Evaluation of skeletal muscle DTI in patients with duchenne muscular dystrophy

Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal‐to‐noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential...

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Published inNMR in biomedicine Vol. 28; no. 11; pp. 1589 - 1597
Main Authors Hooijmans, M. T., Damon, B. M., Froeling, M., Versluis, M. J., Burakiewicz, J., Verschuuren, J. J. G. M., Niks, E. H., Webb, A. G., Kan, H. E.
Format Journal Article
LanguageEnglish
Published England Blackwell Publishing Ltd 01.11.2015
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Abstract Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal‐to‐noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in‐vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and λ3 (p<0.05) in the TA muscle of DMD patients. In‐vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and λ3 in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between‐group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences. Copyright © 2015 John Wiley & Sons, Ltd. A multi‐parametric MR protocol was used to evaluate the confounding effects of signal‐to‐noise ratio (SNR), fat percentage and changes in mean water T2 on the DTI parameter estimation in patients with Duchenne muscular dystrophy (DMD) and healthy controls. No significant changes in fractional anisotropy (FA) were observed between groups when using only regions of interest (ROIs) with SNR > 20, while an increased FA was detected in the lateral head of the gastrocnemius, the soleus and the peroneus muscles using all ROIs. These findings suggest that external factors have an important effect on the DTI estimation in DMD patients, and that a multi‐parametric MR measurement protocol is essential to distinguish between confounders and pathology.
AbstractList Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal-to-noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in-vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and λ3 (p<0.05) in the TA muscle of DMD patients. In-vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and λ3 in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between-group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences.
Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal‐to‐noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in‐vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and λ3 (p<0.05) in the TA muscle of DMD patients. In‐vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and λ3 in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between‐group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences. Copyright © 2015 John Wiley & Sons, Ltd. A multi‐parametric MR protocol was used to evaluate the confounding effects of signal‐to‐noise ratio (SNR), fat percentage and changes in mean water T2 on the DTI parameter estimation in patients with Duchenne muscular dystrophy (DMD) and healthy controls. No significant changes in fractional anisotropy (FA) were observed between groups when using only regions of interest (ROIs) with SNR > 20, while an increased FA was detected in the lateral head of the gastrocnemius, the soleus and the peroneus muscles using all ROIs. These findings suggest that external factors have an important effect on the DTI estimation in DMD patients, and that a multi‐parametric MR measurement protocol is essential to distinguish between confounders and pathology.
Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal‐to‐noise ratio (SNR), %fat, and tissue T 2 . The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in‐vivo measures of mean water T 2 , %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles ( p <0.05) and an increased mean diffusivity ( p <0.05) and λ 3 ( p <0.05) in the TA muscle of DMD patients. In‐vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient ( p <0.009) and λ 3 in the TA and GCL muscles ( p <0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ 3 , these between‐group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T 2 , %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences. Copyright © 2015 John Wiley & Sons, Ltd.
Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal-to-noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in-vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p&lt;0.05) and an increased mean diffusivity (p&lt;0.05) and λ3 (p&lt;0.05) in the TA muscle of DMD patients. In-vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p&lt;0.009) and λ3 in the TA and GCL muscles (p&lt;0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between-group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences.
Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal-to-noise ratio (SNR), %fat, and tissue T2. The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in-vivo measures of mean water T2, %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and λ3 (p<0.05) in the TA muscle of DMD patients. In-vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and λ3 in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and λ3, these between-group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T2, %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences. Copyright © 2015 John Wiley & Sons, Ltd.
Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown that muscle DTI measurements depend on signal-to-noise ratio (SNR), %fat, and tissue T sub(2). The goal of this study was to evaluate the potential biasing effects of these factors on skeletal muscle DTI data in patients with Duchenne Muscular Dystrophy (DMD). MR images were obtained of the right lower leg of 21 DMD patients and 12 healthy controls on a Philips 3T system. DTI measurements were combined with quantitative in-vivo measures of mean water T sub(2), %fat and SNR to evaluate their effect on DTI parameter estimation. All outcome measures were determined within ROIs drawn for six lower leg muscles. Between group analysis, using all ROIs, revealed a significantly elevated FA in the GCL, SOL and PER muscles (p<0.05) and an increased mean diffusivity (p<0.05) and lambda sub(3) (p<0.05) in the TA muscle of DMD patients. In-vivo evaluation of the individual confounders showed behaviour in line with predictions from previous simulation work. To account for these confounders, subsequent analysis used only ROIs with SNR greater than 20. With this criterion we found significantly greater MD in the TA muscle of DMD patient (p<0.009) and lambda sub(3) in the TA and GCL muscles (p<0.001) of DMD patients, but no differences in FA. As both increased %fat and lower SNR are expected to reduce the apparent MD and lambda sub(3), these between-group differences are likely due to pathophysiology. However, the increased FA, observed when using all ROIs, likely reflects the effect of low SNR and %fat on the DTI parameter estimation. These findings suggest that measuring mean water T sub(2), %fat and SNR is essential to ascribe changes in DTI measures to intrinsic diffusion changes or to confounding influences. A multi-parametric MR protocol was used to evaluate the confounding effects of signal-to-noise ratio (SNR), fat percentage and changes in mean water T sub(2) on the DTI parameter estimation in patients with Duchenne muscular dystrophy (DMD) and healthy controls. No significant changes in fractional anisotropy (FA) were observed between groups when using only regions of interest (ROIs) with SNR > 20, while an increased FA was detected in the lateral head of the gastrocnemius, the soleus and the peroneus muscles using all ROIs. These findings suggest that external factors have an important effect on the DTI estimation in DMD patients, and that a multi-parametric MR measurement protocol is essential to distinguish between confounders and pathology.
