Neuroimaging clinics of North America
-
Multiple sclerosis (MS) is a common disease of the central nervous system, with various clinical symptoms and a heterogeneous disease course. MRI can depict focal and diffuse manifestations of the disease, and accurately measure progression over time. ⋯ More recent genome-wide association studies have revealed other genes to be related to disease susceptibility and severity, explaining part of the variability in symptoms, radiological manifestations and disease course. Studies relating genetics and imaging in MS are discussed in this paper.
-
Neuroimaging Clin. N. Am. · Feb 2015
ReviewMolecular genetics of glioblastomas: defining subtypes and understanding the biology.
Despite comprehensive therapy, which includes surgery, radiotherapy, and chemotherapy, the prognosis of glioblastoma multiforme is very poor. Diagnosed individuals present an average of 12 to 18 months of life. ⋯ Despite the overwhelming amount of data available, so far little has been translated into real benefits for the patient. Because this is such a complex topic, the goal is to point out the main alterations in the biological pathways that lead to tumor formation, and how this can contribute to the development of better therapies and clinical care.
-
Neuroimaging Clin. N. Am. · Feb 2015
Brain imaging and genetic risk in the pediatric population, part 2: congenital malformations of the central nervous system.
In this article, an update is presented of the correlation of imaging and genetic findings in congenital malformations of the central nervous system (CMCNS). A nonsystematic search of the PubMed/Medline database was performed. ⋯ The highlights of genotype-imaging phenotype correlation of some congenital malformations are provided. It is hoped that developments in genotype-MR phenotype in CMCNS will foster further prognostic and pathogenic breakthroughs for the frequently associated neurologic dysfunction in children affected by these common diseases.
-
Imaging genomics combines imaging-defined phenotypes with molecular determinants of disease. Recent studies have examined the relationship between MRI-derived feature sets and gene expression in gliomas, including glioblastoma (GBM). ⋯ The combination of clinical, genetic, and imaging data has improved prognostic modeling and has identified potential therapeutic targets. Many challenges remain in fully leveraging the associations between such large datasets, but even current methodology shows promise in helping to craft individually tailored treatments to patients with brain tumors and other diseases.