Simulation of lesions in nuclear magnetic resonance images using zinc nanoparticles in brain phantom

• Grant number: 20/03022-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): September 01, 2020
• Effective date (End): February 28, 2022
• Field of knowledge: Health Sciences - Medicine - Medical Radiology
• Principal Investigator: Marina Piacenti da Silva
• Grantee: Hulder Henrique Zaparoli
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

Multiple sclerosis (MS) is an autoimmune disease characterized by causing damage to the myelin sheath, which, when damaged, impairs the efficient conduction of neural impulses. The cause of MS includes genetic and environmental factors that contribute to the risk of the disease. Although this disease is believed to be multifactorial in etiology, studies point to a role for environmental exposure to heavy metals and susceptibility to genes associated with the immune response and the subsequent development of MS. Among the possible metals involved as external agents that cause multiple sclerosis, there is Zinc (Zn), as this element can play a significant role in the pathogenesis of MS, characterized by its high concentration in the central nervous system and its involvement in physiology of the brain. Thus, interruption of Zn homeostasis may be associated with the development of neurodegenerative diseases.The main test used to detect brain changes in patients with multiple sclerosis is magnetic resonance imaging (MRI). In the picture, MS is characterized by brain lesions where the neurodegeneration process occurs. MRI studies seek to include quantitative mapping in addition to a qualitative image assessment. Although quantitative mapping of markers such as metals can significantly increase the amount, reliability and comparability of data obtained from medical images, careful standardization of protocols and the development of standard reference objects or calibration structures (phantoms) are required to validate the accuracy of these measurements in vivo and to evaluate the repeatability and reproducibility of the measurements in the images. Thus, this work aims to identify metals in magnetic resonance images obtained using a brain simulator object (phantom).