Author Hooijmans, M. T.
Burakiewicz, J.
Webb, A. G.
Niks, E. H.
Froeling, M.
Kan, H. E.
Damon, B. M.
Versluis, M. J.
Verschuuren, J. J. G. M.
AuthorAffiliation 2 Depts. of Radiology and Radiological Sciences, Biomedical Engineering, and Molecular Physiology and Biophysics, Vanderbilt University, Nashville TN USA
4 Philips Healthcare, Benelux, Netherlands
5 Dept of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
3 Dept of Radiology, Utrecht Medical Center, Utrecht, The Netherlands
1 Dept of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
AuthorAffiliation_xml – name: 1 Dept of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
– name: 2 Depts. of Radiology and Radiological Sciences, Biomedical Engineering, and Molecular Physiology and Biophysics, Vanderbilt University, Nashville TN USA
– name: 5 Dept of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
– name: 4 Philips Healthcare, Benelux, Netherlands
– name: 3 Dept of Radiology, Utrecht Medical Center, Utrecht, The Netherlands
Author_xml – sequence: 1
  givenname: M. T.
  surname: Hooijmans
  fullname: Hooijmans, M. T.
  email: Correspondence to: M. T. Hooijmans, Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands., m.t.hooijmans@lumc.nl
  organization: Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
– sequence: 2
  givenname: B. M.
  surname: Damon
  fullname: Damon, B. M.
  organization: Departments of Radiology and Radiological Sciences, Biomedical Engineering, and Molecular Physiology and Biophysics, Vanderbilt University, TN, Nashville, USA
– sequence: 3
  givenname: M.
  surname: Froeling
  fullname: Froeling, M.
  organization: Department of Radiology, Utrecht Medical Center, Utrecht, The Netherlands
– sequence: 4
  givenname: M. J.
  surname: Versluis
  fullname: Versluis, M. J.
  organization: Philips Healthcare, Benelux, The Netherlands
– sequence: 5
  givenname: J.
  surname: Burakiewicz
  fullname: Burakiewicz, J.
  organization: Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
– sequence: 6
  givenname: J. J. G. M.
  surname: Verschuuren
  fullname: Verschuuren, J. J. G. M.
  organization: Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
– sequence: 7
  givenname: E. H.
  surname: Niks
  fullname: Niks, E. H.
  organization: Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
– sequence: 8
  givenname: A. G.
  surname: Webb
  fullname: Webb, A. G.
  organization: Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
– sequence: 9
  givenname: H. E.
  surname: Kan
  fullname: Kan, H. E.
  organization: Department of Radiology, C. J. Gorter Center for High Field MRI, Leiden University Medical Centre, Leiden, The Netherlands
BackLink https://www.ncbi.nlm.nih.gov/pubmed/26449628$$D View this record in MEDLINE/PubMed
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Issue 11
Keywords mean water T2
diffusion tensor imaging
fat fraction
Duchenne muscular dystrophy
signal-to-noise ratio
Language English
License Copyright © 2015 John Wiley & Sons, Ltd.
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Snippet Diffusion tensor imaging (DTI) is a popular method to assess differences in fiber organization in diseased and healthy muscle tissue. Previous work has shown...
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SubjectTerms Adolescent
Child
Child, Preschool
diffusion tensor imaging
Diffusion Tensor Imaging - methods
Duchenne muscular dystrophy
fat fraction
Female
Humans
Leg - pathology
Male
mean water T2
Muscle, Skeletal - pathology
Muscular dystrophy
Muscular Dystrophy, Duchenne - pathology
Musculoskeletal system
Parameter estimation
Reproducibility of Results
Sensitivity and Specificity
Signal-To-Noise Ratio
Title Evaluation of skeletal muscle DTI in patients with duchenne muscular dystrophy
URI https://api.istex.fr/ark:/67375/WNG-G7G9NBRR-W/fulltext.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fnbm.3427
https://www.ncbi.nlm.nih.gov/pubmed/26449628
https://www.proquest.com/docview/1725045938/abstract/
https://search.proquest.com/docview/1727435930
https://search.proquest.com/docview/1732816777
https://pubmed.ncbi.nlm.nih.gov/PMC4670831
Volume 28
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