MOBILITY, MICROSTRUCTURE AND MRI. DTI WITHOUT A DTI BLACK BOX: THE ART OF MAKING DO.

Because of its non invasive nature, NMR is a unique tool for studying the microstrusture of biological and material samples. This is usually done by monitoring the diffusion coefficients and relaxation times, whose behavior is related to the translational and rotational random molecular motion of the system components. These parameters report on motion on very different time scales, thus providing structural information at a microscopic scale well beyond the usual image resolution. However, while relaxation-weighted images are relatively straightforward to record and analyze, the study of diffusion through MRI calls for an higher level of complexity from both a theoretical and instrumental point of view and it is nowadays well established in the form of diffusion tensor imaging (DTI), a technique introduced by Basser et al. in 1994 [1]. Although software modules exist that alleviate the tedious task of setting all the parameters for the DTI sequence in newer instruments or medical scanners, our old spectrometer - a 4.7 Tesla Bruker AM WB equipped with a PFG drive unit for microimaging - did not offer the "turnkey” DT-MRI Bruker acquisition interface. We got round this by implementing a DTI acquisition module and analyzing the raw data with an open source DTI reconstruction software [2]. Our experience led us to elaborate some of the theoretical and methodological basic concepts of DTI, summarized in the following steps: i) Theoretical basis and assumptions of the equations that lead to the true and apparent calculation of the diffusion coefficient(s) [3]; ii) Acquisition scheme: a diffusion-weighted preparation module based on stimulated echo (STEAM) to provide long diffusion times with minimal T2 relaxation [4] prior to and independent of the imaging scheme; iii) DTI scheme: the amount of diffusion weighting and at least six not collinear PFG orientations (icosahedral geometry) to estimate the six independent elements of the symmetric diffusion tensor; iv) the corrections for cross-terms interactions [5]; v) reduction of eddy currents that generate image artifacts; vi) diffusion tensor reconstruction from DTI raw data, providing information on sample microstructure and architecture for each voxel: mean diffusivity; anisotropy indices and fiber orientation mapping; vii) Phantoms to test and validate the whole procedure: isotropic (water, BSA) and anisotropic (fibers and celery) at different anisotropy degree