Early detection of Huntington's Disease: Longitudinal analysis of basal ganglia and cortical thickness

项目摘要/摘要 亨廷顿病(HD)是一种神经退行性疾病，通过核磁共振可以检测到大脑的异常 在临床诊断前一到二十年的研究。需要敏感的结果措施才能实现 在出现HD前进行临床试验，以期尽早进行干预和治疗。 Forecast-HD研究(NS040068)确定了基底节和皮质灰质的纵向变化 出现症状前HD患者的主要神经影像表现为物质萎缩。然而，测量 噪声是一个严重的问题，因为它会影响在疾病进展的早期发现异常的能力。 这项建议的目标是开发用于量化大脑皮层和 基底节在时间和空间上保持一致，并利用这些技术来改善 从现有的预测HD数据库中量化HD患者的进展。我们假设 更准确的量化将为HD进展提供更敏感的测量，从而导致 在临床诊断前对纵向变化的敏感性。预计量化的幅度将大大超过 由于我们新的时间和空间上下文感知分段，因此比目前可能的更准确 策略，该策略利用了纵向MRI数据的固有冗余。将实现三个具体目标： 目的1.开发并验证一种新的时间和空间一致的分割方法 HD纵向研究中基底节的量化。预计影响将特别大 对于边界较弱的结构，如伏隔核，很难用现有的 接近了。验证将通过与专家手动分段进行比较来完成。 目的2.开发和验证一种新的用于临床皮层纵向表面重建的方法 HD纵向研究中一致的皮质厚度定量。我们的方法将利用时间 图像到图像上下文，同时避免过度正则化。验证将基于以下内容的重复性 人口研究中的重测扫描和统计区分能力，使用公共数据集。 目标3：评估从我们的新分割中获得的成像测量的统计敏感性的提高 在纵向的先期HD队列中的方法，并通过记录来验证这些成像措施 它们与已知的临床结果评估(COA)和遗传变量之间的关系。我们将使用1246 从Forecast-HD进行扫描，以评估开发的方法的敏感性，并根据临床变量进行验证。 我们预计建议的分割方法将大幅提高现有成像的敏感度- 基于高清中的措施。这将为开发和评估早期治疗干预提供一种手段。 预防疾病发生和减缓疾病进展的战略。同样重要的是，创新的 预计本提案中将开发的方法对于提高对 其他神经退行性疾病，如阿尔茨海默病或帕金森氏病。

PROJECT SUMMARY/ABSTRACT Huntington's disease (HD) is a neurodegenerative disease where brain abnormalities can be detected via MRI studies one to two decades prior to clinical diagnosis. Sensitive outcome measures are needed for enabling clinical trials during pre-manifest HD with the goal of intervention and treatment at the earliest stage possible. The PREDICT-HD study (NS040068) identified longitudinal alterations in the basal ganglia and cortical gray matter atrophy as the primary neuroimaging findings in pre-manifest HD patients. However, measurement noise is a serious concern as it can affect the ability to detect abnormalities early in the disease progression. The objective of this proposal is to develop innovative methods for quantifying the cerebral cortex and the basal ganglia in a temporally and spatially consistent manner and to leverage these techniques to improve the quantification of HD progression in patients from the existing PREDICT-HD database. We hypothesize that more accurate quantification will provide more sensitive measures of HD progression, leading to increased sensitivity to longitudinal changes prior to clinical diagnosis. The quantification is expected to be substantially more accurate than currently possible due to our novel temporal- and spatial- context-aware segmentation strategy, which leverages the inherent redundancy of longitudinal MRI data. Three specific aims will be fulfilled: Aim 1. Develop and validate a novel temporally and spatially consistent segmentation method for quantification of the basal ganglia in longitudinal studies of HD. The impact is expected to be especially large for structures with weak boundaries, such as the nucleus accumbens, which are hard to quantify with existing approaches. Validation will be accomplished via comparison with expert manual segmentations. Aim 2. Develop and validate a novel longitudinal cortical surface reconstruction method for temporally consistent cortical thickness quantification in longitudinal studies of HD. Our approach will utilize temporal image-to-image context while avoiding over-regularization. The validation will be based on reproducibility in test-retest scans and statistical discrimination power in population studies, using public datasets. Aim 3. Assess the increase in statistical sensitivity of imaging measures derived from our new segmentation approaches in a longitudinal pre-manifest HD cohort, and validate these imaging measures by documenting their association with known clinical outcome assessments (COA's) and genetic variables. We will use 1246 scans from Predict-HD to evaluate the sensitivity of developed methods and validate against clinical variables. We anticipate the proposed segmentation methods to substantially increase the sensitivity of existing imaging- based measures in HD. This will provide a means of developing and evaluating early therapeutic intervention strategies in order to prevent disease onset and slow disease progression. Equally significant, the innovative methods to be developed in this proposal are expected to be crucially important for increased sensitivity for other neurodegenerative disorders such as Alzheimer's disease or Parkinson's disease.