Investigating Anatomic Orientations of Brain Degeneration in Alzheimers Disease

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PROJECT SUMMARY Alzheimer's disease (AD) is the brain to intervention To slow the progression of AD through intervention, a non-invasive and expensive early detection method is key. Using magnetic resonance imaging (MRI) to detect very small anatomic changes in the brain could play an important role in most common form of dementia. The disease is associated with changes in structures that support memory and higher cognitive functions. The pathophysiologic processes leading AD begin well before the onset of clinically detectable symptoms. Currently, no medication or particular has been clearly shown to delay or halt the progression of the disease. early detection. The proposed multidisciplinary research project will involve the collaboration of investigators from diverse and complementary backgrounds (abiomechanical engineer, an MR physicist, a neuroradiologist and cognitive neuroscientists) to investigate early AD imaging biomarkers which can be derived from one of the most common structural MRI scans. We structural MRI biomarkers derived from propose two specific biomechanical methods to aims to validate measure signs the feasibility of early AD. of new Aim 1: Considering anatomic features of individual brains, such as orientations of cortical sulci and gyri, we will analyze three-dimensional deformations along these neuroanatomic orientations. Using the Alzheimer's Disease Neuroimaging (ADNI) dataset, we will compare the longitudinal changes impairment), Initiative in brains of 301 cognitively normal individuals and 870 using images that were obtained over a 48-month period. people with trajectory of early AD (mild anatomic cognitive We will compare the statistical power to detect abnormal brain degeneration patterns in early AD subjects between our new morphometry algorithm and conventional volumetric or cortical thickness measures. Aim predict and (PET) biomarkers. longitudinal biomarkers multidisciplinary advance 2: We will propose a statistical model to individual cognitive decline, considering substantial inter-subject variability in baseline characteristics disease progression rates. Within the ADNI dataset, we will use longitudinal positron emission tomography images and MRI biomarkers, to determine the temporal ordering among MRI, PET, and cognitive The goal of these studies is to gauge the clinical utility of imaging biomarkers by correlating with neurop sychological assessment data. Here, we will determine if single or multi-modality imaging can predict decline clinical onset. The large datasets available and the team led by an Early-Stage Investigator will facilitate the likelihood of meaningful results to the field of AD diagnosis and prevention cognitive before . This framework will be the foundation of continued work to create a new paradigm for use structural MRI biomarkers in longitudinal studies of AD. Once developed, our software programs will be shared through a public software development/sharing platform.