Diffusion-weighted imaging with flow-compensated diffusion encodings and tri-exponential IVIM imaging

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The intravoxel incoherent motion (IVIM) by Denis le Bihan et al. attributes the observed strong signal decay in magnetic resonance diffusion-weighted imaging at low b-values to the presence of a compartment containing blood as a flowing fluid, which is separated from a tissue compartment that only experiences diffusive motion. The IVIM model is attractive because it allows assessment of perfusion parameters in native exams. Ongoing discussions about Gadolinium depositions in the human brain have further increased this attractiveness. This proposal builds on two recent research findings. First, the IVIM effect vanishes when using short flow-compensated (FloCo) diffusion encodings, but returns for FloCo diffusion encodings of longer duration. Using the IVIM model by Denis le Bihan et al. for interpreting this behavior makes possible the assessment of blood flow correlation time τ and vessel segment length l, which represent parameters that are important in the context of angiogenesis in oncology. Second, the often assumed bi-exponential signal decay model breaks down at low b-values and a tri-exponential model (tri-exp) often appears to be more appropriate. The origin of this tri-exponential behavior is currently unclear, but appealing interpretations can easily be imagined such as attributing venous and arterial compartment to the two flow-compartments of the tri-exponential model. This proposal aims at elucidating the mechanisms that generate the FloCo and tri-exp IVIM contrast. Experimentally, this shall be achieved by performing FloCo and tri-exp IVIM with varying echo time (TE) and field strength (B0). This shall help identifying the contributions of different compartments (such as venous, arterial, pre-urine in kidney) by making use of the fact that transversal relaxation times of these compartments differ and moreover depend on B0. Since these IVIM exams are experimentally challenging, one part of the proposal is focused on optimized data acquisition strategies. The experiments will be conducted measuring healthy volunteers.