Muli-scale Structural Imaging of Alzheimer's Disease Neuropathology and Neurodegeneration

阿尔茨海默病神经病理学和神经变性的多尺度结构成像

• 批准号: 10207104
• 负责人: BRADFORD C DICKERSON
• 金额: $ 46.11万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10207104
• 关键词: Alzheimer disease screening; Alzheimer' s Disease; Alzheimer' s disease therapeutic; Amyloid; Area; Atrophic; Autopsy; Biological; Biological Markers; Brain; Cerebrospinal Fluid; Characteristics; Classification; Clinic; Clinical; Clinical Research; Clinical Trials; Complex; Computer Models; Data; Data Set; Databases; Dementia; Detection; Development; Enrollment; Heterogeneity; Histopathology; Image; Individual; Label; Laboratories; Magnetic Resonance Imaging; Maps; Massachusetts; Measurement; Measures; Methods; Molecular Disease; Nerve Degeneration; Neurodegenerative Disorders; Neurofibrillary Tangles; Pathology; Patients; Phenotype; Positron-Emission Tomography; Procedures; Property; Research; Resolution; Spinal Puncture; Structure; Symptoms; Testing; Thick; Tissues; Validation; Work; base; clinical care; clinical diagnostics; clinical trial participant; cost effective; early screening; effective therapy; in vivo; mild cognitive impairment; molecular marker; molecular pathology; morphometry; neuron loss; neuropathology; novel; patient subsets; pre-clinical; screening; specific biomarkers; support vector machine; tau Proteins; three dimensional structure

Project Summary/Abstract. Advanced biomarker mapping has led to the current understanding that Alzheimer’s disease (AD) is an extremely complex neurodegenerative disorder, with substantial heterogeneity in temporal and spatial characteristics of the classical amyloid and tau pathologies and resultant neurodegeneration among patients (as described by the amyloid-tau-neurodegeneration, ‘A-T-N’ biological framework that is the new standard for characterizing the neuropathology of AD). This complexity is a major barrier to clinical care and to the development of effective therapies, highlighting the importance of integrated biomarker neuromapping for understanding AD. However, substantial challenges remain in the neuropathologic characterization of patients. Current procedures for mapping the neurodegenerative component (N) of AD are limited in sensitivity to early pathology. Additionally, the specific biomarkers of the amyloid- and tau-based primary AD neuropathologies are only available through relatively invasive and/or expensive positron emission tomography (PET) and lumbar puncture (LP) cerebrospinal fluid (CSF) procedures in specialized laboratories and clinics. We aim here to advance AD neuropathology mapping on multiple levels: 1) we will implement a novel multi-scale structural mapping (MSSM) MRI procedure for sensitive quantification of the neurodegeneration component of AD; 2) we will use the MSSM procedure to differentially predict amyloid and/or tau positivity in symptomatic and asymptomatic individuals, providing a highly accessible method for pathology detection when advanced biomarkers are not available; 3) we will create individualized ‘A-T-N’ brainmaps through the integration of the MSSM metrics with existing PET amyloid and tau data; and 4) we will use MSSM features for the regional prediction of amyloid and tau pathology for use when PET data are not available. Our Specific Aims are: Aim 1. To test the accuracy of a novel MSSM procedure for probabilistic classification of symptomatic and asymptomatic individuals as being amyloid “positive” or tau “positive.” Hypothesis 1a (H1a). We hypothesize that MSSM ‘N’ metric can be used with a high level of sensitivity to predict whether an individual is A+ measured via PET using standard thresholds and/or T+ measured via PET using standard thresholds, or both. H1b. MSSM will provide better separation of individuals as N+ vs. N- than conventional MRI-based atrophy measures, validated through concordance with molecular pathology and clinical progression. Aim 2. To utilize the novel MSSM features for synthesis of PET-like maps of AD neuropathologic change. H2a. MSSM features will provide accurate spatial prediction of specific regional neuropathologic changes. Prediction accuracy will be measured against independent in vivo datasets including a subset with autopsy confirmation and regional quantification of plaques, tangles, and neuronal loss. Successful MSSM implementation would greatly advance the ability to screen for early and complex AD neuropathology. Successful MSSM implementation would greatly advance the ability to screen for AD neuropathology.

