• UHF
• graph theory
• fMRI
• dMRI

The concept of brain connectivity refers to the way by which different regions of the brain communicate and interact with each other: understanding the brain's connectivity is essential to comprehend how the brain works and, as consequences, may shed a light on the causes of neurological diseases, and the effects of possible interventions.
The anatomical and functional brain connectivity nature can be analyzed through networks. The objective of the analysis of a network is to obtain measures capable of describing how the network itself is organized and exchanges information, as well as to identify the mechanisms that generated it and, consequently, any alterations that can modify it.

Among the various techniques that allow the study of brain networks, Magnetic Resonance Imaging (MRI) is the most suitable method as it is a neuroimaging method with high spatial resolution, it is non-invasive, and it is versatile allowing the measurements of both functional and structural connectivity.
In MRI, structural connectivity is studied through diffusion Magnetic Resonance Imaging (dMRI) method, while functional connectivity is explored by using the resting-state functional MRI (rs-fMRI) technique. In the dMRI method, the signal contrast of the images is based on the detection of differences in Brownian motion of the water molecules so that this technique can be used to study the diffusion of the water in the living brain. On the other hand, rs-fMRI measures spontaneous low-frequency fluctuations (<0.1 Hz) of Blood Oxygenation Level Dependent (BOLD) signal and can be used to investigate the functional architecture and functional connections of the brain, by exploiting the temporal similarity between BOLD signals of different regions of the brain.

In this thesis work, advanced methods were implemented to study brain connectivity using MRI, including the development of structural connectivity techniques at Ultra-High Field (UHF), i.e 7 Tesla. These research activities were conducted at the Laboratory of Medical Physics and Magnetic Resonance of IRCCS Stella Maris and IMAGO7 Research Center (Pisa, Italy), which host respectively a clinical scanner (1.5T until 2021, 3T from December 2021) and the only 7T MRI system for humans in Italy.
An aim of this thesis work was also to explore the application of the study of structural and functional connectivities in clinical populations, as well as to search for a method for integrating structural and functional brain connectivity information using graph measures. We explored this combined approach in neurodegenerative pathology with MRI at a clinical field strength (1.5 T), in particular in a group of subjects affected by Mild Cognitive Impairment condition, a possible precursor of Alzheimer's Disease. Additionally, dMRI techniques were used to investigate structural connectivity and White Matter (WM) alterations in specific fiber tract pathways in two neurodevelopmental disorders: Childhood Apraxia of Speech (CAS) and Dystrophinopathies.

Another important research aim of this thesis concerned the implementation (acquisition, optimization, preprocessing, and analysis) of dMRI techniques on an UHF-7T MRI system. In fact, the 7T scanner available at the IMAGO7 Research Center was recently upgraded with new high-performance software and hardware solutions, which now allow for the implementation of diffusion sequences that were previously strongly impaired due to intrinsic technical limitations. We demonstrated that the use of UHF provides advantages due to increased Signal-to-Noise Ratio (SNR) and improvements in temporal and spatial resolution. However, dMRI encounters challenges at UHF, such as changes in relaxation times and increasing of magnetic field inhomogeneity, which can cause low SNR and geometric distortion. To address these challenges, new techniques based on multi-shot EPI and multi-slice EPI acquisitions were optimized on phantom and applied on healthy volunteers.
Finally, bootstrapping approaches were implemented in order to find a method to evaluate in vivo uncertainty on dMRI and graph measures. In particular, the method was applied in a comparative study, conducted on a group of subjects who underwent optimized dMRI acquisitions at clinical fields (1.5T and 3T) and UHF-7T.
Overall, this study offers valuable insights into the potential of MRI to identify changes in brain connectivities across multiple subjects. Moreover, by comparing UHF-MRI with clinical fields, this thesis demonstrates the specificity of the 7T UHF-MRI and its potential clinical relevance for studying individual cases in numerous neurological disorders