NODDI in clinical research

https://doi.org/10.1016/j.jneumeth.2020.108908Get rights and content
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Highlights

  • We summarized rationale to apply NODDI for clinical research.

  • We surveyed applications of NODDI in the studies of diseases and aging/development.

  • Most studies reported promising results for improving patient stratification.

  • Validating model assumptions are the Achilles’s heel of model-based approaches.

  • Substantial work remains before microstructure imaging to become a clinical tool.

Abstract

Diffusion MRI (dMRI) has proven to be a useful imaging approach for both clinical diagnosis and research investigating the microstructures of nervous tissues, and it has helped us to better understand the neurophysiological mechanisms of many diseases. Though diffusion tensor imaging (DTI) has long been the default tool to analyze dMRI data in clinical research, acquisition with stronger diffusion weightings beyond the DTI regimen is now possible with modern clinical scanners, potentially enabling even more detailed characterization of tissue microstructures. To take advantage of such data, neurite orientation dispersion and density imaging (NODDI) has been proposed as a way to relate the dMRI signal to tissue features via biophysically inspired modeling. The number of reports demonstrating the potential clinical utility of NODDI is rapidly increasing. At the same time, the pitfalls and limitations of NODDI, and general challenges in microstructure modeling, are becoming increasingly recognized by clinicians. dMRI microstructure modeling is a rapidly evolving field with great promise, where people from different scientific backgrounds, such as physics, medicine, biology, neuroscience, and statistics, are collaborating to build novel tools that contribute to improving human healthcare. Here, we review the applications of NODDI in clinical research and discuss future perspectives for investigations toward the implementation of dMRI microstructure imaging in clinical practice.

Abbreviations

ALS
amyotrophic lateral sclerosis
CoV
coefficient of variation
CST
corticospinal tract
DKI
diffusion kurtosis imaging
dMRI
diffusion MRI
DTI
diffusion tensor imaging
FA
fractional anisotropy
FCD
focal cortical dysplasia
ffw
free water fraction
fi
intra-neurite fraction
GM
gray matter
iNPH
idiopathic normal pressure hydrocephalus
MD
mean diffusivity
MS
multiple sclerosis
NDI
neurite density index
NODDI
neurite orientation dispersion and density imaging
ODI
orientation dispersion index
TBI
traumatic brain injury
TLE
temporal lobe epilepsy
UBOs
unidentified bright objects
WM
white matter

Keywords

Diffusion MRI
Modeling
Microstructure
Neurite orientation dispersion and density imaging (NODDI)
Biomarker

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