Ex Vivo Imaging of the Aging Brain to Discover Morphology/Pathology Associations
衰老大脑的离体成像以发现形态学/病理学关联
基本信息
- 批准号:10608603
- 负责人:
- 金额:$ 207.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-04-15 至 2026-03-31
- 项目状态:未结题
- 来源:
- 关键词:3-Dimensional3D PrintAddressAlgorithmsAlzheimer associated neurodegenerationAlzheimer&aposs DiseaseAlzheimer&aposs disease pathologyAlzheimer&aposs disease patientAlzheimer&aposs disease related dementiaAmyloidAmyloid beta-ProteinAtlasesAtrophicAutopsyBenefits and RisksBiological MarkersBloodBlood VesselsBrainBrain imagingBrain regionCardiovascular DiseasesCerebral hemisphereCerebral small vessel diseaseChemicalsClinicalClinical TrialsCognitiveDataData SetDementiaDepositionDetectionDevelopmentDiagnosisDiseaseDisease MarkerDisease ProgressionFutureGrantHeterogeneityHistologicHistologyHistopathologyHumanImageImage AnalysisImpaired cognitionIndividualInfarctionKnowledgeLesionLinkLiteratureLocationMagnetic Resonance ImagingMapsMeasuresMedialMethodsMicrovascular DysfunctionMoldsMolecular AbnormalityMorphologyNerve DegenerationNeurofibrillary TanglesNeurologistNeuronsParticipantPathologicPathologyPatternPennsylvaniaPositron-Emission TomographyResearchResolutionScanningSlideSpecimenStructureSurfaceTauopathiesTechniquesTemporal LobeTestingTherapeuticThickThinnessTimeTracerTranslatingUniversitiesWhite Matter HyperintensityWorkaging brainalpha synucleinautomated segmentationbrain cellbrain magnetic resonance imagingcerebral atrophyclinical practicecohortdeep learningdensityex vivo imaginggray matterhippocampal atrophyhistological imagehuman imagingimaging biomarkerimprovedin vivoin vivo imagingindividual patientmagnetic resonance imaging biomarkermorphometrymultimodalityneuron lossneuropathologynovelopen source toolprospectiveprotein TDP-43successtau Proteinstau aggregationtooltreatment responsetwo-dimensionalvascular risk factorwhite matter
项目摘要
Alzheimer's disease (AD) is associated with surprisingly high degree of pathologic heterogeneity. In most
individuals diagnosed with AD at autopsy, the brain not only harbors the β-amyloid and tau pathologies that are
the hallmarks of AD, but also one or more co-pathologies, including TDP-43, α-synuclein, non-AD tauopathy,
and cerebral small vessel disease (SVD). The primary AD pathologies and co-pathologies all contribute to
neurodegeneration in AD, but their relative contribution in different brain regions and the degree in which co-
pathologies modulate the progression of primary pathologies is not well understood. It is widely recognized that
it is important for clinical trials in AD to account for these additional drivers of neurodegeneration, but there is a
lack of in vivo biomarkers that can reliably detect and quantify co-pathology. Pathologic heterogeneity may help
explain why AD treatments targeting a single pathological mechanism have been largely ineffective.
This project seeks to address this limitation by using ex vivo human brain MRI to characterize the contributions
of primary AD pathologies and co-pathologies to neuronal loss and cortical thinning in AD. The project leverages
a prospective dataset from 100-120 autopsies conducted at the University of Pennsylvania AD Research Center
that will include high-resolution 7 Tesla MRI of intact brain hemispheres with co-registered histology at selected
gray matter locations and around white matter lesions. Moreover, the temporal lobe, part of the brain where
earliest and most severe AD-related neurodegeneration occurs, will be scanned at 9.4 Tesla, and undergo serial
histological imaging, allowing three-dimensional mapping of tau pathology (tangles, threads, etc.) and neuronal
density across the entire temporal lobe. This unique ex vivo imaging dataset will represent a convergence of
structural and pathological imaging data in the same 3D space, allowing a broad range of studies analyzing
trajectories of pathology deposition and pathology-neurodegeneration relationships. The specific aims of the
proposal are as follows. Aim 1 is to develop deep learning-based image analysis techniques for 7 Tesla whole-
hemisphere MRI, which are currently lacking, including segmentation of cortical gray matter, white matter lesions,
normal-appearing white matter, and subcortical structures; groupwise registration to both ex vivo and in vivo MRI
templates; and extraction of both MRI-based and histological features to characterize white matter lesions
associated with SVD. Aim 2 is to analyze the complete 100-120 specimen dataset to characterize the distribution
of tau pathology, neuronal loss, and cortical thinning both in the temporal lobe and in the whole brain and to
describe the impact of co-pathologies on these distributions and on the relationships between them. Aim 3 is to
leverage pathology-specific “signatures” extracted from analyzing this ex vivo dataset to improve the sensitivity
of in vivo biomarkers for inferring the presence of co-pathology and tracking disease progression.