项目摘要/摘要。 先进的生物标记图谱使人们目前认识到阿尔茨海默病 (AD) 是一种 极其复杂的神经退行性疾病，在时间和空间上具有显着的异质性 患者中经典淀粉样蛋白和 tau 蛋白病理学的特征以及由此产生的神经变性 （正如淀粉样蛋白-tau-神经变性所描述的，“A-T-N”生物框架是神经退行性疾病的新标准 这种复杂性是临床护理和治疗的主要障碍。 开发有效的疗法，强调综合生物标志物神经图谱的重要性 然而，在患者的神经病理学特征方面仍然存在重大挑战。 目前绘制 AD 神经退行性成分 (N) 的程序对早期的敏感性有限。 此外，基于淀粉样蛋白和 tau 的原发性 AD 神经病理学的特定生物标志物。 只能通过相对侵入性和/或昂贵的正电子发射断层扫描 (PET) 获得，并且 我们的目标是在专业实验室和诊所进行腰椎穿刺 (LP) 脑脊液 (CSF) 程序。 在多个层面上推进 AD 神经病理学绘图：1）我们将实施一种新颖的多尺度结构 映射 (MSSM) MRI 程序，用于 AD 神经变性部分的灵敏定量 2) 我们； 将使用 MSSM 程序来区分预测有症状和有症状的淀粉样蛋白和/或 tau 蛋白阳性 无症状个体，为晚期病理检测提供了一种易于使用的方法 生物标志物不可用；3）我们将通过整合创建个性化的“A-T-N”脑图 MSSM 指标与现有 PET 淀粉样蛋白和 tau 数据；4) 我们将使用 MSSM 特征进行区域分析； 在无法获得 PET 数据时使用淀粉样蛋白和 tau 蛋白病理学预测 我们的具体目标是： 目标。 1. 测试新型 MSSM 程序对症状和症状进行概率分类的准确性 无症状个体为淀粉样蛋白“阳性”或 tau“阳性”。假设 1a (H1a)。 促进 MSSM“N”指标可以高度敏感地用来预测一个人是否 使用标准阈值通过 PET 测量的 A+ 和/或使用标准阈值通过 PET 测量的 T+，或 与传统的基于 MRI 的 H1b 相比，MSSM 可以更好地区分 N+ 和 N- 个体。 萎缩测量，通过与分子病理学和临床进展的一致性进行验证。 利用新的 MSSM 功能来合成 AD H2a 的类似 PET 的图谱。 MSSM 功能将提供特定区域神经病理变化的准确空间预测。 准确性将根据独立的体内数据集进行测量，包括尸检确认的子集 斑块、缠结和神经损失的区域量化 成功的 MSSM 实施将。 极大地提高了筛查早期和复杂 AD 神经病理学的能力。 实施将大大提高筛查 AD 神经病理学的能力。

项目成果

Brain structural indicators of β-amyloid neuropathology.

β-淀粉样蛋白神经病理学的脑结构指标。

• 发表时间: 2024-04
• 影响因子: 4.2
• 作者: Jang, Ikbeom;Li, Binyin;Rashid, Barnaly;Jacoby, John;Huang, Susie Y;Dickerson, Bradford C;Salat, David H;Alzheimer’s Disease Neuroimaging Initiative
• 通讯作者: Alzheimer’s Disease Neuroimaging Initiative

Automated brain mapping to evaluate the relationship between neurodegeneration, cerebral small vessel disease and structural covariance network disruption in Alzheimer's disease

自动大脑图谱评估阿尔茨海默病中神经退行性变、脑小血管疾病和结构协方差网络破坏之间的关系

• DOI: 10.1093/brain/awx347
• 发表时间: 2018-02-01
• 期刊: Brain
• 影响因子: 14.5
• 作者: Cope TE;Rittman T;Borchert RJ;Jones PS;Vatansever D;Allinson K;Passamonti L;Vazquez Rodriguez P;Bevan-Jones WR;O'Brien JT;Rowe JB
• 通讯作者: Rowe JB