Neuroimaging Biomarkers In Alzheimers Disease

In view of the growing prevalence of AD worldwide, there is an urgent need for the development of better diagnostic tools and more effective therapeutic interventions. Indeed, much work in this field has been done during last decades. As such, a major goal of current clinical research in AD is to improve early detection of disease and presymptomatic detection of neuronal dysfunction, concurrently with the development of better tools to assess disease progression in this group of disorders. All these putative correlates are commonly referred to as AD-related biomarkers. The ideal biomarker should be easy to quantify and measure, reproducible, not subject to wide variation in the general population and unaffected by co- morbid factors. For evaluation of therapies, a biomarker needs to change linearly with disease progression and closely correlate with established clinico-pathological parameters of the disease. There is growing evidence that the use of biomarkers will increase our ability to better indentify the underlying biology of AD, especially in its early stages. These biomarkers will improve the detection of the patients suitable for research studies and drug trials, and they will contribute to a better management of the disease in the clinical practice. Indeed, much work in this field has been done during last decades. The vast number of important applications, combined with the untamed diversity of already identified biomarkers, show that there is a pressing need to structure the research made on AD biomarkers into a solid, comprehensive and easy to use tool to de deployed in clinical settings. To date there are few publications compiling results on this topic. That is why when I was asked to address this task I accepted inmediately. I am happy to present you a bundle of the best articles published about biomarkers for Alzheimer’s disease in recent times.

Biomarkers in Alzheimer’s Disease provides a comprehensive overview of all modalities of Alzheimer’s disease biomarkers, including neuroimaging, cerebrospinal fluid, genomic, and peripheral systems. Each chapter integrates molecular/cellular abnormality due to Alzheimer’s disease and technological advancement of biomarkers techniques. The book is ideal for clinical neuroscience and molecular/cellular neuroscience researchers, psychiatrists, and allied healthcare practitioners involved in the diagnosis and management of patients with cognitive impairment and Alzheimer’s disease, and for differential diagnosis of Alzheimer’s disease with other non-Alzheimer’s dementia. Presents a comprehensive overview detailing all modalities of Alzheimer’s disease biomarkers Written for neuroscience researchers and clinicians studying or treating patients with Alzheimer’s Disease Integrates, in each chapter, the molecular/cellular abnormality due to Alzheimer’s disease and the technological advancement of biomarkers techniques

Subjective cognitive decline (SCD) with self-reported concerns and mild cognitive impairment (MCI) are well-established to be at increased risk of developing Alzheimer’s disease (AD) dementia and a clinical continuum of dementia progression as a spectrum of AD. AD may develop from SCD to MCI (early MCI and late MCI) and eventually to AD. Nevertheless, until recently little was known about their pathophysiology associated with cognitive-behavioral syndrome. Although for researchers, scientists and clinicians, the pathophysiology of AD spectrum is an intriguing issue, delineating it in a clear way is far from easy. Taken together, in-depth understanding of neuroimaging-based pathology behind cognitive impairments across AD spectrum may help to develop new strategy for the early diagnosis and treatment of AD. Neuroimaging has been thought to potentially reveal the pathological mechanisms of AD progression. Individuals across AD spectrum are often associated with anatomical and functional brain alterations and cognitive impairment, most of the pathophysiology will focus primarily on the brain. To investigate brain structures and functions associated with cognition, neuroimaging will be the most appropriate tool.

Zusammenfassung: This fully updated volume provides an up-to-date and comprehensive overview of the current state of technologies helping to accelerate Alzheimer's disease drug development. Addressing the latest advances in preclinical and clinical research, including new insights into the molecular mechanisms and emerging therapeutic strategies, the book continues by exploring digital biomarkers and advanced neuroimaging analysis which will transform how clinical trials in the Alzheimer's disease field are performed. Written for the highly successful Methods in Molecular Biology series, chapters feature the kind of detailed implementation advice that leads to greater success in the lab or clinic. Authoritative and practical, Biomarkers for Alzheimer's Disease Drug Development, Second Edition seeks to inspire and inform future efforts to develop effective treatments for this devastating disease

Nearly 5.3 million Americans are living with Alzheimer's disease, and 26.6 million people are affected worldwide. The Alzheimer's Disease Neuroimaging Initiative (ADNI), a public-private partnership, provides a publicly available, international database of clinical and imaging data to foster research and collaboration on Alzheimer's research worldwide. The Institute of Medicine held a workshop on July 12, 2010, to explore opportunities to use information from and partnerships formed because of ADNI to continue to improve the understanding and treatment of Alzheimer's disease.

There has been increasing interests in exploring biomarkers from brain images, aiming to have a better understanding and a more effective diagnosis of brain disorders such as schizophrenia, bipolar disorder, schizoaffective disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease and so on. Therefore, it is important to identify disease-specific changes for distinguishing healthy controls and patients with brain disorders as well as for differentiating patients with different disorders showing similar clinical symptoms. Biomarkers can be identified from different types of brain Imaging techniques including functional magnetic resonance imaging (fMRI), structural MRI, positron emission tomography (PET), electroencephalography (EEG), and magnetoencephalography (MEG) by using statistical analysis methods. Furthermore, based on measures from brain imaging techniques, machine learning techniques can help to classify or predict disease for individual subjects. In fact, fusion of features from multiple modalities may benefit the understanding of disease mechanism and improve the classification performance. This Research Topic further explores the functional or structural alterations in brain disorders.