scholarly journals Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain

2019 ◽  
Author(s):  
Maxime Chamberland ◽  
Erika P. Raven ◽  
Sila Genc ◽  
Kate Duffy ◽  
Maxime Descoteaux ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Angular Resolution ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
High Angular Resolution ◽  
Typically Developing ◽  
Typically Developing Children ◽  
Tissue Microstructure ◽  
Age Related ◽  
Diffusion Tensor Imaging Dti

AbstractVarious diffusion MRI measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different diffusion measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. In this work, we first demonstrate redundancies in the amount of information captured by 10 diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) measures. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in commonly-used DTI and HARDI measures profiled along 22 brain pathways extracted from typically developing children aged 8 - 18 years (n = 36). The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. Our results also suggest that HARDI measures are more sensitive at detecting age-related changes in tissue microstructure than DTI measures.

scholarly journals Disruption of neurite morphology parallels MS progression

2018 ◽  
Vol 5 (6) ◽  
pp. e502 ◽  
Author(s):  
Barbara Spanò ◽  
Giovanni Giulietti ◽  
Valerio Pisani ◽  
Manuela Morreale ◽  
Elisa Tuzzi ◽  
...  
Keyword(s):  
Brain Tissue ◽  
Disease Severity ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Compartment Model ◽  
Dispersion Index ◽  
Brain Areas ◽  
Neurite Density ◽  
Relapsing Remitting ◽  
Diffusion Tensor Imaging Dti

ObjectivesTo apply advanced diffusion MRI methods to the study of normal-appearing brain tissue in MS and examine their correlation with measures of clinical disability.MethodsA multi-compartment model of diffusion MRI called neurite orientation dispersion and density imaging (NODDI) was used to study 20 patients with relapsing-remitting MS (RRMS), 15 with secondary progressive MS (SPMS), and 20 healthy controls. Maps of NODDI were analyzed voxel-wise to assess the presence of abnormalities within the normal-appearing brain tissue and the association with disease severity. Standard diffusion tensor imaging (DTI) parameters were also computed for comparing the 2 techniques.ResultsPatients with MS showed reduced neurite density index (NDI) and increased orientation dispersion index (ODI) compared with controls in several brain areas (p < 0.05), with patients with SPMS having more widespread abnormalities. DTI indices were also sensitive to some changes. In addition, patients with SPMS showed reduced ODI in the thalamus and caudate nucleus. These abnormalities were associated with scores of disease severity (p < 0.05). The association with the MS functional composite score was higher in patients with SPMS compared with patients with RRMS.ConclusionsNODDI and DTI findings are largely overlapping. Nevertheless, NODDI helps interpret previous findings of increased anisotropy in the thalamus of patients with MS and are consistent with the degeneration of selective axon populations.

Optimal Diffusion Encoding Strategies for Fiber Mapping in Diffusion MRI

2009 ◽  
pp. 90-107 ◽  
Author(s):  
Dimitrios C. Karampinos ◽  
Robert Dawe ◽  
Konstantinos Arfanakis ◽  
John G. Georgiadis
Keyword(s):  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Cerebral White Matter ◽  
Tissue Microstructure ◽  
High Order Schemes ◽  
Selection Strategies ◽  
Diffusion Characteristics ◽  
Encoding Strategies ◽  
White Matter Connectivity ◽  
Selection Of

Diffusion Magnetic Resonance Imaging (diffusion MRI) can provide important information about tissue microstructure by probing the diffusion of water molecules in a biological tissue. Although originally proposed for the characterization of cerebral white matter connectivity and pathologies, its implementation has extended to many other areas of the human body. In a parallel development, a number of diffusion models have been proposed in order to extract the underlying tissue microstructural properties from the diffusion MRI signal. The present study reviews the basic considerations that have to be taken into account in the selection of the diffusion encoding parameters in diffusion MRI acquisition. Both diffusion tensor imaging (DTI) and high-order schemes are reviewed. The selection of these parameters relies strongly on requirements of the adopted diffusion model and the diffusion characteristics of the tissue under study. The authors review several successful parameter selection strategies for the imaging of the human brain, and conclude with the basics of parameter optimization on promising applications of the technique on other tissues, such as the spinal cord, the myocardium, and the skeletal muscles.

Inference of multiple fiber orientations in high angular resolution diffusion imaging

2005 ◽  
Vol 54 (6) ◽  
pp. 1480-1489 ◽  
Author(s):  
Tim Hosey ◽  
Guy Williams ◽  
Richard Ansorge
Keyword(s):  
Angular Resolution ◽  
Diffusion Imaging ◽  
High Angular Resolution
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