Towards Improving the Specificity of Human Brain Microstructure Research with Diffusion-Weighted MRI

The possibility to perform virtual, non-invasive, quantitative, in vivo histological assessments might revolutionize entire fields, among which clinical and cognitive neurosciences. Magnetic Resonance Imaging (MRI) is an ideal non-invasive imaging technique to achieve these goals. Tremendous advancements in the last decades have favored the transition of MRI scanners from “imaging devices” to “measurement devices” (Novikov, 2021), thus capable to yield measurements in physical units, which might be further combined to provide quantities describing histological properties of substrates. A central role in this community endeavor has been played by diffusion-weighted MRI (dMRI), which by measuring the dynamics of spin diffusion, allows inferences on geometrical properties of tissues. Yet, conventional dMRI methodologies suffer from poor specificity. In this thesis, techniques aiming at improving the specificity of microstructural descriptions have been explored in dMRI datasets supporting an increasing level of complexity of the dMRI signal representations. Applications in individuals with different age range, in different populations, and for different MRI scanner fields, have been considered. Firstly, tractography has been combined with Diffusion Tensor Imaging (DTI), an along-tract framework, and morphometry, in the study of the microstructure of the optic radiations in different groups of blind individuals. Secondly, DTI has been combined with Free-Water Imaging (FWI) to monitor the effect of proton-irradiation in a pediatric brain tumor case study. Thirdly, FWI and Diffusion Kurtosis Imaging (DKI) have been combined with an advanced thalamic segmentation framework to study the associations between motor performance and thalamic microstructure in a cohort of individuals affected by Parkinson’s disease. Finally, the largest contribution of this thesis is represented by the adaptation of the Correlation Tensor Imaging - a technique increasing the specificity of DKI harnessing Double Diffusion Encoding previously applied only in preclinical settings - for a clinical 3 T scanner. The ensuing investigation revealed new important insights on the sources of diffusional kurtosis, in particular of the microscopic kurtosis (μK), a component so far neglected by contemporary neuroimaging techniques, which might carry an important clinical role (Alves et al., 2022), and can now be accessed by clinical scanners. In conclusion, strategies to increase the specificity of microstructural descriptions in the brain are presented for different datasets, and their strength and limitations are discussed.