Spatially-Constrained Probability Distribution Model of Incoherent Motion (SPIM) in Diffusion Weighted MRI Signals of Crohn’s Disease

Abstract

Diffusion Weighted imaging (DWI) of the body provides important information about the physiological and microstructural properties of tissues and has great potential for imaging inflammatory activity and improve diagnosis and follow up of Crohn’s disease. The two main challenges for DWI are the lack of realistic signal decay models of heterogeneous diffusion and inherently low signal-to-noise ratio (SNR), which makes robust parameter estimation challenging. Increasing the SNR requires long scan times that are not clinically practical. In this work, to address both challenges, we propose a novel Spatially-constrained Probability distribution model of incoherent Motion (SPIM) of water molecules. This model is composed of a probability model of diffusion that we propose to account for the heterogeneity of incoherent motion within multiple compartment tissue microenvironments in each voxel and a spatial homogeneity prior proposed by Freiman et al. for robust parameter estimation. We evaluated the performance of proposed SPIM model in both simulated and in-vivo DWI data from 5 healthy and 24 Crohn’s disease subjects. SPIM model substantially reduced parameter estimation errors, with a reduction of $35\,\%$ for perfusion and $7\,\%$ for perfusion fraction and $4\,\%$ for diffusion parameters. Coefficient of variation of estimated parameters decreased using SPIM compared to simple bi-exponential signal decay model, which indicates an increase in robustness. Parameters estimated using SPIM model better discriminated enhancing and non-enhancing stages of Crohn’s disease.