Multivariate fuzzy analysis of brain tissue volumes and relaxation rates for supporting the diagnosis of relapsing-remitting multiple sclerosis

Publication date: August 2019Source: Biomedical Signal Processing and Control, Volume 53Author(s): Marco Pota, Massimo Esposito, Rosario Megna, Giuseppe De Pietro, Mario Quarantelli, Vincenzo Brescia Morra, Bruno AlfanoAbstractMultiple Sclerosis (MS) is a chronic neuroinflammatory disorder of the brain and spinal cord, widely studied nowadays, due to its relevant prevalence in the population. Even though no cure exists, an earlier and more adequate choice of treatment could delay its evolution and prevent irreversible sequelae and disability progression. Currently, Magnetic Resonance Imaging (MRI) represents an essential nonclinical tool for the detection of a hallmark of the disease, i.e. the presence of demyelinating lesions within cerebral white matter (WM), and, consequently, for the diagnosis of MS early within its course. However, errors in estimating lesions can contribute to a wrong diagnosis, if only the WM lesion load is taken into account, with a more relevant impact in individuals with a reduced lesion load at an initial clinical event, delaying the start of a treatment until a second clinical relapse or after confirming, successively, dissemination of lesions in time.In this context, this work proposes an innovative system, employing a multivariate analysis approach, with the aim of mining and integrating multiple sensitive neuroimaging markers, including but not limited to the WM lesion load, into classification models for supporting a more robust diagnosis of R...
Source: Biomedical Signal Processing and Control - Category: Biomedical Science Source Type: research