Abstract
Since the realization that diffusion MRI can probe the microstructural organization and orientation of biological tissue in vivo and non‐invasively, a multitude of diffusion imaging methods have been developed and applied to study the living human brain. Diffusion tensor imaging was the first model to be widely adopted in clinical and neuroscience research, but it was also clear from the beginning that it suffered from limitations when mapping complex configurations, such as crossing fibres. In this review, we highlight the main steps that have led the field of diffusion imaging to move from the tensor model to the adoption of diffusion and fibre orientation density functions as a more effective way to describe the complexity of white matter organization within each brain voxel. Among several techniques, spherical deconvolution has emerged today as one of the main approaches to model multiple fibre orientations and for tractography applications. Here we illustrate the main concepts and the reasoning behind this technique, as well as the latest developments in the field. The final part of this review provides practical guidelines and recommendations on how to set up processing and acquisition protocols suitable for spherical deconvolution.
Highlights
Even before diffusion MRI was proposed as a method for tractography,[1,2,3] it was recognized that the diffusion tensor model was strongly affected by the presence of crossing fibres
Three clear examples of these limitations are the inability: (i) to resolve and visualize crossing configuration between white matter tracts using Diffusion tensor imaging (DTI) (Figure 1); (ii) to correctly delineate and track white matter pathways that traverse regions of crossing fibres (Figure 2); and (iii) to differentiate between fibre coherence and intrinsic white matter properties using tensor‐derived metrics (Figure 3)
The realization that the microstructural organization and orientation of white matter could be estimated non‐invasively in vivo in the human brain using diffusion MRI, and that these orientations could be used for fibre tracking, has stimulated a tremendous amount of research in the fields of neuroscience, neuroanatomy and more recently connectomics
Summary
Since the realization that diffusion MRI can probe the microstructural organization and orientation of biological tissue in vivo and non‐invasively, a multitude of diffusion imaging methods have been developed and applied to study the living human brain. We highlight the main steps that have led the field of diffusion imaging to move from the tensor model to the adoption of diffusion and fibre orientation density functions as a more effective way to describe the complexity of white matter organization within each brain voxel. Spherical deconvolution has emerged today as one of the main approaches to model multiple fibre orientations and for tractography applications. KEYWORDS diffusion imaging, diffusion tensor imaging, fiber orientation density function, fiber response, ODF, MRI, spherical deconvolution, tractography
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