PURPOSE: MR-based quantification of liver magnetic susceptibility may enable field strength-independent measurement of liver iron concentration (LIC). However, susceptibility quantification is challenging, due to nonlocal effects of susceptibility on the B0 field. The purpose of this work is to demonstrate feasibility of susceptibility-based LIC quantification using a fat-referenced approach. METHODS: Phantoms consisting of vials with increasing iron concentrations immersed between oil/water layers, and 27 subjects (9 controls/18 subjects with liver iron overload) were scanned. Ferriscan (1.5 T) provided R2-based reference LIC. Multiecho three-dimensional-SPGR (1.5 T/3 T) enabled fat-water, B0- and R2*-mapping. Phantom iron concentration (mg Fe L(-1)) was estimated from B0 differences (ΔB0) between vials and neighboring oil. Liver susceptibility and LIC (mg Fe g(-1) dry tissue) was estimated from ΔB0 between the lateral right lobe of the liver and adjacent subcutaneous adipose tissue. RESULTS: Estimated phantom iron concentrations had good correlation with true iron concentrations (1.5 T:slope = 0.86, intercept = 0.72, r(2) = 0.98; 3 T:slope = 0.85, intercept = 1.73, r(2) = 0.98). In liver, ΔB0 correlated strongly with R2* (1.5 T:r(2) = 0.86; 3 T:r(2) = 0.93) and B0-LIC had good agreement with Ferriscan-LIC (slopes/intercepts nearly 1.0/0.0, 1.5 T:r(2) = 0.67, slope = 0.93 ± 0.13, P ≈ 0.50, intercept = 1.93 ± 0.78, P ≈ 0.02; 3 T:r(2) = 0.84, slope = 1.01 ± 0.09, P ≈ 0.90, intercept = 0.23 ± 0.52, P ≈ 0.68). DISCUSSION: Fat-referenced, susceptibility-based LIC estimation is feasible at both field strengths. This approach may enable improved susceptibility mapping in the abdomen.
PURPOSE: MR-based quantification of liver magnetic susceptibility may enable field strength-independent measurement of liver iron concentration (LIC). However, susceptibility quantification is challenging, due to nonlocal effects of susceptibility on the B0 field. The purpose of this work is to demonstrate feasibility of susceptibility-based LIC quantification using a fat-referenced approach. METHODS: Phantoms consisting of vials with increasing iron concentrations immersed between oil/water layers, and 27 subjects (9 controls/18 subjects with liver iron overload) were scanned. Ferriscan (1.5 T) provided R2-based reference LIC. Multiecho three-dimensional-SPGR (1.5 T/3 T) enabled fat-water, B0- and R2*-mapping. Phantom iron concentration (mg Fe L(-1)) was estimated from B0 differences (ΔB0) between vials and neighboring oil. Liver susceptibility and LIC (mg Fe g(-1) dry tissue) was estimated from ΔB0 between the lateral right lobe of the liver and adjacent subcutaneous adipose tissue. RESULTS: Estimated phantom iron concentrations had good correlation with true iron concentrations (1.5 T:slope = 0.86, intercept = 0.72, r(2) = 0.98; 3 T:slope = 0.85, intercept = 1.73, r(2) = 0.98). In liver, ΔB0 correlated strongly with R2* (1.5 T:r(2) = 0.86; 3 T:r(2) = 0.93) and B0-LIC had good agreement with Ferriscan-LIC (slopes/intercepts nearly 1.0/0.0, 1.5 T:r(2) = 0.67, slope = 0.93 ± 0.13, P ≈ 0.50, intercept = 1.93 ± 0.78, P ≈ 0.02; 3 T:r(2) = 0.84, slope = 1.01 ± 0.09, P ≈ 0.90, intercept = 0.23 ± 0.52, P ≈ 0.68). DISCUSSION: Fat-referenced, susceptibility-based LIC estimation is feasible at both field strengths. This approach may enable improved susceptibility mapping in the abdomen.
Authors: Aziz H Poonawalla; Brett P Sjoberg; Jennifer L Rehm; Diego Hernando; Catherine D Hines; Pablo Irarrazaval; Scott B Reeder Journal: J Magn Reson Imaging Date: 2012-10-10 Impact factor: 4.813
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: Ante Zhu; Scott B Reeder; Kevin M Johnson; Sydney M Nguyen; Thaddeus G Golos; Ann Shimakawa; Matthias R Muehler; Christopher J Francois; Ian M Bird; Sean B Fain; Dinesh M Shah; Oliver Wieben; Diego Hernando Journal: J Magn Reson Imaging Date: 2019-07-05 Impact factor: 4.813
Authors: Axel J Krafft; Ralf B Loeffler; Ruitian Song; Xiao Bian; M Beth McCarville; Jane S Hankins; Claudia M Hillenbrand Journal: Magn Reson Med Date: 2015-08-26 Impact factor: 4.668
Authors: Ante Zhu; Scott B Reeder; Kevin M Johnson; Sydney M Nguyen; Sean B Fain; Ian M Bird; Thaddeus G Golos; Oliver Wieben; Dinesh M Shah; Diego Hernando Journal: Magn Reson Imaging Date: 2019-10-23 Impact factor: 2.546