Example of map of arterial delay obtained from resting state functional magnetic images through cross-correlation analysis with the superior sagittal sinus signal in a healthy subject.
Functional MRI
Functional and effective connectivity
The main project of this research line is the investigation of the functional and effective connectivity of resting state networks in normal subjects and multiple sclerosis patients. The relatively simple experimental setup of the resting state fMRI makes it ideally suitable for large-scale investigation of how multiple sclerosis affects functional brain connectivity and how the connectivity impairment correlates with clinical disability scales. More specifically, we aim to investigate both functional and effective connectivity with motor disability.
Assessment of cerebral hemodynamic impairment
Alterations in cerebral hemodynamic have been reported in multiple sclerosis patients both in white matter (WM) and grey matter (GM). In particular cerebral arterial arrival time seems to be prolonged in normal appearing WM and deep GM, and associated with disability. As suggested in previous works resting state functional magnetic resonance imaging can be used to map the vascular delay since blood oxygenation level dependent fluctuation largely depends, even not only, on changes in cerebral blood flow. The aim of this study is to investigate the cerebral hemodynamic impairment in multiple sclerosis patients by using noncontrast mapping of arterial delay in rs-fMRI.
EEG-fMRI integration
Combination of information from EEG and fMRI allows one to overcome the low spatial resolution of the former and the low temporal resolution of the latter. Even though both techniques are widely used, their integration is not equally widespread. This is mainly due to several technical matters that arise when combining the two methods as well as to an incomplete understanding of the relationship between the hemodynamic response measured by BOLD-fMRI and the underlying neuronal activity detected by EEG. The main aim of this research line is to investigate how changes in EEG frequency bands affect functional and effective connectivity of resting state networks (RSNs) identified with fMRI.
FAIR people: Alessandra Bertoldo, Matteo Tonietto, Erica Silvestri, Andrea Nordio, Ilaria Mazzonetto, Marco Castellaro
Example of quantitative high resolution (2x2x2 mm) ASL at 3T
Maximum Intensity Projection of in vivo ASL angiography
Perfusion
Quantitative magnetic resonance perfusion research area is mainly divided in two projects
Development of novel methods for quantification of perfusion for Dynamic Susceptibility Contrast MRI
Dynamic Susceptibility Contrast MRI permits the in vivo quantification of brain perfusion using an exogenous contrast agent. We aims to develop new deconvolution approaches to overcome the limitations of existing methods. In this field we developed Nonlinear Stochastic Regularization and we are now working on the application of Stable Spline to DSC-MRI. We have also developed a method for automatic extraction of the Arterial Input function directly from DSC-MRI images.
Development of novel methods for quantification of perfusion for Arterial Spin Labelling
Arterial Spin Labelling permits the in vivo absolute quantification of brain perfusion without needing any contrast agent injection. In this field we have developed a novel deconvolution algorithm, based on Stable Spline kernel, to quantify perfusion and arterial arrival time from QUASAR ASL data. ASL pre-processing is a fundamental step in the analysis of this kind of data, therefore we are developing novel methods for motion correction and outlier detection in order to enhance the robustness of ASL. Current developing involves novel encoding scheme combined with optimized readout for both angiography or perfusion quantification.
FAIR people: Alessandra Bertoldo, Marco Castellaro, Giacomo Tarroni
Processing pipeline of the two-shell diffusion tensor images analysed with NODDI