scholarly journals In vivo restricted diffusion imaging (RDI) is sensitive to differences in axonal density in typical children and adults

2021 ◽  
Vol 226 (8) ◽  
pp. 2689-2705
Author(s):  
Dea Garic ◽  
Fang-Cheng Yeh ◽  
Paulo Graziano ◽  
Anthony Steven Dick
2020 ◽  
Author(s):  
Dea Garic ◽  
Fang-Cheng Yeh ◽  
Paulo Graziano ◽  
Anthony Steven Dick

ABSTRACTBackgroundThe ability to dissociate axonal density in vivo from other microstructural properties of white matter is important for the diagnosis and treatment of neurologic disease, and new methods to do so are being developed. We investigated one such method–restricted diffusion imaging (RDI)–to see whether it can more accurately replicate histological axonal density patterns in the corpus callosum (CC) of adults and children compared to diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and generalized q-sampling imaging (GQI) methods. To do so, we compared known axonal density patterns defined by histology to to diffusion-weighted imaging (DWI) scans of 840 healthy 20- to 40-year-old adults, and, in a replication and extension, to DWI scans of 129 typically developing 7-month-old to 18-year-old children and adolescents. Contrast analyses were used to to compare pattern similarities between the in-vivo metric and previously-published histological density models. We found that RDI was effective at mapping axonal density of small (Cohen’s d= 2.60) and large fiber sizes (Cohen’s d= 2.84) in adults. The same pattern was observed in the developing sample (Cohen’s d= 3.09 and 3.78, respectively). Other metrics, notably NODDI’s intracellular volume fraction (ICVF), were also sensitive to differences in axonal density across the longitudinal axis of the CC. In conclusion, the study showed that RDI is effective at measuring axonal density of small and large axons in adults and children, with both single- and multi-shell acquisition DWI data. Its effectiveness and availability to be used on standard as well as advanced DWI acquisitions makes it a promising method in clinical settings.


2012 ◽  
Vol 1 (1) ◽  
pp. 78-91 ◽  
Author(s):  
S Kollias

Diffusion tensor imaging (DTI) is a neuroimaging MR technique, which allows in vivo and non-destructive visualization of myeloarchitectonics in the neural tissue and provides quantitative estimates of WM integrity by measuring molecular diffusion. It is based on the phenomenon of diffusion anisotropy in the nerve tissue, in that water molecules diffuse faster along the neural fibre direction and slower in the fibre-transverse direction. On the basis of their topographic location, trajectory, and areas that interconnect the various fibre systems of the mammalian brain are divided into commissural, projectional and association fibre systems. DTI has opened an entirely new window on the white matter anatomy with both clinical and scientific applications. Its utility is found in both the localization and the quantitative assessment of specific neuronal pathways. The potential of this technique to address connectivity in the human brain is not without a few methodological limitations. A wide spectrum of diffusion imaging paradigms and computational tractography algorithms has been explored in recent years, which established DTI as promising new avenue, for the non-invasive in vivo mapping of structural connectivity at the macroscale level. Further improvements in the spatial resolution of DTI may allow this technique to be applied in the near future for mapping connectivity also at the mesoscale level. DOI: http://dx.doi.org/10.3126/njr.v1i1.6330 Nepalese Journal of Radiology Vol.1(1): 78-91


2012 ◽  
Vol 51 (05) ◽  
pp. 441-448 ◽  
Author(s):  
P. F. Neher ◽  
I. Reicht ◽  
T. van Bruggen ◽  
C. Goch ◽  
M. Reisert ◽  
...  

SummaryBackground: Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of tissue structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop the algorithmic tools necessary to cope with the complexity of the datasets.Objectives: This work illustrates our strategy that encompasses the development of a modularized and open software tool for data processing, visualization and interactive exploration in diffusion imaging research and aims at reinforcing sustainable evaluation and progress in the field.Methods: In this paper, the usability and capabilities of a new application and toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITKDI, are demonstrated using in-vivo datasets.Results: MITK-DI provides a comprehensive software framework for high-performance data processing, analysis and interactive data exploration, which is designed in a modular, extensible fashion (using CTK) and in adherence to widely accepted coding standards (e.g. ITK, VTK). MITK-DI is available both as an open source software development toolkit and as a ready-to-use in stallable application.Conclusions: The open source release of the modular MITK-DI tools will increase verifiability and comparability within the research community and will also be an important step towards bringing many of the current techniques towards clinical application.


NeuroImage ◽  
2013 ◽  
Vol 82 ◽  
pp. 416-425 ◽  
Author(s):  
Novena A. Rangwala ◽  
David B. Hackney ◽  
Weiying Dai ◽  
David C. Alsop

2003 ◽  
Vol 45 (3) ◽  
pp. 223-234 ◽  
Author(s):  
Roland Bammer ◽  
Burak Acar ◽  
Michael E. Moseley
Keyword(s):  

2007 ◽  
Vol 17 (12) ◽  
pp. 3079-3085 ◽  
Author(s):  
J. F. Budzik ◽  
V. Le Thuc ◽  
X. Demondion ◽  
M. Morel ◽  
D. Chechin ◽  
...  

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