Background: Magnetic resonance elastography (MRE) can determine the presence and stage of liver fibrosis. Data on normative MRE values, while reported in adults, are limited in children.
Purpose: To determine the distribution of MRE-measured liver stiffness in children without liver disease.
Study Type: Prospective, observational.
Population: Eighty-one healthy children (mean 12.6 ± 2.6 years, range 8-17 years).
Field Strength/sequence: 3.0T Signa HDxt, General Electric MR Scanner; 2D GRE MRE sequence.
Assessment: History, examination, laboratory evaluation, and (MR) exams (proton density fat fraction, PDFF, and MRE) were performed. MR elastograms were analyzed manually at two reading centers and compared with each other for agreement and with published values in healthy adults and thresholds for fibrosis in adult and pediatric patients.
Statistical Tests: Descriptive statistics, Bland-Altman analysis, t-test to compare hepatic stiffness values with reference standards.
Results: Stiffness values obtained at both reading centers were similar, without significant bias (P = 0.362) and with excellent correlation (intraclass correlation coefficient [ICC] = 0.782). Mean hepatic stiffness value for the study population was 2.45 ± 0.35 kPa (95 percentile 3.19 kPa), which was significantly higher than reported values for healthy adult subjects (2.10 ± 0.23 kPa, P < 0.001). In all, 74-85% of subjects had stiffness measurements suggestive of no fibrosis.
Data Conclusion: Mean liver stiffness measured with MRE in this cohort was significantly higher than that reported in healthy adults. Despite rigorous screening, some healthy children had stiffness measurements suggestive of liver fibrosis using current published thresholds. Although MRE has the potential to provide noninvasive assessment in patients with suspected hepatic disease, further refinement of this technology will help advance its use as a diagnostic tool for evidence of fibrosis in pediatric populations.
Level Of Evidence: 1 Technical Efficacy: 5 J. Magn. Reson. Imaging 2020;51:919-927.
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http://dx.doi.org/10.1002/jmri.26905 | DOI Listing |
Eur Radiol
January 2025
Imaging Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Background: Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis.
Purpose: To develop and validate deep learning (DL) models for predicting MRE-derived liver stiffness using routine clinical non-contrast abdominal T1-weighted (T1w) and T2-weighted (T2w) data from multiple institutions/system manufacturers in pediatric and adult patients.
Arq Gastroenterol
January 2025
Universidade Federal de São Paulo, São Paulo, SP, Brasil.
Background: Liver biopsy (LB) is still the gold standard method for assessing hepatic fibrosis (HF), associated diseases, and liver inflammation. Nowadays, noninvasive techniques such as Acoustic radiation force impulse (ARFI) elastography have been introduced instead of liver biopsy. However, there are controversies about the time it should be performed after treatment for hepatitis C virus (HCV).
View Article and Find Full Text PDFJ Magn Reson Imaging
February 2025
BioMedical Engineering and Imaging Institute, Icahn School of Medicine Mount Sinai, New York, New York, USA.
Background: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.
Purpose: To report initial results on automatic classification of liver MRE image quality using various deep learning (DL) architectures.
Study Type: Retrospective, single center, IRB-approved human study.
PLOS Glob Public Health
December 2024
Department of Endocrinology, Changhai Hospital, Naval Medical University, Shanghai, People's Republic of China.
To estimate the prevalence and associated factors of hepatic steatosis and fibrosis in adults with type 2 diabetes (T2DM) in the United States.Data were retrieved from the 2017‒March 2020 prepandemic cycle of the National Health and Nutritional Examination and Survey (NHANES). The study population included patients with T2DM.
View Article and Find Full Text PDFHepatol Commun
December 2024
Department of Infectious Diseases, Vestfold Hospital Trust, Tønsberg, Norway.
Background: Little is known about the determinants of disease progression among African patients with chronic HBV infection.
Methods: We used machine-learning models with longitudinal data to establish predictive algorithms in a well-characterized cohort of Ethiopian HBV-infected patients without baseline liver fibrosis. Disease progression was defined as an increase in liver stiffness to >7.
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