Quantifying Brain Abnormality by Multimodality Neuroimage Analysis,

通过多模态神经图像分析量化大脑异常，

• 批准号: 8688869
• 负责人: Dinggang Shen
• 金额: $ 39.8万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8688869
• 关键词: Affect; Algorithms; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid; Appearance; Autistic Disorder; Autopsy; Brain; Brain Diseases; Brain region; Cause of Death; Characteristics; Classification; Clinical; Cognitive; Complex; Computers; Data; Databases; Dementia; Diagnosis; Diagnostic; Discipline of Nuclear Medicine; Disease; Disease Progression; Early Diagnosis; Effectiveness; Elderly; Evaluation; Feedback; Goals; Image; Individual; Intervention; Joints; Judgment; Label; Learning; Maps; Measures; Methods; Modality; Modeling; Molecular; Monitor; Multiple Sclerosis; Neurofibrillary Tangles; Neuropsychological Tests; Pathology; Patients; Pattern; Performance; Phase; Predisposition; Preventive Intervention; Process; Prophylactic treatment; Psychometrics; Public Health; Recording of previous events; Reporting; Research; Research Personnel; Schizophrenia; Scientist; Senile Plaques; Sensitivity and Specificity; Severity of illness; Staging; Structure; Techniques; Testing; Therapeutic; base; clinically relevant; comparison group; cost; design; disease diagnosis; effective therapy; imaging modality; improved; innovation; mild cognitive impairment; multimodality; multitask; nervous system disorder; neuroimaging; neuropsychological; novel; pre-clinical; public health relevance; screening; success

DESCRIPTION (provided by applicant): Alzheimer's disease (AD) affects a total of 5.3 million individuals in the U.S. alone, making it the 7th leading cause of death and also costing about 172 billion dollars annually. Currently, AD diagnosis is predominantly based on clinical and psychometric assessment. However, diagnosis can only be certain if an autopsy reports the presence of characteristic neuritic ¿-amyloid plaques and neurofibrilatory tangles in specific brain regions in an individual with a history of progressive dementia. Thus, there is a significant unmet need for non-invasive objective diagnosis and quantification of pathologies, as well as general assessment of disease progression. The goal of this project is to develop a novel neuroimaging analysis framework that will harness the complementary information from different imaging modalities for effective quantification of disease -induced pathologies, so as to promote early detection for possible treatment and prophylaxis. Achieving this goal requires significant innovation in neuroimage analysis techniques to detect sophisticated yet subtle brain alteration patterns. Accordingly, the specific aims of this project are (Aim 1: Disease Diagnosis) to develop a multimodality multivariate diagnosis technique for accurate identification of individuals who are at risk for AD, (Aim 2: Progress Monitoring) to design a novel multi-task kernel learning framework for prediction and quantification of brain abnormality at various disease stages, and (Aim 3: Evaluation) to assess the developed methods using a large database of elderly subjects, for their diagnostic power in quantifying brain alteration patterns in AD/MCI patients, their predictive power of MCI patients who are at risk for AD, and also their capability in quantifying abnormalities as the disease progresses. We expect, upon successful completion of this project, that the resulting comprehensive, integrated, and effective diagnosis/monitoring framework will be conducive to improving the success of early detection of MCI/AD, as well as other neurological disorders including schizophrenia, autism, and multiple sclerosis. Public Health Relevance Statement: Prior to the appearance of clinical symptomatology, AD undergoes a prodromal phase, lasting from years to decades, with disease pathology or predisposition that is clinically undetectable or uncertain. Thus, identifying individuals who are t risk for AD is critical if disease-modifying treatments are to be effective. For this reason, the neuroimage analysis techniques developed in this project are significantly relevant to public health in that they will help improve accuracy in patient identification and disease monitoring for effective treatment.

描述（由申请人提供）：阿尔茨海默病（AD）仅在美国就影响了总共530万人，使其成为第七大死亡原因，每年也花费约1720亿美元。目前，AD的诊断主要基于临床和心理测量评估。然而，只有尸检报告有进行性痴呆病史的个体在特定脑区出现特征性的神经性淀粉样斑块和神经纤颤缠结时，诊断才能确定。因此，有一个显著的