Primary Research Project: Functional MRI
主要研究项目:功能性核磁共振成像
基本信息
- 批准号:7645104
- 负责人:
- 金额:$ 23.28万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2008
- 资助国家:美国
- 起止时间:2008-07-01 至 2011-06-30
- 项目状态:已结题
- 来源:
- 关键词:Acute myocardial infarctionAlgorithmsAmericanAnteriorAntidepressive AgentsBase of the BrainBehavioralBiochemical GeneticsBrainBrain StemBrodmann&aposs areaCaliberCardiacCardiologyClassificationClinicalClinical ManagementCognitive TherapyComplexConditionCoronary arteryCorpus striatum structureDataDepressed moodDevelopmentDiabetes MellitusDiagnosisDiagnostic testsDiseaseDisease remissionEscitalopramEvaluationFamily PhysiciansFunctional Magnetic Resonance ImagingGeneticGoalsHealth ProfessionalHippocampus (Brain)HyperlipidemiaHypertensionHypothalamic structureImageIndividualInterventionLateralLife StyleMagnetic Resonance ImagingMajor Depressive DisorderMeasurementMeasuresMedialMedicalMental DepressionMental HealthMethodsModelingMultivariate AnalysisMyocardial IschemiaOrganOutcomePatientsPatternPharmaceutical PreparationsPharmacotherapyPsychiatristPsychologistPsychosocial FactorPsychotherapyRandomizedRecording of previous eventsResearch Project GrantsRestRisk FactorsRoleScanningSelection BiasSelective Serotonin Reuptake InhibitorSmokingStandards of Weights and MeasuresTestingTimeTrainingTreatment outcomeWeekbasecohortcollegediet and exerciseduloxetineinterestresearch studyresponsesingle episode major depressive disordertool
项目摘要
Although there are several effective treatments for a major depressive episode, there are no
reliable predictors of the likelihood of remission, response or non-response with an initial trial of
either an antidepressant medication or psychotherapy. In prioritizing a role for direct measures of
brain functioning in the development of new algorithms for clinical management of depressed
patients, a systematic characterization of pretreatment patterns predictive of unambiguous
remission to standard treatments is a necessary first step. This project will characterize imagingbased
brain subtypes that distinguish groups of never-treated depressed patients who
subsequently respond to pharmacotherapy or cognitive behavior therapy (CBT), respectively. A
prospectively-treated cohort of 400 never-treated depressed patients randomized to receive either
escitalopram, duloxetine or CBT for 1.2 weeks will define these subtypes. Resting-state BOLD
functional magnetic resonance imaging (fMRI) scans will be acquired prior to initiating
antidepressant therapy and at a fixed, early time point specific for each treatment. Pre-treatment
scan patterns derived using multivariate analyses and associated with the six possible response
outcomes (3 types of response; 3 types of nonresponse) will be used to determine whether
pretreatment brain patterns can distinguish among outcome groups. A second fMRI scan,
acquired early in the treatment course, will be used to assess the likelihood of response to the
specific treatment assigned. The proposed studies are a first step towards defining brain-based
subtypes predictive of differential treatment outcome in major depression. The data from these
studies will also be entered into more complex algorithms integrating imaging findings with
behavioral, environmental, biochemical and genetic information for individual patients.
尽管对重大抑郁症发作有几种有效的治疗方法,但没有
可靠预测缓解,反应或无响应的可能性,并初步试验
抗抑郁药或心理治疗。在优先级的角色来直接衡量
大脑在开发新算法的临床管理方面的功能
患者,一种预处理的预处理模式的系统表征
缓解标准治疗是必要的第一步。该项目将表征基于成像的
大脑亚型区分从未治疗过的抑郁症患者组
随后,分别对药物治疗或认知行为疗法(CBT)做出反应。一个
前瞻性治疗的队列由400名从未治疗过的抑郁症患者随机接受
依依西更,杜洛西汀或CBT 1.2周将定义这些亚型。静止状态大胆
在启动之前将获得功能磁共振成像(fMRI)扫描
抗抑郁药治疗,在每种治疗方面的固定早期时间点。预处理
使用多元分析得出的扫描模式并与六个可能的响应相关联
结果(3种响应的3种类型; 3种无响应类型)将用于确定是否是否
预处理大脑模式可以区分结果组。第二次fMRI扫描,
在治疗课程的早期获得,将用于评估对响应的可能性
分配的具体处理。拟议的研究是定义基于大脑的第一步
亚型可预测严重抑郁症的差异治疗结果。这些数据
研究还将进入更复杂的算法,将成像发现与
个人患者的行为,环境,生化和遗传信息。
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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Helen S Mayberg其他文献
Posttraumatic Stress Disorder: A State-of-the-Science Review
创伤后应激障碍:最新科学回顾
- DOI:
10.1176/foc.7.2.foc254 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Charles B. Nemeroff;J. Bremner;Edna B Foa;Helen S Mayberg;Carol S. North;Murray B. Stein - 通讯作者:
Murray B. Stein
Support Vector Machine Classification of Resting State fMRI Datasets Using Dynamic Network Clusters
使用动态网络集群对静息态 fMRI 数据集进行支持向量机分类
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Hyo Yul Byun;Helen S Mayberg - 通讯作者:
Helen S Mayberg
The capacity of brain circuits to enhance psychiatry.
大脑回路增强精神病学的能力。
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
B. Dunlop;Helen S Mayberg - 通讯作者:
Helen S Mayberg
Helen S Mayberg的其他文献
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{{ truncateString('Helen S Mayberg', 18)}}的其他基金
Establishing the anatomical and functional mechanisms of white matter deep brain stimulation
建立白质深部脑刺激的解剖和功能机制
- 批准号:
10803745 - 财政年份:2023
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10604638 - 财政年份:2022
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10647096 - 财政年份:2022
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10310774 - 财政年份:2021
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
9929246 - 财政年份:2019
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
9869948 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10768061 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10545620 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10547822 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
Electrophysiological Biomarkers to Optimize DBS for Depression
电生理生物标志物优化 DBS 治疗抑郁症
- 批准号:
10767494 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
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