Anisotropic conductivity modeling for tDCS in Parkinson's disease using multidimensional diffusion MRI

Transcranial direct current stimulation (tDCS) dose depends on how brain conductivity is modeled. White matter anisotropy is conventionally estimated from single-shell diffusion tensor imaging (DTI). Multidimensional diffusion MRI (MD-dMRI), specifically q-space trajectory imaging (QTI), instead gives a mean tensor expected to carry less kurtosis bias. Our primary question was whether replacing the conventional single-shell tensor with this mean tensor would change the predicted field. We built, to our knowledge, the first MD-dMRI tDCS conductivity model and compared it against DTI and isotropic models in 29 participants (12 with Parkinson's disease, 17 controls) across four montages, with the same mesh, electrodes, and solver. The three models agreed within a few percent. The two anisotropic models differed mainly in tensor orientation (about 21 degrees in white matter), with small differences in field magnitude. Field did not differ between patients and controls in any region or montage (which was an exploratory, underpowered comparison). Whole-brain electric field correlated with MR elastography stiffness (partial r = +0.58) but attenuated to non-significance once cerebrospinal fluid morphology was accounted for (r = +0.06 to +0.09). With no ground-truth field or conductivity available, the study establishes the feasibility of the MD-dMRI model and characterizes field sensitivity rather than improved dosimetry accuracy. The choice of diffusion tensor is second order for dose, which is primarily influenced by individual anatomy. For Parkinson's disease, modeling efforts should focus on cerebrospinal fluid- and atrophy-aware head models and dose normalization, rather than a more complex diffusion tensor.