Robust detection of atrophy over short intervals in AD and FTLD

项目总结 阿尔茨海默病、额颞叶变性和其他导致痴呆症的疾病是 21世纪的主要公共卫生问题。这一神经退行性疾病家族涉及 大脑功能回路的中断，最终导致脑细胞死亡。在生活的人中，标准 神经变性的测量是从脑部MRI扫描中得出的，它可以定量地测量位置 以及萎缩的程度。这在传统上是这样做的，并在许多研究中继续这样做，时间间隔为 一年，每隔一年收集一到两次扫描，估计大脑萎缩的年化比率。在一些 临床试验，扫描可能会更频繁地收集，但在最近一次失败的III期试验中，旨在减缓 神经退行性变他们是相隔80周采集的。这项工作的目标是展示新的 我们和同事开发的方法能够提高检测脑内萎缩的敏感度 个体在短的时间间隔上，下降到短到3个月。这是通过制作大量的 为每个个体在每个时间点进行极快、高精度的重复测量。我们的目标是 证明这些新的MRI神经退行性变测量方法的可靠性和有效性 早发性患者的MRI测量及与PET和临床测量对照的外部验证 阿尔茨海默病或行为变异型额颞叶痴呆。如果成功，这项工作可能会带来革命性的 这一领域为追踪神经变性打开了一扇新的大门，潜在地极大地方便了临床 审判。

PROJECT SUMMARY Alzheimer’s disease, Frontotemporal Lobar Degeneration, and other diseases that lead to dementia are one of the 21st century’s major public health problems. This family of neurodegenerative diseases involves the disruption of functional brain circuits and ultimately the death of brain cells. In living people, the standard measure of neurodegeneration is derived from brain MRI scans, which can quantitatively measure the location and amount of atrophy. This is traditionally done, and continues to be done in many studies, over intervals of one year, with one or two scans collected one year apart, estimating annualized rates of brain atrophy. In some clinical trials, scans may be collected more frequently, but in one recent failed phase III trial aiming to slow neurodegeneration they were collected 80 weeks apart. The goal of this work is to demonstrate that new methods we and our colleagues have developed are able to improve the sensitivity to detect atrophy within individuals over short intervals of time, down to as little as 3 months. This is done by making a large number of extremely fast, highly precise repeated measurements at each time point for each individual. We aim to demonstrate the reliability and validity of these new MRI measures of neurodegeneration against traditional MRI measures and externally validated against PET and clinical measures in individuals with Early-onset Alzheimer’s disease or behavioral variant Frontotemporal Dementia. If successful, this work could revolutionize the field and open the door to a new means to track neurodegeneration, potentially greatly facilitating clinical trials.