Student: Pam Wochner
1st supervisor: Ralph Sinkus, King’s College London
2nd supervisor: Jack Lee, King’s College London
Diffusion Weighted Imaging (DWI) in MRI is using the loss of phase coherence within the imaging voxel – induced by the random walk of the spins under the influence of a linear gradient – to deduce micro-structural information. Since diffusion is typically symmetric in space (i.e. equal # of spins moving to the left as to the right), the entire spin ensemble within the imaging voxel does not experience a net phase accrual, but only a loss in total signal magnitude due to dephasing. Hence, classical DWI cannot utilize the MRI-phase information per se. iDWI on the contrary utilizes a novel concept which enables utilization of the MRI-phase information. This opens the gateway to entirely new concepts for diffusion weighted imaging, in particular to elevated sensitivity to micro-architectural complexity, i.e. anomalous diffusion. Anomalous diffusion allows to link the exponent γ of the diffusion space-time relation (R2~tγ, γ<1) to fractality of space (γ=2/dw, dw=fractal dimension of space ∈ [2,3]). In classical DWI this exponent can be measured by taking the log of the log of a multi-b experiment. Clearly, this requires very high SNR clinically not available. On the contrary, iDWI provides linear phase-sensitivity to γ as a function of encoding frequency ν (ν finds its correlate in the classical b-value). Thereby, iDWI has the potential to provide superior sensitivity to micro-structure and is therefore a prime candidate for an imaging biomarker in the context of tumour characterization and response to therapy.
Our team has already preliminary theoretical and numerical results demonstrating proof of concept for this innovative approach. First theoretical estimates indicate one order of magnitude increase in sensitivity to measure the anomalous diffusion coefficient γ. γ is expected to be a key indicator for the onset of cell death, but challenging to assess via classical DWI. Thus, if successful, iDWI can represent a revolution in diffusion imaging. This CDT proposal shall enable and provide the necessary groundwork to further explore the concept, theory, and provide initial experimental data in phantoms and rodent tumour models under therapy.
Figure 1. Random walk trajectories. a, Normal diffusive random walk; b, Lévy random walk with γ=2 (Lévy flight). In the normal diffusive random walk, each step contributes equally to the average transport properties. In the Lévy flight, long steps are more frequent and make the dominant contribution to the transport.