Diffusion-Weighted MR imaging: Clinical applications of kurtosis analysis to prostate cancer

TL;DR

This paper explores the use of kurtosis analysis in diffusion-weighted MRI to better characterize tissue microstructure, specifically applying it to prostate cancer imaging to provide additional diagnostic information beyond standard ADC measurements.

Contribution

It introduces the AKC parameter for non-Gaussian diffusion quantification and demonstrates its application in clinical prostate MRI to enhance tissue microstructure assessment.

Findings

Non-Gaussian diffusion maps complement ADC maps in prostate imaging

AKC parameter provides additional tissue organization information

Potential for improved prostate cancer diagnosis and characterization

Abstract

Magnetic resonance imaging technique known as DWI (diffusion-weighted imaging) allows measurement of water diffusivity on a pixel basis for evaluating pathology throughout the body and is now routinely incorporated into many body MRI protocols, mainly in oncology. Indeed water molecules motion reflects the interactions with other molecules, membranes, cells, and in general the interactions with the environment. Microstructural changes as e.g. cellular organization and/or integrity then affect the motion of water molecules, and consequently alter the water diffusion properties measured by DWI. Then DWI technique can be used to extract information about tissue organization at the cellular level indirectly from water motion. In general the signal intensity in DWI can be quantified by using a parameter known as ADC (Apparent Diffusion Coefficient) emphasizing that it is not the real diffusion coefficient, which is a measure of the average water molecular motion. In the simplest models, the distribu- tion of a water molecule diffusing in a certain period of time is considered to have a Gaussian form with its width proportional to the ADC. However, water in biological structures often displays non-Gaussian diffusion behavior, consequently the DWI signal shows a more complex behavior that need to be modeled following different approaches. In this work we explore the possibility to quantify the degree to which water diffusion in biologic tissues is non-Gaussian introducing the AKC parameter (Apparent Kurtosis Coefficient). In this work we have realized DWI non-Gaussian diffusion maps to be used in the clinical routine along with standard ADC maps, giving to the radiologist another tool to explore how much structure inside a voxel is organized. In particular in this work some prostate DWI examples have been analyzed and will be shown.