Literature DB >> 18667287

Improved T2* assessment in liver iron overload by magnetic resonance imaging.

Vincenzo Positano1, Benedetta Salani, Alessia Pepe, Maria Filomena Santarelli, Daniele De Marchi, Anna Ramazzotti, Brunella Favilli, Eliana Cracolici, Massimo Midiri, Paolo Cianciulli, Massimo Lombardi, Luigi Landini.   

Abstract

In the clinical MRI practice, it is common to assess liver iron overload by T2* multi-echo gradient-echo images. However, there is no full consensus about the best image analysis approach for the T2* measurements. The currently used methods involve manual drawing of a region of interest (ROI) within MR images of the liver. Evaluation of a representative liver T2* value is done by fitting an appropriate model to the signal decay within the ROIs vs. the echo time. The resulting T2* value may depend on both ROI placement and choice of the signal decay model. The aim of this study was to understand how the choice of the analysis methodology may affect the accuracy of T2* measurements. A software model of the iron overloaded liver was inferred from MR images acquired from 40 thalassemia major patients. Different image analysis methods were compared exploiting the developed software model. Moreover, a method for global semiautomatic T2* measurement involving the whole liver was developed. The global method included automatic segmentation of parenchyma by an adaptive fuzzy-clustering algorithm able to compensate for signal inhomogeneities. Global liver T2* value was evaluated using a pixel-wise technique and an optimized signal decay model. The global approach was compared with the ROI-based approach used in the clinical practice. For the ROI-based approach, the intra-observer and inter-observer coefficients of variation (CoVs) were 3.7% and 5.6%, respectively. For the global analysis, the CoVs for intra-observers and inter-observers reproducibility were 0.85% and 2.87%, respectively. The variability shown by the ROI-based approach was acceptable for use in the clinical practice; however, the developed global method increased the accuracy in T2* assessment and significantly reduced the operator dependence and sampling errors. This global approach could be useful in the clinical arena for patients with borderline liver iron overload and/or requiring follow-up studies.

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Year:  2008        PMID: 18667287     DOI: 10.1016/j.mri.2008.06.004

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  36 in total

Review 1.  Magnetic resonance imaging quantification of liver iron.

Authors:  Claude B Sirlin; Scott B Reeder
Journal:  Magn Reson Imaging Clin N Am       Date:  2010-08       Impact factor: 2.266

2.  Comparison of whole liver and small region-of-interest measurements of MRI liver R2* in children with iron overload.

Authors:  M Beth McCarville; Claudia M Hillenbrand; Ralf B Loeffler; Matthew P Smeltzer; Ruitan Song; Chin-Shang Li; Jane S Hankins
Journal:  Pediatr Radiol       Date:  2010-03-24

3.  Autoregressive moving average modeling for spectral parameter estimation from a multigradient echo chemical shift acquisition.

Authors:  Brian A Taylor; Ken-Pin Hwang; John D Hazle; R Jason Stafford
Journal:  Med Phys       Date:  2009-03       Impact factor: 4.071

4.  Automated vessel exclusion technique for quantitative assessment of hepatic iron overload by R2*-MRI.

Authors:  Aaryani Tipirneni-Sajja; Ruitian Song; M Beth McCarville; Ralf B Loeffler; Jane S Hankins; Claudia M Hillenbrand
Journal:  J Magn Reson Imaging       Date:  2017-10-30       Impact factor: 4.813

5.  Automated two-point dixon screening for the evaluation of hepatic steatosis and siderosis: comparison with R2-relaxometry and chemical shift-based sequences.

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

6.  Technical Failure of MR Elastography Examinations of the Liver: Experience from a Large Single-Center Study.

Authors:  Mathilde Wagner; Idoia Corcuera-Solano; Grace Lo; Steven Esses; Joseph Liao; Cecilia Besa; Nelson Chen; Ginu Abraham; Maggie Fung; James S Babb; Richard L Ehman; Bachir Taouli
Journal:  Radiology       Date:  2017-01-03       Impact factor: 11.105

7.  Lithium suppression of tau induces brain iron accumulation and neurodegeneration.

Authors:  P Lei; S Ayton; A T Appukuttan; S Moon; J A Duce; I Volitakis; R Cherny; S J Wood; M Greenough; G Berger; C Pantelis; P McGorry; A Yung; D I Finkelstein; A I Bush
Journal:  Mol Psychiatry       Date:  2016-07-12       Impact factor: 15.992

8.  The use of appropriate calibration curves corrects for systematic differences in liver R2* values measured using different software packages.

Authors:  Antonella Meloni; Hugh Y Rienhoff; Amber Jones; Alessia Pepe; Massimo Lombardi; John C Wood
Journal:  Br J Haematol       Date:  2013-03-18       Impact factor: 6.998

9.  Fast approximation to pixelwise relaxivity maps: validation in iron overloaded subjects.

Authors:  Antonella Meloni; Heather Zmyewski; Hugh Young Rienhoff; Amber Jones; Alessia Pepe; Massimo Lombardi; John C Wood
Journal:  Magn Reson Imaging       Date:  2013-06-15       Impact factor: 2.546

10.  The role of MR imaging in detection of hepatic iron overload in patients with cirrhosis of different origins.

Authors:  Edyta Szurowska; Katarzyna Sikorska; E Izycka-Swieszewska; Tomasz Nowicki; Tomasz Romanowski; Krzysztof P Bielawski; Michał Studniarek
Journal:  BMC Gastroenterol       Date:  2010-01-27       Impact factor: 3.067

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