BACKGROUND: MRI has been proposed for non-invasive detection and quantification of liver iron content, but has not been validated as a reproducible and sensitive method, especially in patients with mild iron overload. We aimed to assess the accuracy of a simple, rapid, and easy to implement MRI procedure to detect and quantify hepatic iron stores. METHODS: Of 191 patients recruited, 17 were excluded and 174 studied, 139 in a study group and 35 in a validation group. All patients underwent both percutaneous liver biopsy with biochemical assessment of hepatic iron concentration (B-HIC) and MRI of the liver with various gradient-recalled-echo (GRE) sequences obtained with a 1.5 T magnet. Correlation between liver to muscle (L/M) signal intensity ratio and liver iron concentration was calculated. An algorithm to calculate magnetic resonance hepatic iron concentration (MR-HIC) was developed with data from the study group and then applied to the validation group. FINDINGS: A highly T2-weighted GRE sequence was most sensitive, with 89% sensitivity and 80% specificity in the validation group, with an L/M ratio below 0.88. This threshold allowed us to detect all clinically relevant liver iron overload greater than 60 micromol/g (normal value <36 micromol/g). With other sequences, an L/M ratio less than 1 was highly specific (>87%) for raised hepatic iron concentration. With respect to B-HIC range analysed (3-375 micromol/g), mean difference and 95% CI between B-HIC and MR-HIC were quite similar for study and validation groups (0.8 micromol/g [-6.3 to 7.9] and -2.1 micromol/g [-12.9 to 8.9], respectively). INTERPRETATION: MRI is a rapid, non-invasive, and cost effective technique that could limit use of liver biopsy to assess liver iron content. Our MR-HIC algorithm is designed to be used on various magnetic resonance machines.
BACKGROUND: MRI has been proposed for non-invasive detection and quantification of liver iron content, but has not been validated as a reproducible and sensitive method, especially in patients with mild iron overload. We aimed to assess the accuracy of a simple, rapid, and easy to implement MRI procedure to detect and quantify hepatic iron stores. METHODS: Of 191 patients recruited, 17 were excluded and 174 studied, 139 in a study group and 35 in a validation group. All patients underwent both percutaneous liver biopsy with biochemical assessment of hepatic iron concentration (B-HIC) and MRI of the liver with various gradient-recalled-echo (GRE) sequences obtained with a 1.5 T magnet. Correlation between liver to muscle (L/M) signal intensity ratio and liver iron concentration was calculated. An algorithm to calculate magnetic resonance hepatic iron concentration (MR-HIC) was developed with data from the study group and then applied to the validation group. FINDINGS: A highly T2-weighted GRE sequence was most sensitive, with 89% sensitivity and 80% specificity in the validation group, with an L/M ratio below 0.88. This threshold allowed us to detect all clinically relevant liver iron overload greater than 60 micromol/g (normal value <36 micromol/g). With other sequences, an L/M ratio less than 1 was highly specific (>87%) for raised hepatic iron concentration. With respect to B-HIC range analysed (3-375 micromol/g), mean difference and 95% CI between B-HIC and MR-HIC were quite similar for study and validation groups (0.8 micromol/g [-6.3 to 7.9] and -2.1 micromol/g [-12.9 to 8.9], respectively). INTERPRETATION: MRI is a rapid, non-invasive, and cost effective technique that could limit use of liver biopsy to assess liver iron content. Our MR-HIC algorithm is designed to be used on various magnetic resonance machines.
Authors: Agustin Castiella; Jose M Alústiza; Jose I Emparanza; Eva Ma Zapata; Belen Costero; Maria I Díez Journal: Eur Radiol Date: 2010-08-06 Impact factor: 5.315
Authors: Jens H Jensen; Haiying Tang; Christina L Tosti; Srirama V Swaminathan; Alvaro Nunez; Kristi Hultman; Kamila U Szulc; Ed X Wu; Daniel Kim; Sujit Sheth; Truman R Brown; Gary M Brittenham Journal: Magn Reson Med Date: 2010-05 Impact factor: 4.668
Authors: B Henninger; C Kremser; S Rauch; R Eder; H Zoller; A Finkenstedt; H J Michaely; M Schocke Journal: Eur Radiol Date: 2012-05-30 Impact factor: 5.315
Authors: James T Lee; Joy Liau; Paul Murphy; Michael E Schroeder; Claude B Sirlin; Mark Bydder Journal: Magn Reson Imaging Date: 2012-01-27 Impact factor: 2.546