PURPOSE: To compare the accuracy of four chemical shift magnetic resonance imaging (MRI) (CS-MRI) analysis methods and MR spectroscopy (MRS) with and without T2-correction in fat quantification in the presence of excess iron. MATERIALS AND METHODS: CS-MRI with six opposed- and in-phase acquisitions and MRS with five-echo acquisitions (TEs of 20, 30, 40, 50, 60 msec) were performed at 1.5 T on phantoms containing various fat fractions (FFs), on phantoms containing various iron concentrations, and in 18 patients with chronic liver disease. For CS-MRI, FFs were estimated with the dual-echo method, with two T2*-correction methods (triple- and multiecho), and with multiinterference methods that corrected for both T2* and spectral interference effects. For MRS, FF was estimated without T2-correction (single-echo MRS) and with T2-correction (multiecho MRS). RESULTS: In the phantoms, T2*- or T2-correction methods for CS-MRI and MRS provided unbiased estimations of FFs (mean bias, -1.1% to 0.5%) regardless of iron concentration, whereas the dual-echo method (-5.5% to -8.4%) and single-echo MRS (12.1% to 37.3%) resulted in large biases in FFs. In patients, the FFs estimated with triple-echo (R = 0.98), multiecho (R = 0.99), and multiinterference (R = 0.99) methods had stronger correlations with multiecho MRS FFs than with the dual-echo method (R = 0.86; P ≤ 0.011). The FFs estimated with multiinterference method showed the closest agreement with multiecho MRS FFs (the 95% limit-of-agreement, -0.2 ± 1.1). CONCLUSION: T2*- or T2-correction methods are effective in correcting the confounding effects of iron, enabling an accurate fat quantification throughout a wide range of iron concentrations. Spectral modeling of fat may further improve the accuracy of CS-MRI in fat quantification.
PURPOSE: To compare the accuracy of four chemical shift magnetic resonance imaging (MRI) (CS-MRI) analysis methods and MR spectroscopy (MRS) with and without T2-correction in fat quantification in the presence of excess iron. MATERIALS AND METHODS:CS-MRI with six opposed- and in-phase acquisitions and MRS with five-echo acquisitions (TEs of 20, 30, 40, 50, 60 msec) were performed at 1.5 T on phantoms containing various fat fractions (FFs), on phantoms containing various iron concentrations, and in 18 patients with chronic liver disease. For CS-MRI, FFs were estimated with the dual-echo method, with two T2*-correction methods (triple- and multiecho), and with multiinterference methods that corrected for both T2* and spectral interference effects. For MRS, FF was estimated without T2-correction (single-echo MRS) and with T2-correction (multiecho MRS). RESULTS: In the phantoms, T2*- or T2-correction methods for CS-MRI and MRS provided unbiased estimations of FFs (mean bias, -1.1% to 0.5%) regardless of iron concentration, whereas the dual-echo method (-5.5% to -8.4%) and single-echo MRS (12.1% to 37.3%) resulted in large biases in FFs. In patients, the FFs estimated with triple-echo (R = 0.98), multiecho (R = 0.99), and multiinterference (R = 0.99) methods had stronger correlations with multiecho MRSFFs than with the dual-echo method (R = 0.86; P ≤ 0.011). The FFs estimated with multiinterference method showed the closest agreement with multiecho MRSFFs (the 95% limit-of-agreement, -0.2 ± 1.1). CONCLUSION: T2*- or T2-correction methods are effective in correcting the confounding effects of iron, enabling an accurate fat quantification throughout a wide range of iron concentrations. Spectral modeling of fat may further improve the accuracy of CS-MRI in fat quantification.
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: Brian A Taylor; Ralf B Loeffler; Ruitian Song; M Beth McCarville; Jane S Hankins; Claudia M Hillenbrand Journal: J Magn Reson Imaging Date: 2011-12-16 Impact factor: 4.813
Authors: William T Triplett; Celine Baligand; Sean C Forbes; Rebecca J Willcocks; Donovan J Lott; Soren DeVos; Jim Pollaro; William D Rooney; H Lee Sweeney; Carsten G Bönnemann; Dah-Jyuu Wang; Krista Vandenborne; Glenn A Walter Journal: Magn Reson Med Date: 2013-09-04 Impact factor: 4.668
Authors: Catherine D G Hines; Rashmi Agni; Calista Roen; Ian Rowland; Diego Hernando; Eric Bultman; Debra Horng; Huanzhou Yu; Ann Shimakawa; Jean H Brittain; Scott B Reeder Journal: J Magn Reson Imaging Date: 2011-11-29 Impact factor: 4.813
Authors: Lucia Pacifico; Michele Di Martino; Caterina Anania; Gian Marco Andreoli; Mario Bezzi; Carlo Catalano; Claudio Chiesa Journal: World J Gastroenterol Date: 2015-04-21 Impact factor: 5.742