Combined quantification of fatty infiltration, T1-relaxation times and T2*-relaxation times in normal-appearing skeletal muscle of controls and dystrophic patients

  • Benjamin Leporq
  • Arnaud Le Troter
  • Yann Le Fur
  • Emmanuelle Salort-Campana
  • Maxime Guye
  • Olivier Beuf
  • Shahram Attarian
  • David Bendahan
Research Article

Abstract

Objectives

To evaluate the combination of a fat–water separation method with an automated segmentation algorithm to quantify the intermuscular fatty-infiltrated fraction, the relaxation times, and the microscopic fatty infiltration in the normal-appearing muscle.

Materials and methods

MR acquisitions were performed at 1.5T in seven patients with facio-scapulo-humeral dystrophy and eight controls. Disease severity was assessed using commonly used scales for the upper and lower limbs. The fat–water separation method provided proton density fat fraction (PDFF) and relaxation times maps (T2* and T1). The segmentation algorithm distinguished adipose tissue and normal-appearing muscle from the T2* map and combined active contours, a clustering analysis, and a morphological closing process to calculate the index of fatty infiltration (IFI) in the muscle compartment defined as the relative amount of pixels with the ratio between the number of pixels within IMAT and the total number of pixels (IMAT + normal appearing muscle).

Results

In patients, relaxation times were longer and a larger fatty infiltration has been quantified in the normal-appearing muscle. T2* and PDFF distributions were broader. The relaxation times were correlated to the Vignos scale whereas the microscopic fatty infiltration was linked to the Medwin-Gardner-Walton scale. The IFI was linked to a composite clinical severity scale gathering the whole set of scales.

Conclusion

The MRI indices quantified within the normal-appearing muscle could be considered as potential biomarkers of dystrophies and quantitatively illustrate tissue alterations such as inflammation and fatty infiltration.

Keywords

Magnetic resonance imaging Segmentation Muscle dystrophies 

Notes

Acknowledgements

This work was performed within the framework of the LABEX PRIMES (ANR-11-LABX-0063) of Université de Lyon, within the program “Investissements d’Avenir” (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR).

Authors’ contribution

Leporq: Protocol/project development; Data analysis. Le Troter: Protocol/project development; Data analysis. Le Fur: Protocol/project development. Salort-Campana: Data collection or management. Guye: Data collection or management. Attarian: Data collection or management. Beuf: Protocol/project development. Bendahan: Data collection or management; Data analysis.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical statement

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© ESMRMB 2017

Authors and Affiliations

  • Benjamin Leporq
    • 1
  • Arnaud Le Troter
    • 2
  • Yann Le Fur
    • 2
  • Emmanuelle Salort-Campana
    • 3
  • Maxime Guye
    • 2
  • Olivier Beuf
    • 1
  • Shahram Attarian
    • 3
  • David Bendahan
    • 2
  1. 1.Laboratoire CREATIS CNRS UMR 5220; Inserm U1206; INSA-Lyon; UCBL Lyon 1Villeurbanne CedexFrance
  2. 2.Aix-Marseille University, CRMBM, CNRS UMRMarseilleFrance
  3. 3.Reference Center for Neuromuscular DisordersTimone HospitalMarseilleFrance

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