PURPOSE: To evaluate the diagnostic accuracy of magnetic resonance (MR) elastography as a method to help diagnose clinically substantial fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) and, by using MR elastography as a reference standard, to compare various laboratory marker panels in the identification of patients with NAFLD and advanced fibrosis. MATERIALS AND METHODS: This retrospective study was institutional review board approved and HIPAA complaint. Informed consent was waived. This study was conducted in patients with NAFLD, who were identified by imaging characteristics consistent with steatosis in a prospective database that tracks all MR elastographic examinations. Six laboratory-based models of fibrosis were compared with MR elastographic results as well as fibrosis stage from liver biopsy results. The area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value, and negative predictive value of each data set were compared. RESULTS: Among 325 patients with NAFLD with MR elastographic data, there were 142 patients who underwent liver biopsy within 1 year of MR elastography. When comparing MR elastography results with liver biopsy results, the best cutoff for advanced fibrosis (stage F3-F4, 46 [32.4%] of 142) was 4.15 kPa (AUROC = 0.954, sensitivity = 0.85, specificity = 0.929). This cutoff value identified 104 patients with advanced fibrosis (32.0% of 325 patients). The FIB-4 score (AUROC = 0.827) and NAFLD fibrosis score (AUROC = 0.821) had the best diagnostic accuracy for advanced fibrosis, with high negative predictive values (NAFLD fibrosis score = 0.90 and FIB-4 score = 0.899). CONCLUSION: MR elastography is a useful diagnostic tool for detecting advanced fibrosis in NAFLD. Of the laboratory-based methods, the NAFLD fibrosis and FIB-4 scores can most reliably detect advanced fibrosis.
PURPOSE: To evaluate the diagnostic accuracy of magnetic resonance (MR) elastography as a method to help diagnose clinically substantial fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) and, by using MR elastography as a reference standard, to compare various laboratory marker panels in the identification of patients with NAFLD and advanced fibrosis. MATERIALS AND METHODS: This retrospective study was institutional review board approved and HIPAA complaint. Informed consent was waived. This study was conducted in patients with NAFLD, who were identified by imaging characteristics consistent with steatosis in a prospective database that tracks all MR elastographic examinations. Six laboratory-based models of fibrosis were compared with MR elastographic results as well as fibrosis stage from liver biopsy results. The area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value, and negative predictive value of each data set were compared. RESULTS: Among 325 patients with NAFLD with MR elastographic data, there were 142 patients who underwent liver biopsy within 1 year of MR elastography. When comparing MR elastography results with liver biopsy results, the best cutoff for advanced fibrosis (stage F3-F4, 46 [32.4%] of 142) was 4.15 kPa (AUROC = 0.954, sensitivity = 0.85, specificity = 0.929). This cutoff value identified 104 patients with advanced fibrosis (32.0% of 325 patients). The FIB-4 score (AUROC = 0.827) and NAFLD fibrosis score (AUROC = 0.821) had the best diagnostic accuracy for advanced fibrosis, with high negative predictive values (NAFLD fibrosis score = 0.90 and FIB-4 score = 0.899). CONCLUSION: MR elastography is a useful diagnostic tool for detecting advanced fibrosis in NAFLD. Of the laboratory-based methods, the NAFLD fibrosis and FIB-4 scores can most reliably detect advanced fibrosis.
Authors: E W Steyerberg; F E Harrell; G J Borsboom; M J Eijkemans; Y Vergouwe; J D Habbema Journal: J Clin Epidemiol Date: 2001-08 Impact factor: 6.437
Authors: M Sasso; I Tengher-Barna; M Ziol; V Miette; C Fournier; L Sandrin; R Poupon; A-C Cardoso; P Marcellin; C Douvin; V de Ledinghen; J-C Trinchet; M Beaugrand Journal: J Viral Hepat Date: 2011-10-13 Impact factor: 3.728
Authors: Ewout W Steyerberg; Sacha E Bleeker; Henriëtte A Moll; Diederick E Grobbee; Karel G M Moons Journal: J Clin Epidemiol Date: 2003-05 Impact factor: 6.437
Authors: Norah J Shire; Meng Yin; Jun Chen; Radha A Railkar; Sabrina Fox-Bosetti; Stephanie M Johnson; Chan R Beals; Bernard J Dardzinski; Schuyler O Sanderson; Jayant A Talwalkar; Richard L Ehman Journal: J Magn Reson Imaging Date: 2011-07-12 Impact factor: 4.813
Authors: Thierry Poynard; Victor de Ledinghen; Jean Pierre Zarski; Carol Stanciu; Mona Munteanu; Julien Vergniol; Julie France; Anca Trifan; Gilles Le Naour; Jean Christophe Vaillant; Vlad Ratziu; Frederic Charlotte Journal: J Hepatol Date: 2011-09-01 Impact factor: 25.083
Authors: Robert P Myers; Gilles Pomier-Layrargues; Richard Kirsch; Aaron Pollett; Andres Duarte-Rojo; David Wong; Melanie Beaton; Mark Levstik; Pam Crotty; Magdy Elkashab Journal: Hepatology Date: 2011-11-18 Impact factor: 17.425
Authors: Chun-Tao Wai; Joel K Greenson; Robert J Fontana; John D Kalbfleisch; Jorge A Marrero; Hari S Conjeevaram; Anna S-F Lok Journal: Hepatology Date: 2003-08 Impact factor: 17.425
Authors: Rohit Loomba; Nicholas Schork; Chi-Hua Chen; Ricki Bettencourt; Ana Bhatt; Brandon Ang; Phirum Nguyen; Carolyn Hernandez; Lisa Richards; Joanie Salotti; Steven Lin; Ekihiro Seki; Karen E Nelson; Claude B Sirlin; David Brenner Journal: Gastroenterology Date: 2015-08-20 Impact factor: 22.682
Authors: Siddharth Singh; Sudhakar K Venkatesh; Rohit Loomba; Zhen Wang; Claude Sirlin; Jun Chen; Meng Yin; Frank H Miller; Russell N Low; Tarek Hassanein; Edmund M Godfrey; Patrick Asbach; Mohammad Hassan Murad; David J Lomas; Jayant A Talwalkar; Richard L Ehman Journal: Eur Radiol Date: 2015-08-28 Impact factor: 5.315