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

亨廷顿病的早期检测：基底神经节和皮质厚度的纵向分析

• 批准号: 9174773
• 负责人: Ipek Oguz
• 金额: $ 32.87万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9174773
• 关键词: Affect; Age; Alzheimer' s Disease; Atrophic; Basal Ganglia; Biological; Biological Markers; Brain; Brain imaging; Cerebral cortex; Clinical; Clinical Trials; Cognitive; Consensus; Data; Data Set; Databases; Dependency; Discrimination; Disease; Disease Progression; Early Diagnosis; Early Intervention; Genetic; Genetic screening method; Globus Pallidus; Goals; Huntington Disease; Image; Image Analysis; Inherited; Intervention; Joints; Length; Longevity; Longitudinal Studies; MRI Scans; Magnetic Resonance Imaging; Manuals; Measurement; Measures; Methods; Motor; Neurodegenerative Disorders; Noise; Nucleus Accumbens; Onset of illness; Outcome Assessment; Outcome Measure; Parkinson Disease; Patients; Population; Reproducibility; Research; Scanning; Staging; Statistical sensitivity; Structure; Surface; Techniques; Testing; Therapeutic Intervention; Thick; Time; Trinucleotide Repeats; Validation; base; brain abnormalities; clinical Diagnosis; cohort; gray matter; improved; innovation; interest; longitudinal analysis; neuroimaging; normal aging; novel; novel therapeutic intervention; prevent; putamen; reconstruction

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.

项目概要/摘要 亨廷顿舞蹈症 (HD) 是一种神经退行性疾病，可通过 MRI 检测到大脑异常 在临床诊断前一到二十年进行研究。需要采取敏感的结果措施来实现 在 HD 前期进行临床试验，目标是尽早进行干预和治疗。 PREDICT-HD 研究 (NS040068) 确定了基底神经节和皮质灰质的纵向变化 物质萎缩是 HD 患者的主要神经影像学表现。然而，测量 噪音是一个严重的问题，因为它会影响疾病进展早期检测异常的能力。 该提案的目的是开发量化大脑皮层和大脑皮层的创新方法 基底神经节以时间和空间一致的方式，并利用这些技术来改善 从现有的 PREDICT-HD 数据库中量化患者的 HD 进展。我们假设 更准确的量化将为HD进展提供更灵敏的测量，从而导致增加 临床诊断前对纵向变化的敏感性。预计量化将大幅提升 由于我们新颖的时间和空间上下文感知分割，比目前更准确 策略，利用纵向 MRI 数据固有的冗余。将实现三个具体目标： 目标 1. 开发并验证一种新颖的时空一致分割方法 HD 纵向研究中基底神经节的量化。预计影响会特别大 对于边界较弱的结构，例如伏隔核，很难用现有的方法进行量化 接近。验证将通过与专家手动分割进行比较来完成。 目标 2. 开发并验证一种新颖的纵向皮层表面重建方法，用于时间 HD 纵向研究中一致的皮质厚度量化。我们的方法将利用时间 图像到图像的上下文，同时避免过度正则化。验证将基于重现性 使用公共数据集进行人口研究中的重测扫描和统计辨别力。 目标 3. 评估从我们的新分割中得出的成像测量的统计敏感性的增加 纵向预表现 HD 队列中的方法，并通过记录来验证这些成像测量 它们与已知的临床结果评估（COA）和遗传变量的关联。我们将使用 1246 Predict-HD 扫描可评估所开发方法的敏感性并根据临床变量进行验证。 我们预计所提出的分割方法将大大提高现有成像的灵敏度 - 基于高清的措施。这将为开发和评估早期治疗干预提供一种手段 预防疾病发作和减缓疾病进展的策略。同样重要的是，创新 预计本提案中将开发的方法对于提高对环境的敏感性至关重要。 其他神经退行性疾病，例如阿尔茨海默病或帕金森病。