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RESEARCH PRODUCT
Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI)
A. Lo CastoFederico MidiriGiorgio ColluraMaria BraiG. La TonaNicola ToschiNicola ToschiCesare GagliardoMaurizio Marralesubject
Diffusion tensor imaging (DTI)computer.software_genreSensitivity and Specificity030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSettore MED/36 - Diagnostica per Immagini e RadioterapiaImage Interpretation Computer-AssistedHumansPreprocessorRadiology Nuclear Medicine and imagingMagnetic resonance imaging (MRI)Diffusion (business)DKIDiffusion Kurtosis ImagingParametric statisticsPhysicsBrain DiseasesDiffusion weighted imaging (DWI)Reproducibility of ResultsBrainSettore MED/37 - NeuroradiologiaImage EnhancementWhite MatterSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Acquisition ProtocolDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingNeuroradiologyDiffusion processDTIDWI NeuroradiologyDiffusional kurtosis imaging (DKI)Settore MED/26 - NeurologiaNeurology (clinical)Data miningBrain; Diffusion tensor imaging (DTI); Diffusion weighted imaging (DWI); Diffusional kurtosis imaging (DKI); Magnetic resonance imaging (MRI); NeuroradiologycomputerAlgorithms030217 neurology & neurosurgeryMRIDiffusion MRIdescription
In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher order diffusion model that is a straightforward extension of the DTI model. Here, we analyze the physics underlying this method, we report our MRI acquisition protocol with the preprocessing pipeline used and the DKI parametric maps obtained on a 1.5 T scanner, and we review the most relevant clinical applications of this technique in various neurological diseases.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2016-01-01 | Clinical Neuroradiology |