DKI is a diffusion technique based on the use of very high values ??(b=2000 s/mm2) and on the complex tissue structural technique with interesting applications in neuroradiology, mainly in the diagnosis and follow-up of gliomas.

Kurtosis is a statistical measure that determines the degree of concentration that the values ??of a variable present around the central zone of the frequency distribution. Diffusion imaging (DWI) with low b values ??assumes that the movement of water molecules after the application of the gradients of the diffusion sequence is the same in any direction in space and follows a Gaussian distribution. In biological tissues the movement of water molecules varies from the Gaussian distribution. This degree of deviation is related to tissue structural complexity and barriers to the free diffusion of water and it can be calculated using DKI. This presentation will explain in a simple way what are the technical requirements necessary to obtain the DKI as well as the parameters that can be calculated, such as the kurtosis coefficient (K). It is intended to provide information that may be useful in routine clinical practice, illustrating representative cases. Examples of the different applications of DKI in the diagnosis and monitoring of different pathologies will be given. In brain tumors, it can be useful to differentiate high-grade and low-grade gliomas, as well as to distinguish between recurrence of high-grade gliomas and pseudoprogression or radionecrosis and gliomas from other tumors such as primary CNS lymphomas. We will also show the usefullness of DKI in the diagnosis of head and neck tumors as well as in neurodegenerative diseases.