{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T14:10:56Z","timestamp":1771510256649,"version":"3.50.1"},"reference-count":32,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2015,10,22]],"date-time":"2015-10-22T00:00:00Z","timestamp":1445472000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"NIH","award":["EB01981"],"award-info":[{"award-number":["EB01981"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2016,5]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>MR elastography (MRE) is a phase\u2010contrast MRI technique that is used to quantitatively assess liver stiffness for staging hepatic fibrosis. The current approach requires manual selection of a region of interest (ROI) with good wave quality from which to measure stiffness. The purpose of this work was to develop and evaluate a fully automated approach for measuring hepatic stiffness from MRE images to further reduce measurement variability.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>An automated liver elasticity calculation (ALEC) algorithm was developed to address reader stiffness measurement variability. ALEC has three stages: initial tissue estimation, segmentation, and ROI cleanup. Stiffnesses measured by the algorithm were compared with technicians and an expert radiologist in a set of 121 clinical cases acquired at 1.5 Tesla. Intra\u2010class correlation (ICC), Bland\u2010Altman analysis, and a noninferiority test were performed to evaluate whether the algorithm can be used in place of manual analysis by technicians.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The stiffness measurement difference with the expert was 1.42%\u2009\u00b1\u200911.17% (mean\u2009\u00b1\u2009standard deviation) for the algorithm and 1.82%\u2009\u00b1\u200913.65% for the technicians. The ICCs were 0.981 and 0.984, respectively. Both the algorithm and technicians were equivalent to the expert within a 5% significance margin (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01). The algorithm had no failures in the 119 cases that were considered analyzable by the human readers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The results of this study show that the newly developed automated algorithm is able to measure stiffness in clinical liver MRE exams with an accuracy that is equivalent to that of an expert radiologist. ALEC may be useful for analysis of archived data and suitable for performing multi\u2010center studies. J. Magn. Reson. 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