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      Non-invasive assessment of skeletal muscle fibrosis in mice using nuclear magnetic resonance imaging and ultrasound shear wave elastography

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          Abstract

          Fibrosis is a key pathological feature in muscle disorders, but its quantification mainly relies on histological and biochemical assays. Muscle fibrosis most frequently is entangled with other pathological processes, as cell membrane lesions, inflammation, necrosis, regeneration, or fatty infiltration, making in vivo assessment difficult. Here, we (1) describe a novel mouse model with variable levels of induced skeletal muscle fibrosis displaying minimal inflammation and no fat infiltration, and (2) report how fibrosis affects non-invasive metrics derived from nuclear magnetic resonance (NMR) and ultrasound shear-wave elastography (SWE) associated with a passive biomechanical assay. Our findings show that collagen fraction correlates with multiple non-invasive metrics. Among them, muscle stiffness as measured by SWE, T 2, and extracellular volume (ECV) as measured by NMR have the strongest correlations with histology. We also report that combining metrics in a multi-modality index allowed better discrimination between fibrotic and normal skeletal muscles. This study demonstrates that skeletal muscle fibrosis leads to alterations that can be assessed in vivo with multiple imaging parameters. Furthermore, combining NMR and SWE passive biomechanical assay improves the non-invasive evaluation of skeletal muscle fibrosis and may allow disentangling it from co-occurring pathological alterations in more complex scenarios, such as muscular dystrophies.

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          Most cited references37

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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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 http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.
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              Accuracy of real-time shear wave elastography for assessing liver fibrosis in chronic hepatitis C: a pilot study.

              Real-time shear wave elastography (SWE) is a novel, noninvasive method to assess liver fibrosis by measuring liver stiffness. This single-center study was conducted to assess the accuracy of SWE in patients with chronic hepatitis C (CHC), in comparison with transient elastography (TE), by using liver biopsy (LB) as the reference standard. Consecutive patients with CHC scheduled for LB by referring physicians were studied. One hundred and twenty-one patients met inclusion criteria. On the same day, real-time SWE using the ultrasound (US) system, Aixplorer (SuperSonic Imagine S.A., Aix-en-Provence, France), TE using FibroScan (Echosens, Paris, France), and US-assisted LB were consecutively performed. Fibrosis was staged according to the METAVIR scoring system. Analyses of receiver operating characteristic (ROC) curve were performed to calculate optimal area under the ROC curve (AUROC) for F0-F1 versus F2-F4, F0- F2 versus F3-F4, and F0-F3 versus F4 for both real-time SWE and TE. Liver stiffness values increased in parallel with degree of liver fibrosis, both with SWE and TE. AUROCs were 0.92 (95% confidence interval [CI]: 0.85-0.96) for SWE and 0.84 (95% CI: 0.76-0.90) for TE (P = 0.002), 0.98 (95% CI: 0.94-1.00) for SWE and 0.96 (95% CI: 0.90-0.99) for TE (P = 0.14), and 0.98 (95% CI: 0.93-1.00) for SWE and 0.96 (95% CI: 0.91-0.99) for TE (P = 0.48), when comparing F0-F1 versus F2- F4, F0- F2 versus F3-F4, and F0 -F3 versus F4, respectively. The results of this study show that real-time SWE is more accurate than TE in assessing significant fibrosis (≥ F2). With respect to TE, SWE has the advantage of imaging liver stiffness in real time while guided by a B-mode image. Thus, the region of measurement can be guided with both anatomical and tissue stiffness information. Copyright © 2012 American Association for the Study of Liver Diseases.
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                Author and article information

                Contributors
                aurea.martinsbach@ndcn.ox.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 January 2021
                11 January 2021
                2021
                : 11
                : 284
                Affiliations
                [1 ]GRID grid.418250.a, ISNI 0000 0001 0308 8843, AIM & CEA NMR Laboratory, Neuromuscular Investigation Center, , Institute of Myology, ; Paris, France
                [2 ]GRID grid.418250.a, ISNI 0000 0001 0308 8843, Neuromuscular Physiology Laboratory, Neuromuscular Investigation Center, , Institute of Myology, ; Paris, France
                [3 ]GRID grid.11843.3f, ISNI 0000 0001 2157 9291, Université de Strasbourg, CNRS, ICube, FMTS, ; Strasbourg, France
                Article
                78747
                10.1038/s41598-020-78747-8
                7801669
                33431931
                f55914d3-dade-45b7-8bf9-ee6c66bf8f3c
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 March 2020
                : 17 November 2020
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                © The Author(s) 2021

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                diagnostic markers,neuromuscular disease,magnetic resonance imaging,ultrasonography

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