Ultrasound Elastography and MR Elastography for Assessing Liver Fibrosis: Part 1, Principles and Techniques.
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ABSTRACT:
SUBMITTER: Tang A
PROVIDER: S-EPMC4819982 | biostudies-literature | 2015 Jul
REPOSITORIES: biostudies-literature
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Ultrasound Elastography and MR Elastography for Assessing Liver Fibrosis: Part 1, Principles and Techniques.
Tang An A Cloutier Guy G Szeverenyi Nikolaus M NM Sirlin Claude B CB
AJR. American journal of roentgenology 20150423 1
<h4>Objective</h4>The purpose of this article is to provide an overview of ultrasound and MR elastography, including a glossary of relevant terminology, a classification of elastography techniques, and a discussion of their respective strengths and limitations.<h4>Conclusion</h4>Elastography is an emerging technique for the noninvasive assessment of mechanical tissue properties. These techniques report metrics related to tissue stiffness, such as shear-wave speed, magnitude of the complex shear ...[more]
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Project description:Tissue stiffness has long been known to be a biomarker of tissue pathology. Ultrasound elastography measures tissue mechanical properties by monitoring the response of tissue to acoustic energy. Different elastographic techniques have been applied to many different tissues and diseases. Depending on the pathology, patient-based factors, and ultrasound operator-based factors, these techniques vary in accuracy and reliability. In this review, we discuss the physical principles of ultrasound elastography, discuss differences between different ultrasound elastographic techniques, and review the advantages and disadvantages of these techniques in clinical practice.
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Project description:PurposeTo evaluate the diagnostic accuracy of magnetic resonance (MR) elastography as a method to help diagnose clinically substantial fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) and, by using MR elastography as a reference standard, to compare various laboratory marker panels in the identification of patients with NAFLD and advanced fibrosis.Materials and methodsThis retrospective study was institutional review board approved and HIPAA complaint. Informed consent was waived. This study was conducted in patients with NAFLD, who were identified by imaging characteristics consistent with steatosis in a prospective database that tracks all MR elastographic examinations. Six laboratory-based models of fibrosis were compared with MR elastographic results as well as fibrosis stage from liver biopsy results. The area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value, and negative predictive value of each data set were compared.ResultsAmong 325 patients with NAFLD with MR elastographic data, there were 142 patients who underwent liver biopsy within 1 year of MR elastography. When comparing MR elastography results with liver biopsy results, the best cutoff for advanced fibrosis (stage F3-F4, 46 [32.4%] of 142) was 4.15 kPa (AUROC = 0.954, sensitivity = 0.85, specificity = 0.929). This cutoff value identified 104 patients with advanced fibrosis (32.0% of 325 patients). The FIB-4 score (AUROC = 0.827) and NAFLD fibrosis score (AUROC = 0.821) had the best diagnostic accuracy for advanced fibrosis, with high negative predictive values (NAFLD fibrosis score = 0.90 and FIB-4 score = 0.899).ConclusionMR elastography is a useful diagnostic tool for detecting advanced fibrosis in NAFLD. Of the laboratory-based methods, the NAFLD fibrosis and FIB-4 scores can most reliably detect advanced fibrosis.
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Project description:Background Stiffness thresholds for liver MR elastography in children vary between studies and may differ from thresholds in adults. Normative liver stiffness data are needed to optimize diagnostic thresholds for children. Purpose To determine normal liver stiffness, and associated normal ranges for children, as measured with MR elastography across vendors and field strengths. Materials and Methods This was a prospective multicenter cohort study (ClinicalTrials.gov identifier: NCT03235414). Volunteers aged 7-17.9 years without a known history of liver disease were recruited at four sites for a research MRI and blood draw between February 2018 and October 2019. MRI was performed on three vendor platforms and at two field strengths (1.5 T and 3.0 T). All MRI scans were centrally analyzed; stiffness, proton density fat fraction (PDFF), and R2* values were expressed as means of means. Mean and 95% confidence intervals (CIs) for liver stiffness were calculated. Pearson correlation coefficient (r), two-sample t test, or analysis of variance was used to assess univariable associations. Results Seventy-one volunteers had complete data and no documented exclusion criterion (median age, 12 years; interquartile range [IQR], 10-15 years; 39 female participants). Median body mass index percentile was 54% (IQR, 32.5%-69.5%). Mean liver stiffness was 2.1 kPa (95% CI: 2.0, 2.2 kPa) with mean ± 1.96 kPa standard deviation of 1.5-2.8 kPa. Median liver PDFF was 2.0% (IQR, 1.7%-2.6%). There was no association between liver stiffness and any patient variable or MRI scanner factor. Conclusion Mean liver stiffness measured with MR elastography in children without liver disease was 2.1 kPa (similar to that in adults). The 95th percentile of normal liver stiffness was 2.8 kPa. Liver stiffness was independent of sex, age, or body mass index and did not vary with MRI scanner vendor or field strength. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Yin in this issue.
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Project description:ObjectiveTo develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard.MethodsThis ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed.ResultsFor classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model.ConclusionRandom forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.
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