Diffusion Tensor Imaging in First-Episode Schizophrenia

首发精神分裂症的弥散张量成像

基本信息

项目摘要

DESCRIPTION (provided by applicant): Considerable research suggests that schizophrenia is characterized by a defect in frontotemporal regions with increasing evidence that a defect in the brain white matter of this integrated system is critical to phenomenology. Diffusion tensor imaging (DTI) can be used to quantify the directionality and coherence of water self-diffusion allowing the examination of white matter microstructure in-vivo. Initial DTI studies in schizophrenia demonstrated that white matter pathology is present in chronic patients compared to healthy volunteers, but left major unanswered questions regarding the specificity of anatomic pathology, especially early in the illness and prior to antipsychotic treatment. Moreover, little work to date has been directed at understanding the functional significance of these white matter deficits. Through the K01 mechanism the PI has completed preliminary studies demonstrating lower fractional anisotropy (FA) or higher trace in the middle frontal and superior temporal white matter, cingulum bundle and uncinate fasciculus in first-episode schizophrenia patients compared to healthy volunteers. Larger samples are required to confirm these initial findings, discern their neuropsychological and clinical correlates and to examine how they relate to brain volumetric measures comprising the frontotemporal system. Moreover, recent empirical and theoretical work suggests that a defect in the brain white matter may be a contributing factor to antipsychotic nonresponse in schizophrenia, but research in this area has been limited by the lack of controlled clinical trials from which to recruit patients and test hypotheses. We propose scanning a unique group of 60 antipsychotic drug-naive, first-episode schizophrenia patients to be enrolled in an NIMH- sponsored double-blind 12 week clinical trial of risperidone versus aripiprazole to be conducted under the aegis of our Advanced Center for Intervention and Services Research in Schizophrenia and 60 age- and sex-matched healthy volunteers. The specific aims of this study are to: (1) determine the regional specificity of white matter microstructural pathology in antipsychotic drug-naive first-episode patients with schizophrenia compared to healthy volunteers using DTI; (2) determine the functional correlates of abnormal white matter microstructure in patients compared to healthy volunteers; (3) examine the relationship between frontal lobe white matter microstructure and hippocampal volume in patients compared to healthy volunteers; (4) identify brain white matter regions that predict treatment response in antipsychotic drug-naive patients with first-episode schizophrenia. The identification of these abnormalities at the first episode of illness may be useful for identifying indicators of vulnerability, which may lead to improved early identification of individuals at risk for schizophrenia.
描述(由申请人提供):大量研究表明,精神分裂症的特征是额颞区的缺陷,越来越多的证据表明,这个整合系统的脑白质缺陷对现象学至关重要。扩散张量成像(DTI)可以用来量化水自扩散的方向性和一致性,从而可以在活体内检查脑白质的微结构。最初对精神分裂症的DTI研究表明,与健康志愿者相比,慢性患者中存在白质病理,但关于解剖病理的特殊性,特别是在疾病的早期和抗精神病药物治疗之前,仍有一些主要的悬而未决的问题。此外,到目前为止,很少有人针对这些白质缺陷的功能意义进行研究。通过K01机制,PI已经完成了初步研究,表明与健康志愿者相比,首发精神分裂症患者额叶中部和颞上白质、扣带束和钩束的分数各向异性(FA)较低或较高。需要更大的样本来证实这些初步发现,辨别它们的神经心理学和临床相关性,并检查它们与组成额颞部系统的脑体积测量的关系。此外,最近的经验和理论工作表明,脑白质缺陷可能是精神分裂症抗精神病药物无反应的一个促成因素,但这一领域的研究一直受到缺乏可供招募患者和检验假说的对照临床试验的限制。我们建议扫描一组独特的60名未服用抗精神病药物的首发精神分裂症患者,他们将参加由NIMH赞助的利培酮与阿立哌唑的12周双盲临床试验,该试验由我们的精神分裂症干预和服务研究高级中心和60名年龄和性别匹配的健康志愿者进行。本研究的具体目的是:(1)用DTI技术确定首发精神分裂症患者脑白质微结构病理的区域特异性;(2)与健康志愿者比较,确定患者脑白质微结构异常的功能相关性;(3)与健康志愿者比较,检测患者额叶白质微结构与海马体体积的关系;(4)找出预测抗精神病药物未用药的首发精神分裂症患者疗效的脑白质区域。在疾病的第一次发作时识别这些异常可能有助于识别脆弱性指标,这可能导致改进对精神分裂症风险个人的早期识别。

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)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

PHILIP R SZESZKO其他文献

PHILIP R SZESZKO的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('PHILIP R SZESZKO', 18)}}的其他基金

Predicting Suicidal Behavior in Veterans with Bipolar Disorder using Behavioral and Neuroimaging Based Impulsivity Phenotypes
使用基于行为和神经影像的冲动表型预测患有双相情感障碍的退伍军人的自杀行为
  • 批准号:
    10425238
  • 财政年份:
    2020
  • 资助金额:
    $ 29.88万
  • 项目类别:
Predicting Suicidal Behavior in Veterans with Bipolar Disorder using Behavioral and Neuroimaging Based Impulsivity Phenotypes
使用基于行为和神经影像的冲动表型预测患有双相情感障碍的退伍军人的自杀行为
  • 批准号:
    10704555
  • 财政年份:
    2020
  • 资助金额:
    $ 29.88万
  • 项目类别:
Predicting Suicidal Behavior in Veterans with Bipolar Disorder using Behavioral and Neuroimaging Based Impulsivity Phenotypes
使用基于行为和神经影像的冲动表型预测患有双相情感障碍的退伍军人的自杀行为
  • 批准号:
    9886839
  • 财政年份:
    2020
  • 资助金额:
    $ 29.88万
  • 项目类别:
Crossing White Matter Fibers as an Endophenotype in First-Episode Psychosis
穿越白质纤维作为首发精神病的内表型
  • 批准号:
    9169853
  • 财政年份:
    2016
  • 资助金额:
    $ 29.88万
  • 项目类别:
MR Imaging Predictors of Response & Outcome in First Episode Schizophrenia
MR 成像反应预测因子
  • 批准号:
    8065451
  • 财政年份:
    2010
  • 资助金额:
    $ 29.88万
  • 项目类别:
DIFFUSION TENSOR IMAGING IN FIRST EPISODE SCHIZOPHRENIA
首发精神分裂症的弥散张量成像
  • 批准号:
    8167222
  • 财政年份:
    2010
  • 资助金额:
    $ 29.88万
  • 项目类别:
GENETICS OF WHITE MATTER DEFICITS IN SCHIZOPHRENIA
精神分裂症白质缺陷的遗传学
  • 批准号:
    8167249
  • 财政年份:
    2010
  • 资助金额:
    $ 29.88万
  • 项目类别:
WHITE MATTER ENDOPHENOTYPES IN BIPOLAR DISORDER
双相情感障碍中的白质内表型
  • 批准号:
    8167288
  • 财政年份:
    2010
  • 资助金额:
    $ 29.88万
  • 项目类别:
MAPPING CORTICAL THICKNESS IN OBSESSIVE-COMPULSIVE DISORDER
绘制强迫症患者的皮质厚度图
  • 批准号:
    7955799
  • 财政年份:
    2009
  • 资助金额:
    $ 29.88万
  • 项目类别:
NEUROIMAGING STUDIES OF FRONTAL LOBE PATHOLOGY IN OCD
强迫症额叶病理学的神经影像学研究
  • 批准号:
    7955798
  • 财政年份:
    2009
  • 资助金额:
    $ 29.88万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 29.88万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了