OBJECTIVES: To assess magnetic resonance imaging (MRI) with conventional chemical shift-based sequences with and without T2* correction for the evaluation of steatosis hepatitis (SH) in the presence of iron. METHODS: Thirty-one patients who underwent MRI and liver biopsy because of clinically suspected diffuse liver disease were retrospectively analysed. The signal intensity (SI) was calculated in co-localised regions of interest (ROIs) using conventional spoiled gradient-echo T1 FLASH in-phase and opposed-phase (IP/OP). T2* relaxation time was recorded in a fat-saturated multi-echo-gradient-echo sequence. The fat fraction (FF) was calculated with non-corrected and T2*-corrected SIs. Results were correlated with liver biopsy. RESULTS: There was significant difference (P < 0.001) between uncorrected and T2* corrected FF in patients with SH and concomitant hepatic iron overload (HIO). Using 5 % as a threshold resulted in eight false negative results with uncorrected FF whereas T2* corrected FF lead to true positive results in 5/8 patients. ROC analysis calculated three threshold values (8.97 %, 5.3 % and 3.92 %) for T2* corrected FF with accuracy 84 %, sensitivity 83-91 % and specificity 63-88 %. CONCLUSIONS: FF with T2* correction is accurate for the diagnosis of hepatic fat in the presence of HIO. Findings of our study suggest the use of IP/OP imaging in combination with T2* correction. KEY POINTS: • Magnetic resonance helps quantify both iron and fat content within the liver • T2* correction helps to predict the correct diagnosis of steatosis hepatitis • "Fat fraction" from T2*-corrected chemical shift-based sequences accurately quantifies hepatic fat • "Fat fraction" without T2* correction underestimates hepatic fat with iron overload.
OBJECTIVES: To assess magnetic resonance imaging (MRI) with conventional chemical shift-based sequences with and without T2* correction for the evaluation of steatosis hepatitis (SH) in the presence of iron. METHODS: Thirty-one patients who underwent MRI and liver biopsy because of clinically suspected diffuse liver disease were retrospectively analysed. The signal intensity (SI) was calculated in co-localised regions of interest (ROIs) using conventional spoiled gradient-echo T1 FLASH in-phase and opposed-phase (IP/OP). T2* relaxation time was recorded in a fat-saturated multi-echo-gradient-echo sequence. The fat fraction (FF) was calculated with non-corrected and T2*-corrected SIs. Results were correlated with liver biopsy. RESULTS: There was significant difference (P < 0.001) between uncorrected and T2* corrected FF in patients with SH and concomitant hepatic iron overload (HIO). Using 5 % as a threshold resulted in eight false negative results with uncorrected FF whereas T2* corrected FF lead to true positive results in 5/8 patients. ROC analysis calculated three threshold values (8.97 %, 5.3 % and 3.92 %) for T2* corrected FF with accuracy 84 %, sensitivity 83-91 % and specificity 63-88 %. CONCLUSIONS: FF with T2* correction is accurate for the diagnosis of hepatic fat in the presence of HIO. Findings of our study suggest the use of IP/OP imaging in combination with T2* correction. KEY POINTS: • Magnetic resonance helps quantify both iron and fat content within the liver • T2* correction helps to predict the correct diagnosis of steatosis hepatitis • "Fat fraction" from T2*-corrected chemical shift-based sequences accurately quantifies hepatic fat • "Fat fraction" without T2* correction underestimates hepatic fat with iron overload.
Authors: H Levenson; F Greensite; J Hoefs; L Friloux; G Applegate; E Silva; G Kanel; R Buxton Journal: AJR Am J Roentgenol Date: 1991-02 Impact factor: 3.959
Authors: Mark Bydder; Masoud Shiehmorteza; Takeshi Yokoo; Sebastian Sugay; Michael S Middleton; Olivier Girard; Michael E Schroeder; Tanya Wolfson; Anthony Gamst; Claude Sirlin Journal: Magn Reson Imaging Date: 2010-04-21 Impact factor: 2.546
Authors: David E Kleiner; Elizabeth M Brunt; Mark Van Natta; Cynthia Behling; Melissa J Contos; Oscar W Cummings; Linda D Ferrell; Yao-Chang Liu; Michael S Torbenson; Aynur Unalp-Arida; Matthew Yeh; Arthur J McCullough; Arun J Sanyal Journal: Hepatology Date: 2005-06 Impact factor: 17.425
Authors: Benedikt Schaefer; David Haschka; Armin Finkenstedt; Britt-Sabina Petersen; Igor Theurl; Benjamin Henninger; Andreas R Janecke; Chia-Yu Wang; Herbert Y Lin; Lothar Veits; Wolfgang Vogel; Günter Weiss; Andre Franke; Heinz Zoller Journal: Hum Mol Genet Date: 2015-08-26 Impact factor: 6.150
Authors: Camilo A Campo; Diego Hernando; Tilman Schubert; Candice A Bookwalter; Andrew J Van Pay; Scott B Reeder Journal: AJR Am J Roentgenol Date: 2017-07-13 Impact factor: 3.959
Authors: Guido M Kukuk; Kanishka Hittatiya; Alois M Sprinkart; Holger Eggers; Jürgen Gieseke; Wolfgang Block; Philipp Moeller; Winfried A Willinek; Ulrich Spengler; Jonel Trebicka; Hans-Peter Fischer; Hans H Schild; Frank Träber Journal: Eur Radiol Date: 2015-04-23 Impact factor: 5.315
Authors: B Henninger; H Zoller; S Rauch; M Schocke; S Kannengiesser; X Zhong; G Reiter; W Jaschke; C Kremser Journal: Eur Radiol Date: 2014-12-14 Impact factor: 5.315
Authors: Francesco Paparo; Giovanni Cenderello; Matteo Revelli; Lorenzo Bacigalupo; Mariangela Rutigliani; Daniele Zefiro; Luca Cevasco; Maria Amico; Roberto Bandelloni; Giovanni Cassola; Gian Luca Forni; Gian Andrea Rollandi Journal: Biomed Res Int Date: 2015-03-19 Impact factor: 3.411