阿尔茨海默病(AD)与高度的病理异质性有关。在大多数
在尸检中被诊断为阿尔茨海默病的人,大脑不仅含有β-淀粉样蛋白和tau病理
AD的特征,但也有一个或多个共同病理,包括TdP-43,α-突触核蛋白,非AD血管病变,
和脑部小血管疾病(SVD)。阿尔茨海默病的主要病理和共同病理都有助于
阿尔茨海默病的神经退行性变,但它们在不同脑区的相对贡献和相互作用的程度。
病理对原发病理进展的调节作用尚不清楚。人们普遍认识到
对于AD的临床试验来说,解释这些导致神经变性的额外驱动因素是很重要的,但有一个
缺乏能够可靠地检测和量化共病的体内生物标志物。病理异质性可能会有所帮助
解释为什么针对单一病理机制的AD治疗在很大程度上无效。
这个项目试图通过使用体外人脑核磁共振来表征这些贡献来解决这一局限。
阿尔茨海默病的原发病理和共病导致AD的神经元丢失和皮质变薄。该项目利用
在宾夕法尼亚大学AD研究中心进行的100-120例尸检的前瞻性数据集
这将包括对完整的大脑半球进行高分辨率7特斯拉磁共振成像,并与SELECTED的组织学共同注册
灰质部位及周围白质病变。此外,颞叶,大脑的一部分,
最早和最严重的AD相关神经变性发生,将在9.4特斯拉扫描,并进行连续
组织成像,允许对tau病理(缠结、线条等)进行三维映射。和神经元
整个颞叶的密度。这一独特的体外成像数据集将代表
同一3D空间中的结构和病理成像数据,允许广泛的研究分析
病理沉积和病理-神经退变关系的轨迹。《公约》的具体目标
建议如下。目标1是为7辆特斯拉整车开发基于深度学习的图像分析技术-
目前缺乏的半球MRI,包括皮质灰质分割,白质病变,
外观正常的白质和皮质下结构;GroupWise注册到体外和体内MRI
模板;以及基于MRI和组织学特征的提取以表征白质病变
与奇异值分解有关。目标2是分析完整的100-120个样本数据集以表征其分布
在颞叶和整个大脑中的tau病理、神经元丢失和皮质变薄
描述共病对这些分布的影响以及它们之间的关系。目标3是
利用从分析该体外数据集中提取的特定于病理的“特征”来提高灵敏度
体内生物标记物用于推断共同病理的存在和跟踪疾病进展。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Paul A. Yushkevich其他文献
Posterior hippocampal sparing in Lewy body disorders with Alzheimer’s copathology: An <em>in vivo</em> MRI study
- DOI:
10.1016/j.nicl.2024.103714 - 发表时间:
2025-01-01 - 期刊:
- 影响因子:
- 作者:
Jesse S. Cohen;Jeffrey Phillips;Sandhitsu R. Das;Christopher A. Olm;Hamsanandini Radhakrishnan;Emma Rhodes;Katheryn A.Q. Cousins;Sharon X. Xie;Ilya M. Nasrallah;Paul A. Yushkevich;David A. Wolk;Edward B. Lee;Daniel Weintraub;David J. Irwin;Corey T. McMillan - 通讯作者:
Corey T. McMillan
Operationalizing postmortem pathology-MRI association studies in Alzheimer’s disease and related disorders with MRI-guided histology sampling
- DOI:
10.1186/s40478-025-02030-y - 发表时间:
2025-05-28 - 期刊:
- 影响因子:5.700
- 作者:
Chinmayee Athalye;Alejandra Bahena;Pulkit Khandelwal;Sheina Emrani;Winifred Trotman;Lisa M. Levorse;Zahra Khodakarami;Daniel T. Ohm;Eric Teunissen-Bermeo;Noah Capp;Shokufeh Sadaghiani;Sanaz Arezoumandan;Sydney A. Lim;Karthik Prabhakaran;Ranjit Ittyerah;John L. Robinson;Theresa Schuck;Edward B. Lee;M. Dylan Tisdall;Sandhitsu R. Das;David A. Wolk;David J. Irwin;Paul A. Yushkevich - 通讯作者:
Paul A. Yushkevich
Correction: Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer’s disease
- DOI:
10.1186/s13195-023-01374-8 - 发表时间:
2024-01-12 - 期刊:
