MRI is an especially sensitive tool for supporting the diagnosis of multiple sclerosis (MS) and monitoring its progression. Nevertheless, the correlation between clinical and MRI measures is modest, suggesting that MRI-visible damage is not sufficient to explain the entire spectrum of MS pathological manifestations. There is increasing evidence, indeed, that large volumes of normal-appearing white and gray matter are not spared by the pathological process, since a wide range of abnormalities are detectable outside MRI-visible lesions at post mortem examination. This diffuse pathology leads to neuronal and axonal damage which is responsible for irreversible disability. Quantitative MRI techniques such as proton MR spectroscopy (1H-MRS), magnetization transfer imaging (MTI), diffusion tensor imaging (DTI), perfusion and functional imaging have been shown to be pathologically much more specific and able to quantify diffuse, non MRI-visible abnormalities.
Among these techniques, 1H-MRS has the unique advantage of providing specific biochemical information about the molecular changes associated with the disease. Due to its selective localization in neurons and axons, N-acetylaspartate is considered a marker of neuro-axonal integrity and its level is correlated with clinical disability.
Perfusion imaging is a measure of blood supply to a tissue and is an important indicator of tissue viability as it provides information about the delivery of nutrients and the removal of catabolic products. With dynamic methods the T2* signal loss, due to the intravascular bolus of Gadolinium (Gd), can be used to generate a concentration-time curve of Gd in the imaging area. From this is possible to measures cerebral blood flow, volume and mean transit time. Preliminary studies have shown a perfusion decrease in cortical and sub-cortical gray matter consistent with a neurodegenerative process.
My research investigates the clinical application of integrated multimodal high-field MR structural, chemical and functional techniques to the evaluation of patients with brain disorders, especially MS. These techniques combined with conventional MRI measures could help us to predict the long-term prognosis and to select out patients for aggressive treatments.