Predictive Imagable Biomarkers for Brain Disorders

Know about the book -

Predictive Imagable Biomarkers for Brain Disorders is written by Pravat K. Mandal and published by Frontiers Media SA. It's available with International Standard Book Number or ISBN identification 288963048X (ISBN 10) and 9782889630486 (ISBN 13).

Recent research on Neurodegenerative disorders such as Alzheimer's Disease, Parkinson's Disease, etc. and Neuropsychiatric disorders such as Schizophrenia, has shown strong evidence that altered brain tissue structure, physiology, and connectivity reflect the extent of severity of behavioral and physical abnormalities. With the advancement of high field strength MR technologies like MRS (Magnetic Resonance Spectroscopy), fMRI (functional Magnetic Resonance Imaging) and DTI (Diffusion Tensor Imaging), it has become possible to non-invasively measure these changes brain microenvironment in terms of levels of antioxidants; neurotransmitters; regional activity, susceptibility and connectivity during transition from healthy to pathological conditions, and during progression of disease stages. Advanced Machine Learning (ML) and Statistical modeling algorithms are utilizing features extracted from multimodal MR based, neuropsychological and neurophysiological data to build classifiers that identify highly sensitive and specific biomarkers to aid in understanding the causal processes of these brain disorders and can be translated from bench to bedside clinical practices for non-invasive diagnostic testing. It is also important to have global clinical research data sharing platforms that utilize data mining and ML to identify early biomarkers and test the sensitivity of old ones from time to time with advancement in research. This Research Topic updates the reader about the latest research in imagable biomarkers using MR methodologies and use of AI for testing the sensitivity of these biomarkers.