Optimizing automated MRI measures of atrophy in neurodegenerative disease

描述(由申请人提供)：据估计，美国有510万人患有阿尔茨海默氏症，随着预期寿命的增加，预计这一数字将继续上升(医学研究所，2008年)。除了患者及其照顾者(通常是家庭成员)的个人费用外，到2050年，照顾痴呆症患者的成本预计将从2011年估计的1870亿美元增加到1.1万亿美元。目前，被广泛接受的阿尔茨海默病患者海马体测量的自动化方法是自由冲浪。在脑图像分析公司，我们已经使用我们的自动化管道Brains AutoWorkup处理了来自ADNI 1数据集(3500次扫描)的MRI数据。在我们的分析中发现，与标准自由水和自由水中的纵向流相比，我们的方法检测到更高的年萎缩率和更低的相对标准偏差。这导致临床试验每臂所需受试者的估计从使用自由浏览(纵向和横截面工作流)的131或204人大幅减少到使用大脑神经网络方法的56人。这份申请描述了我们打算如何实施和测试纵向ANN方法，并与阿尔茨海默病研究人员和海马体专家合作准备的海马区分段相比，测试我们当前的海马区分段。这将为脑图像分析公司提供它需要的信息，以表明我们的皮质下分割方法是商业图像处理领域中最可行的，在阿尔茨海默病及其治疗的研究中。该项目的第二阶段将包括将这些方法实施到最新版本的Brains中，以及额外的计划基础设施，以使我们的方法在更大的商业规模上可用，以及在大型数据集上实施，以探索临床相关性。在这个项目上与我们合作的将是著名的神经科学研究人员。这些人包括长期担任大脑开发团队负责人的文森特·马尼奥塔博士和南希·安德烈森博士，以及在支持临床试验的大型成像研究方面拥有丰富经验的统计员道格·朗贝恩博士。

DESCRIPTION (provided by applicant): Alzheimer's disease afflicts an estimated 5.1 million people in the United States, and as life expectancies increase it is anticipated that this number will continue to rise (Institute of Medicine, 2008). Besides the personal toll on the patients and their caregivers (who often are family members), the cost of caring for those with dementia is anticipated to grow from the 2011 estimate of $187 billion to $1.1 trillion by the year 2050. Currently the most widely accepted automated method for measurement of the hippocampus in Alzheimer's disease is FreeSurfer. At Brain Image Analysis, LLC we have processed the MRI data from the ADNI 1 dataset (>3500 scans) using our automated pipeline, BRAINS AutoWorkup. In our analysis have found that, in comparisons with both the standard FreeSurfer and the longitudinal stream in FreeSurfer, our methods detect a higher annual atrophy rate with a lower relative standard deviation. This leads to a substantial reduction in the estimates of subjects needed per arm of a clinical trial from 131 or 204 using FreeSurfer (longitudinal and cross-sectional workflows) to 56 using BRAINS ANN methods. This application describes how we intend to implement and test a longitudinal ANN method and test our current hippocampal segmentations against those being prepared by a collaboration of Alzheimer's disease researchers and hippocampus experts. This will provide Brain Image Analysis, LLC with the information it needs to show our methods of subcortical segmentation are the most feasible in the field for commercial image processing in the study of Alzheimer's disease and its treatment. Phase II of this project will encompass implementation of these methods into the newest version of BRAINS and the additional program infrastructure to make our methods available on a larger commercial scale, as well as implementation on a large dataset to explore clinical correlates. Working with us on this project will be renowned neuroscience researchers. These include Dr. Vincent Magnotta and Dr. Nancy Andreasen, long-term leaders of development team for BRAINS, and Dr. Doug Langbehn, serving as our statistician with substantial experience in large imaging studies designed to support clinical trials.