Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI

Inge Timmers, Alard Roebroeck, Matteo Bastiani, Bernadette Jansma, Estela Rubio-Gozalbo, Hui Zhang

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

Neurite orientation dispersion and density imaging (NODDI) enables more specific characterization of tissue microstructure by estimating neurite density (NDI) and orientation dispersion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. We assessed the added value of NODDI parameters over FA, by contrasting group differences identified by both models. Diffusion-weighted images with multiple shells were acquired in a group of 8 healthy controls and 8 patients with an inherited metabolic disease. Both standard DTI and NODDI analyses were performed. Tract based spatial statistics (TBSS) was used for group inferences, after which overlap and unique contributions across different parameters were evaluated. Results showed that group differences in NDI and ODI were complementary, and together could explain much of the FA results. Further, compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Finally, ODI from single-shell NODDI analysis, but not NDI, was found to reproduce the group differences from the multi-shell analysis. To conclude, by using a clinically feasible acquisition and analysis protocol, we demonstrated that NODDI is of added value to standard DTI, by revealing specific microstructural substrates to white matter changes detected with FA. As the (simpler) DTI model was more sensitive in identifying group differences, NODDI is recommended to be used complementary to DTI, thereby adding greater specificity regarding microstructural underpinnings of the differences. The finding that ODI abnormalities can be identified reliably using single-shell data may allow the retrospective analysis of standard DTI with NODDI.

Original languageEnglish
Article numbere0167884
Number of pages15
JournalPLOS ONE
Volume11
Issue number12
DOIs
Publication statusPublished - 21 Dec 2016

Keywords

  • NEURITE ORIENTATION DISPERSION
  • MULTISHELL DIFFUSION MRI
  • HUMAN BRAIN
  • CLASSIC GALACTOSEMIA
  • MULTIPLE-SCLEROSIS
  • ALZHEIMERS-DISEASE
  • DENSITY
  • CHILDREN
  • REGISTRATION
  • DISORDERS

Cite this

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title = "Assessing Microstructural Substrates of White Matter Abnormalities: A Comparative Study Using DTI and NODDI",
abstract = "Neurite orientation dispersion and density imaging (NODDI) enables more specific characterization of tissue microstructure by estimating neurite density (NDI) and orientation dispersion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. We assessed the added value of NODDI parameters over FA, by contrasting group differences identified by both models. Diffusion-weighted images with multiple shells were acquired in a group of 8 healthy controls and 8 patients with an inherited metabolic disease. Both standard DTI and NODDI analyses were performed. Tract based spatial statistics (TBSS) was used for group inferences, after which overlap and unique contributions across different parameters were evaluated. Results showed that group differences in NDI and ODI were complementary, and together could explain much of the FA results. Further, compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Finally, ODI from single-shell NODDI analysis, but not NDI, was found to reproduce the group differences from the multi-shell analysis. To conclude, by using a clinically feasible acquisition and analysis protocol, we demonstrated that NODDI is of added value to standard DTI, by revealing specific microstructural substrates to white matter changes detected with FA. As the (simpler) DTI model was more sensitive in identifying group differences, NODDI is recommended to be used complementary to DTI, thereby adding greater specificity regarding microstructural underpinnings of the differences. The finding that ODI abnormalities can be identified reliably using single-shell data may allow the retrospective analysis of standard DTI with NODDI.",
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Assessing Microstructural Substrates of White Matter Abnormalities : A Comparative Study Using DTI and NODDI. / Timmers, Inge; Roebroeck, Alard; Bastiani, Matteo; Jansma, Bernadette; Rubio-Gozalbo, Estela; Zhang, Hui.

In: PLOS ONE, Vol. 11, No. 12, e0167884, 21.12.2016.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Assessing Microstructural Substrates of White Matter Abnormalities

T2 - A Comparative Study Using DTI and NODDI

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AU - Zhang, Hui

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AB - Neurite orientation dispersion and density imaging (NODDI) enables more specific characterization of tissue microstructure by estimating neurite density (NDI) and orientation dispersion (ODI), two key contributors to fractional anisotropy (FA). The present work compared NODDI- with diffusion tensor imaging (DTI)-derived indices for investigating white matter abnormalities in a clinical sample. We assessed the added value of NODDI parameters over FA, by contrasting group differences identified by both models. Diffusion-weighted images with multiple shells were acquired in a group of 8 healthy controls and 8 patients with an inherited metabolic disease. Both standard DTI and NODDI analyses were performed. Tract based spatial statistics (TBSS) was used for group inferences, after which overlap and unique contributions across different parameters were evaluated. Results showed that group differences in NDI and ODI were complementary, and together could explain much of the FA results. Further, compared to FA analysis, NDI and ODI gave a pattern of results that was more regionally specific and were able to capture additional discriminative voxels that FA failed to identify. Finally, ODI from single-shell NODDI analysis, but not NDI, was found to reproduce the group differences from the multi-shell analysis. To conclude, by using a clinically feasible acquisition and analysis protocol, we demonstrated that NODDI is of added value to standard DTI, by revealing specific microstructural substrates to white matter changes detected with FA. As the (simpler) DTI model was more sensitive in identifying group differences, NODDI is recommended to be used complementary to DTI, thereby adding greater specificity regarding microstructural underpinnings of the differences. The finding that ODI abnormalities can be identified reliably using single-shell data may allow the retrospective analysis of standard DTI with NODDI.

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KW - MULTISHELL DIFFUSION MRI

KW - HUMAN BRAIN

KW - CLASSIC GALACTOSEMIA

KW - MULTIPLE-SCLEROSIS

KW - ALZHEIMERS-DISEASE

KW - DENSITY

KW - CHILDREN

KW - REGISTRATION

KW - DISORDERS

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