Optimizing automated MRI measures of atrophy in neurodegenerative disease

描述（由申请人提供）：阿尔茨海默病在美国折磨着大约510万人，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）。除了患者及其护理人员（通常是家庭成员）的个人费用外，到2050年，护理痴呆症患者的费用预计将从2011年的1870亿美元增加到1.1万亿美元。目前最广泛接受的自动化方法测量的海马在阿尔茨海默病是FreeSurfer。在Brain Image Analysis，LLC，我们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FreeSurfer和FreeSurfer中的纵向流相比，我们的方法检测到更高的年萎缩率，相对标准差更低。这导致临床试验每组所需受试者的估计值大幅减少，从使用FreeSurfer（纵向和横截面工作流程）的131或204例减少到使用BRAINS ANN方法的56例。本申请描述了我们打算如何实施和测试纵向人工神经网络方法，并测试我们目前的海马分割对阿尔茨海默病研究人员和海马专家的合作准备。这将为Brain Image Analysis，LLC提供所需的信息，以表明我们的皮层下分割方法在阿尔茨海默病及其治疗研究中的商业图像处理领域是最可行的。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和额外的程序基础设施中，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。其中包括Brains开发团队的长期领导者Vincent Magnotta博士和Nancy Andreasen博士，以及在支持临床试验的大型成像研究方面具有丰富经验的统计学家Doug Langbehn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.