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      Non-Invasive Assessment of Hepatic Steatosis in Patients with NAFLD Using Controlled Attenuation Parameter and 1H-MR Spectroscopy

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          Non-invasive assessment of steatosis and fibrosis is of growing relevance in non-alcoholic fatty liver disease (NAFLD). 1H-Magnetic resonance spectroscopy ( 1H-MRS) and the ultrasound-based controlled attenuation parameter (CAP) correlate with biopsy proven steatosis, but have not been correlated with each other so far. We therefore performed a head-to-head comparison between both methods.


          Fifty patients with biopsy-proven NAFLD and 15 healthy volunteers were evaluated with 1H-MRS and transient elastography (TE) including CAP. Steatosis was defined according to the percentage of affected hepatocytes: S1 5-33%, S2 34–66%, S3 ≥67%.


          Steatosis grade in patients with NAFLD was S1 36%, S2 40% and S3 24%. CAP and 1H-MRS significantly correlated with histopathology and showed comparable accuracy for the detection of hepatic steatosis: areas under the receiver-operating characteristics curves were 0.93 vs. 0.88 for steatosis ≥S1 and 0.94 vs. 0.88 for ≥S2, respectively. Boot-strapping analysis revealed a CAP cut-off of 300 dB/m for detection of S2-3 steatosis, while retaining the lower cut-off of 215 dB/m for the definition of healthy individuals. Direct comparison between CAP and 1H-MRS revealed only modest correlation (total cohort: r = 0.63 [0.44, 0.76]; NAFLD cases: r = 0.56 [0.32, 0.74]). For detection of F2–4 fibrosis TE had sensitivity and specificity of 100% and 98.1% at a cut-off value of 8.85 kPa.


          Our data suggest a comparable diagnostic value of CAP and 1H-MRS for hepatic steatosis quantification. Combined with the simultaneous TE fibrosis assessment, CAP represents an efficient method for non-invasive characterization of NAFLD. Limited correlation between CAP and 1H-MRS may be explained by different technical aspects, anthropometry, and presence of advanced liver fibrosis.

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          Most cited references 55

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          Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

          Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
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            Design and validation of a histological scoring system for nonalcoholic fatty liver disease.

            Nonalcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis in the absence of a history of significant alcohol use or other known liver disease. Nonalcoholic steatohepatitis (NASH) is the progressive form of NAFLD. The Pathology Committee of the NASH Clinical Research Network designed and validated a histological feature scoring system that addresses the full spectrum of lesions of NAFLD and proposed a NAFLD activity score (NAS) for use in clinical trials. The scoring system comprised 14 histological features, 4 of which were evaluated semi-quantitatively: steatosis (0-3), lobular inflammation (0-2), hepatocellular ballooning (0-2), and fibrosis (0-4). Another nine features were recorded as present or absent. An anonymized study set of 50 cases (32 from adult hepatology services, 18 from pediatric hepatology services) was assembled, coded, and circulated. For the validation study, agreement on scoring and a diagnostic categorization ("NASH," "borderline," or "not NASH") were evaluated by using weighted kappa statistics. Inter-rater agreement on adult cases was: 0.84 for fibrosis, 0.79 for steatosis, 0.56 for injury, and 0.45 for lobular inflammation. Agreement on diagnostic category was 0.61. Using multiple logistic regression, five features were independently associated with the diagnosis of NASH in adult biopsies: steatosis (P = .009), hepatocellular ballooning (P = .0001), lobular inflammation (P = .0001), fibrosis (P = .0001), and the absence of lipogranulomas (P = .001). The proposed NAS is the unweighted sum of steatosis, lobular inflammation, and hepatocellular ballooning scores. In conclusion, we present a strong scoring system and NAS for NAFLD and NASH with reasonable inter-rater reproducibility that should be useful for studies of both adults and children with any degree of NAFLD. NAS of > or =5 correlated with a diagnosis of NASH, and biopsies with scores of less than 3 were diagnosed as "not NASH."
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              pROC: an open-source package for R and S+ to analyze and compare ROC curves

              Background Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. Results With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. Conclusions pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                17 March 2014
                : 9
                : 3
                [1 ]IFB AdiposityDiseases, Leipzig University Medical Center, Leipzig, Germany
                [2 ]Department of Medicine, Neurology and Dermatology, Division of Gastroenterology and Rheumatology, University Hospital Leipzig, Leipzig, Germany
                [3 ]Clinical Trial Center, University of Leipzig, Leipzig, Germany
                [4 ]Department of Diagnostics and Interventional Radiology, University Hospital Leipzig, Leipzig, Germany
                [5 ]Department of Medicine, Neurology and Dermatology, Division of Gastroenterology and Rheumatology, Section of Hepatology, University Hospital Leipzig, Leipzig, Germany
                [6 ]Institute of Pathology, University Hospital Leipzig, Leipzig, Germany
                [7 ]Clinic for Gastroenterology and Hepatology, Klinikum St. Georg, Leipzig, Germany
                Lady Davis Institute for Medical Research/McGill University, Canada
                Author notes

                Competing Interests: The authors have read the journal's policy and have the following conflicts: TK received travel grants from Echosens/France. All other authors have declared that no competing interests exist. The authors confirm that this does not alter their adherence to all PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: T. Karlas NG HT CW HB T. Kahn JM TB MT VK JW. Performed the experiments: T. Karlas NG SB CW NL AS HB MT VK JW. Analyzed the data: T. Karlas DP NG SB CW MW IS NL AS HB T. Kahn JM TB MT VK JW. Contributed reagents/materials/analysis tools: T. Karlas DP NG SB HT CW MW IS NL AS HB T. Kahn JM TB MT VK JW. Wrote the paper: T. Karlas DP NG SB HT CW HB JM TB MT VK JW. Figure preparation: DP. Study Logistics: HT. Reference Pathology: CW. Revision of manuscript: MW IS NL AS T. Kahn.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Pages: 11
                This work was supported by the Federal Ministry of Education and Research (BMBF), Germany, FKZ: 01EO1001 (Project No. K7-40). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Gastroenterology and Hepatology
                Liver Diseases
                Nonalcoholic Steatohepatitis
                Radiology and Imaging
                Physical Sciences
                Applied Chemistry
                Chemical Properties
                Physical Chemistry
                Condensed Matter Physics
                Nuclear Magnetic Resonance



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