- 影响因子:7.600
- 作者:
Long Xie;Sandhitsu R. Das;Laura E. M. Wisse;Ranjit Ittyerah;Robin de Flores;Leslie M. Shaw;Paul A. Yushkevich;David A. Wolk - 通讯作者:
David A. Wolk
213: Novel 3D morphologic analysis of the early placenta using deformable medial modeling
- DOI:
10.1016/j.ajog.2016.11.118 - 发表时间:
2017-01-01 - 期刊:
- 影响因子:
- 作者:
Alison M. Pouch;Ipek Oguz;Natalie Yushkevich;James C. Gee;Paul A. Yushkevich;Nadav Schwartz - 通讯作者:
Nadav Schwartz
Paul A. Yushkevich的其他文献
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{{ truncateString('Paul A. Yushkevich', 18)}}的其他基金
AD-specific changes in the MTL: Novel biomarkers using in vivo / ex vivo imaging
MTL 中的 AD 特异性变化:使用体内/离体成像的新型生物标志物
- 批准号:
9301869 - 财政年份:2017
- 资助金额:
$ 207.77万 - 项目类别:
AD-specific changes in the MTL: Novel biomarkers using in vivo / ex vivo imaging
MTL 中的 AD 特异性变化:使用体内/离体成像的新型生物标志物
- 批准号:
9927957 - 财政年份:2017
- 资助金额:
$ 207.77万 - 项目类别:
Adaptive Large-Scale Framework for Automatic Biomedical Image Segmentation
自动生物医学图像分割的自适应大规模框架
- 批准号:
9350173 - 财政年份:2014
- 资助金额:
$ 207.77万 - 项目类别:
Adaptive Large-Scale Framework for Automatic Biomedical Image Segmentation
自动生物医学图像分割的自适应大规模框架
- 批准号:
8761531 - 财政年份:2014
- 资助金额:
$ 207.77万 - 项目类别:
Adaptive Large-Scale Framework for Automatic Biomedical Image Segmentation
自动生物医学图像分割的自适应大规模框架
- 批准号:
9119513 - 财政年份:2014
- 资助金额:
$ 207.77万 - 项目类别:
Continued Development and Maintenance of ITK-SNAP 3D Image Segmentation Software
ITK-SNAP 3D 图像分割软件的持续开发和维护
- 批准号:
8333255 - 财政年份:2011
- 资助金额:
$ 207.77万 - 项目类别:
Continued Development and Maintenance of ITK-SNAP 3D Image Segmentation Software
ITK-SNAP 3D 图像分割软件的持续开发和维护
- 批准号:
8531010 - 财政年份:2011
- 资助金额:
$ 207.77万 - 项目类别:
Continued Development and Maintenance of ITK-SNAP 3D Image Segmentation Software
ITK-SNAP 3D 图像分割软件的持续开发和维护
- 批准号:
8725972 - 财政年份:2011
- 资助金额:
$ 207.77万 - 项目类别:
Continued Development and Maintenance of ITK-SNAP 3D Image Segmentation Software
ITK-SNAP 3D 图像分割软件的持续开发和维护
- 批准号:
8222185 - 财政年份:2011
- 资助金额:
$ 207.77万 - 项目类别:
Novel Imaging Biomarkers for Treatment Evaluation in Neurodegenerative Disorders
用于神经退行性疾病治疗评估的新型成像生物标志物
- 批准号:
8454486 - 财政年份:2010
- 资助金额:
$ 207.77万 - 项目类别:
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