic steatosis was established through a high-fat diet and subcutaneous injection of CCl4. Liver ultrasound images and elastography were acquired, along with serum data and histopathological results of rat livers.The Pyradiomics software was used to extract radiomic features from 2D ultrasound images of rat livers. The rats were then randomly divided into a training set and a validation set, and feature selection was performed through dimensionality reduction. Various machine learning (ML) algorithms were employed to build clinical diagnostic models, radiomic models, and combined diagnostic models. The efficiency of each diagnostic model for diagnosing NASH was evaluated using Receiver Operating Characteristic (ROC) curves, Clinical Decision Curve Analysis (DCA), and calibration curves. Results In the machine learning radiomic model for predicting the diagnosis of NASH, the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve for the clinical radiomic model in the training set and validation set were 0.989 and 0.885, respectively. The Decision Curve Analysis revealed that the clinical radiomic model had the highest net benefit within the probability threshold range of > 65%. The calibration curve in the validation set demonstrated that the clinical combined radiomic model is the optimal method for diagnosing Non-Alcoholic Steatohepatitis. Conclusion The combined diagnostic model constructed using machine learning algorithms based on ultrasound image radiomics has a high clinical predictive performance in diagnosing Non-Alcoholic Steatohepatitis.

show abstract

Section: Discussionsupporting

confidence: 76%

Machine Learning Model for Non-Alcoholic Steatohepatitis Diagnosis Based on Ultrasound Radiomics

xia,

wei,

wang

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Liver biopsy showed that more than 80% of the patients had liver inflammation or even fatty changes. One study in a nonalcoholic steatohepatitis (NASH) model showed that SWE can be used to measure steatosis and shear wave elastography/ultrasound-based imaging can be used to assess disease phenotype and progression (Morin et al 2021). We analyzed the sensitivity and specificity of ultrasonic shear wave to liver inflammation and steatosis through ROC curve.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of liver stiffness using ultrasonic shear wave elastography in patients with COVID-19 induced pneumonia

Meng

et al. 2023

Can. J. Physiol. Pharmacol.

View full text Add to dashboard Cite

In patients with COVID-19-induced pneumonia, shear wave elasticity (SWE) was used to assess liver stiffness. This study included 48 cases of COVID-19-induced pneumonia and 48 cases of normal physical examination. Basic and clinical data, including aspartate aminotransferase, were evaluated (AST). Color ultrasonography was used to test the liver's shear wave elasticity. A biopsy of the liver was also performed. In patients with COVID-19-induced pneumonia, AST and ALT levels were higher than in the control group. Liver SWE showed that liver stiffness is hard (8.745±0.2104) compared with control group (7.386±0.1521)(P<0.0001). Pathological biopsy showed that liver inflammation accounted for 89.58%, steatosis accounted for 81.25%, necrosis accounted for 10.42%, and fibrosis accounted for 33.33% in patients with COVID-19 induced pneumonia. ROC curve analysis showed that the SWE is highly sensitive and specific for the diagnosis of liver inflammation and steatosis. The sensitivity was 88.76%, and the specificity was 77.01% for the evaluation of liver inflammation. For steatosis, the sensitivity was 90.20%, and the specificity was 78.40%. The SWE of liver is useful to assess liver function and pathological status in COVID-19 patients.

show abstract

“…5A), indicating that restoration of PC level in bile reduced hepatocellular or biliary tract injury. Second, measuring liver elasticity is emerging as a non-invasive surrogate to measure liver fibrosis [17]. Thus, we employed shear wave elastography to measure liver elasticity in the Abcb4 -/mice before and after hABCB4 mRNA LNP injections.…”

Section: Abcb4 Mrna Lnp Restores Pc Level In the Abcb4 -/Mouse Modelmentioning

confidence: 99%

Targeting ABCB4 using mRNA-LNP for the treatment of rare liver diseases

Alsuraih

LaViolette

Lin

et al. 2023

Preprint

View full text Add to dashboard Cite

Mutations in the ABCB4 gene lead to a wide-spectrum of rare liver diseases including progressive familial intrahepatic cholestasis type 3 (PFIC3) and low-phospholipid associated cholelithiasis (LPAC) syndrome. PFIC3 patients develop symptoms during late infancy, including severe itching, jaundice, and failure to thrive. The condition may progress to liver failure during childhood or adulthood. This is a highly unmet medical condition where liver transplantation is the only option to correct this disease. Recently, exciting data suggested that restoration of the ABCB4 function via gene replacement could rescue liver phenotypes associated with ABCB4 dysfunction in a pre-clinical PFIC3 mouse model. Here, we used mRNA LNP platform to determine expression and durability of ABCB4 in the liver of wild-type mice. In addition, we generated Abcb4-/- mice to study the efficacy of systemic delivery of ABCB4 mRNA LNP. We observed a robust and durable expression of hABCB4 up to 72 hours post systemic dosing in the liver of wild-type mice. Systemic administration of hABCB4 mRNA achieved a remarkable restoration of phosphatidylcholine levels in bile, a significant decrease in liver stiffness as measured by shear wave elastography, and amelioration of liver histopathology including fibrosis and ductular reaction. We conclude that administration of hABCB4 mRNA LNPs was sufficient to ameliorate fibrosis markers in the PFIC3 mouse model. Our data suggests that gene replacement using mRNA LNP modality could provide an excellent opportunity for patients with biliary diseases.

show abstract

Application of Ultrasound and Shear Wave Elastography Imaging in a Rat Model of NAFLD/NASH

Cited by 4 publications

References 0 publications

Machine Learning Model for Non-Alcoholic Steatohepatitis Diagnosis Based on Ultrasound Radiomics

Machine Learning Model for Non-Alcoholic Steatohepatitis Diagnosis Based on Ultrasound Radiomics

Evaluation of liver stiffness using ultrasonic shear wave elastography in patients with COVID-19 induced pneumonia

Targeting ABCB4 using mRNA-LNP for the treatment of rare liver diseases

Contact Info

Product

Resources

About