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Diffusion Tensor Imaging of Dystrophic Skeletal Muscle

Comparison of Two Segmentation Methods Adapted to Chemical-shift-encoded Water-fat MRI

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Abstract

Purpose

To compare the influence of two different regions of interest (ROIs) on diffusion tensor metrics in dystrophic thigh muscles using a custom-made (whole muscle) ROI including and a selective ROI excluding areas of fatty replacement.

Methods

Diffusion tensor imaging (DTI) and chemical-shift-encoded water-fat magnetic resonance imaging (MRI) of the thigh was conducted on a 3-Tesla system in 15 cases with muscular dystrophy and controls. The ROIs were chosen according to patterns of fatty replacement on co-registered axial DTI and gradient echo sequence (GRE) images. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), fiber track length (FTL), and muscle fat fractions (MFF) were compared between both ROI segmentations. These comparisons, muscle-specific correlation coefficients, and the influence of ROI localization on tensor metrics were derived based on linear mixed effects regression models.

Results

In the cases a high correlation was observed for ADC and FA with MFF using a custom ROI. The correlation was weaker but still significant with a selective ROI method. Using the custom ROI, FTL correlated significantly with MFF in 3 out of 4 muscles (r ≤ −0.51). A correlation was not found for the selective ROI method. Interaction analysis revealed that the association of ADC and FA with MFF was not significantly influenced by the ROI localization. For FTL the ROI localization significantly reduced the negative association with MFF.

Conclusion

The DTI metrics and FTL of custom ROI segmentation are significantly influenced by MFF. Contrary to ADC and FA, the effect of MFF on FTL is significantly reduced when applying selective ROI segmentation, which could therefore be a better option for MR tractography.

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Abbreviations

ADC:

Apparent diffusion coefficient

BF:

Biceps femoris muscle

DTI:

Diffusion tensor imaging

EPI:

Echo planar imaging

FA:

Fractional anisotropy

FTL:

Fiber track length

G:

Gracilis muscle

GRE:

Gradient echo sequence

MFF:

Muscle fat fraction

NSA:

Number of signal averages

RF:

Rectus femoris muscle

ROI:

Region of interest

SNR:

Signal-to-noise ratio

ST:

Semitendinosus muscle

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Acknowledgements

We kindly thank Dr. Jan Sedlacik (Department of Neuroradiology, University Medical Center Hamburg-Eppendorf) for the critical review of this work.

Author information

Authors and Affiliations

  1. Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany

    S. Keller, G. Adam & J. Yamamura

  2. Childrens’ Medical Center Dallas, Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Z. J. Wang

  3. Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany

    A. Aigner

  4. Department Stroke and Neurovascular Imaging, The Permanente Medical Group, San Francisco, CA, USA

    A. C. Kim

  5. Department of Neurology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany

    A. Golsari

  6. Philips Healthcare, Hamburg, Germany

    H. Kooijman

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  1. S. Keller
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Correspondence to S. Keller.

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Conflict of interest

S. Keller, Z.J. Wang, A. Aigner, A.C. Kim, A. Golsari, G. Adam and J. Yamamura declare that they have no competing interests. H. Kooijman is an employee of Philips Healthcare.

Caption Electronic Supplementary Material

Supplement Table 1.

Pearson correlation coefficientsa of ADC, FA, FTL, MFF, and demographics in cases and controls (aBased on mixed effects models with random intercepts for person)

Supplement Table 2:

Standard deviation of three technical replicate regions-of-interest used for the custom and selective ROI method in cases

Supplement Table 3.

Correlation analysis of custom and selective ROI DTI metrics and FTL

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Keller, S., Wang, Z.J., Aigner, A. et al. Diffusion Tensor Imaging of Dystrophic Skeletal Muscle. Clin Neuroradiol 29, 231–242 (2019). https://doi.org/10.1007/s00062-018-0667-3

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  • DOI: https://doi.org/10.1007/s00062-018-0667-3

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