ArticleBioMed research international2015
Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T.
Article in BioMed research international, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Late Gadolinium Enhancement Entropy as a Novel Imaging Biomarker of Myocardial Tissue Heterogeneity-A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Superparamagnetic iron oxide nanoparticles in clinical applications: current status and future perspectives.EBioMedicine · 2025Review
- Comparative Analysis of CT Texture in Lumbar and Femur and Its Correlation with Bone Mineral Density and Content over Time: An Exploratory Study.Diagnostics (Basel, Switzerland) · 2023Article
- Usefulness of Noncontrast MRI-Based Radiomics Combined Clinic Biomarkers in Stratification of Liver Fibrosis.Canadian journal of gastroenterology & hepatology · 2022Article
- Use of Texture Analysis on Noncontrast MRI in Classification of Early Stage of Liver Fibrosis.Canadian journal of gastroenterology & hepatology · 2021Article
- Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis.Chinese medical journal · 2020Article
- Inflammatory lesions and brain tumors: is it possible to differentiate them based on texture features in magnetic resonance imaging?The journal of venomous animals and toxins including tropical diseases · 2020Article
- Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology.European radiology · 2020Article
- Deep residual nets model for staging liver fibrosis on plain CT images.International journal of computer assisted radiology and surgery · 2020Article
- Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability.Quantitative imaging in medicine and surgery · 2019Article
- Liver Fibrosis Conventional and Molecular Imaging Diagnosis Update.Journal of liver · 2019Article
- Imaging of Hepatic Fibrosis.Current gastroenterology reports · 2018Review
- Gestational and lactational exposure to dichlorinated bisphenol A induces early alterations of hepatic lipid composition in mice.Magma (New York, N.Y.) · 2018Article
- Relationship between Extension or Texture Features of Late Gadolinium Enhancement and Ventricular Tachyarrhythmias in Hypertrophic Cardiomyopathy.BioMed research international · 2018Observational
- Liver Fibrosis Quantification by Magnetic Resonance Imaging.Topics in magnetic resonance imaging : TMRI · 2017Review
- Magnetic resonance elastography assessment of fibrosis in children with NAFLD: Promising but not perfect.Hepatology (Baltimore, Md.) · 2017Article
- Evaluation of hepatic fibrosis: a review from the society of abdominal radiology disease focus panel.Abdominal radiology (New York) · 2017Review
- A comprehensive literatures update of clinical researches of superparamagnetic resonance iron oxide nanoparticles for magnetic resonance imaging.Quantitative imaging in medicine and surgery · 2017Review
- Heavy Metal Accumulation is Associated with Molecular and Pathological Perturbations in Liver of Variola louti from the Jeddah Coast of Red Sea.International journal of environmental research and public health · 2016Article
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13 authors.
Funding
Abstract
purposeTo noninvasively assess liver fibrosis using combined-contrast-enhanced (CCE) magnetic resonance imaging (MRI) and texture analysis. MATERIALS AND
methodsIn this IRB-approved, HIPAA-compliant prospective study, 46 adults with newly diagnosed HCV infection and recent liver biopsy underwent CCE liver MRI following intravenous administration of superparamagnetic iron oxides (ferumoxides) and gadolinium DTPA (gadopentetate dimeglumine). The image texture of the liver was quantified in regions-of-interest by calculating 165 texture features. Liver biopsy specimens were stained with Masson trichrome and assessed qualitatively (METAVIR fibrosis score) and quantitatively (% collagen stained area). Using L 1 regularization path algorithm, two texture-based multivariate linear models were constructed, one for quantitative and the other for quantitative histology prediction. The prediction performance of each model was assessed using receiver operating characteristics (ROC) and correlation analyses.
resultsThe texture-based predicted fibrosis score significantly correlated with qualitative (r = 0.698, P < 0.001) and quantitative (r = 0.757, P < 0.001) histology. The prediction model for qualitative histology had 0.814-0.976 areas under the curve (AUC), 0.659-1.000 sensitivity, 0.778-0.930 specificity, and 0.674-0.935 accuracy, depending on the binary classification threshold. The prediction model for quantitative histology had 0.742-0.950 AUC, 0.688-1.000 sensitivity, 0.679-0.857 specificity, and 0.696-0.848 accuracy, depending on the binary classification threshold.
conclusionCCE MRI and texture analysis may permit noninvasive assessment of liver fibrosis.
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