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Non-invasive measurement of liver iron concentration using 3-Tesla magnetic resonance imaging: validation against biopsy

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

A Gastrointestinal to this article was published on 09 January 2018

Abstract

Objectives

To evaluate the performance and limitations of the R2* and signal intensity ratio (SIR) methods for quantifying liver iron concentration (LIC) at 3 T.

Methods

A total of 105 patients who underwent a liver biopsy with biochemical LIC (LICb) were included prospectively. All patients underwent a 3-T MRI scan with a breath-hold multiple-echo gradient-echo sequence (mGRE). LIC calculated by 3-T SIR algorithm (LICSIR) and by R2* (LICR2*) were correlated with LICb. Sensitivity and specificity were calculated. The comparison of methods was analysed for successive classes.

Results

LICb was strongly correlated with R2* (r = 0.95, p < 0.001) and LICSIR (r = 0.92, p < 0.001). In comparison to LICb, LICR2* and LICSIR detect liver iron overload with a sensitivity/specificity of 0.96/0.93 and 0.92/0.95, respectively, and a bias ± SD of 7.6 ± 73.4 and 14.8 ± 37.6 μmol/g, respectively. LICR2* presented the lowest differences for patients with LICb values under 130 μmol/g. Above this value, LICSIR has the lowest differences.

Conclusions

At 3 T, R2* provides precise LIC quantification for lower overload but the SIR method is recommended to overcome R2* limitations in higher overload. Our software, available at www.mrquantif.org, uses both methods jointly and selects the best one.

Key points

• Liver iron can be accurately quantified by MRI at 3 T

• At 3 T, R2* provides precise quantification of slight liver iron overload

• At 3 T, SIR method is recommended in case of high iron overload

• Slight liver iron overload present in metabolic syndrome can be depicted

• Treatment can be monitored with great confidence

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Abbreviations

AUC:

area under the curve

BMI:

body mass index

DIOS:

dysmetabolic iron overload syndrome

LIC:

liver iron concentration

LICb :

LIC assessed by biopsy using biochemical analysis

LICR2* :

LIC calculated by T2* conversion

LICSIR :

LIC calculated by SIR method

mGRE:

multiple-echo gradient-echo sequence

MRI:

magnetic resonance imaging

NASH:

non-alcoholic steatohepatitis

SIR:

signal intensity ratio

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Acknowledgements

We received support from the national clinical research program for public hospitals of France. Thanks to Tracey Westcott for the language help. Thanks to all the MRI team of University Hospital of Rennes.

Funding

This study has received funding by the French national research program “Programme Hospitalier de Recherche Clinique (PHRC)”.

Author information

Authors and Affiliations

  1. Department of Radiology, Rennes University Hospital, 2 rue H. Le Guilloux, 35033, Rennes, France

    Gaspard d’Assignies, Anita Paisant, Anne Boulic, Elise Bannier & Yves Gandon

  2. LTSI, INSERM U1099, University of Rennes 1, Beaulieu Campus, 35042, Rennes, France

    Gaspard d’Assignies, Hervé Saint-Jalmes & Yves Gandon

  3. Clinical investigation centre, Rennes University Hospital, CIC INSERM 1414, 2 rue H. Le Guilloux, 35033, Rennes, France

    Anita Paisant, Edouard Bardou-Jacquet, Fabrice Lainé & Jeff Morcet

  4. Department of Hepatology, Rennes University Hospital, 2 rue H. Le Guilloux, 35033, Rennes, France

    Edouard Bardou-Jacquet & Fabrice Lainé

  5. INSERM UMR991, Rennes University Hospital, 2 rue H. Le Guilloux, 35033, Rennes, France

    Edouard Bardou-Jacquet & Martine Ropert

  6. VisAGeS U746 Unit/Project, INSERM/INRIA, IRISA, UMR CNRS 6074, University of Rennes 1, Beaulieu Campus, 35042, Rennes, France

    Elise Bannier

  7. Department of Biochemistry, Rennes University Hospital, 2 rue H. Le Guilloux, 35033, Rennes, France

    Martine Ropert

  8. CRLCC, Centre Eugène Marquis, F-35000, Rennes, France

    Hervé Saint-Jalmes

Authors
  1. Gaspard d’Assignies
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  2. Anita Paisant
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  3. Edouard Bardou-Jacquet
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  4. Anne Boulic
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  5. Elise Bannier
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  6. Fabrice Lainé
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  7. Martine Ropert
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  8. Jeff Morcet
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  9. Hervé Saint-Jalmes
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  10. Yves Gandon
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Corresponding author

Correspondence to Yves Gandon.

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Guarantor

The scientific guarantor of this publication is Prof Yves Gandon

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (MJ) is a senior biostatistician and has significant statistical expertise.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

The study protocol (Clinical trial NCT00401336) was approved by the local institutional review board (ref. 05/17-544).

Study subjects or cohorts overlap

This series of patients have been previously used to define a liver-to-muscle signal intensity ratio (SIR) algorithm from five different monoecho sequences. Here we report the R2* results calculated from a multiecho sequence. We also calculated SIR results from this unique sequence using the previously reported algorithm based on monoecho sequences.

Methodology

• prospective

• diagnostic or prognostic study

• performed at one institution

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d’Assignies, G., Paisant, A., Bardou-Jacquet, E. et al. Non-invasive measurement of liver iron concentration using 3-Tesla magnetic resonance imaging: validation against biopsy. Eur Radiol 28, 2022–2030 (2018). https://doi.org/10.1007/s00330-017-5106-3

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  • DOI: https://doi.org/10.1007/s00330-017-5106-3

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