Primary Research Project: Functional MRI

主要研究项目：功能性核磁共振成像

• 批准号: 7892511
• 负责人: Helen S Mayberg
• 金额: $ 23.26万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7892511
• 关键词: Acute myocardial infarction; Algorithms; American; Anterior; Antidepressive Agents; Base of the Brain; Behavioral; Biochemical; Biochemical Genetics; Brain; Brain Stem; Brodmann' s area; Caliber; Cardiac; Cardiology; Classification; Clinical; Clinical Management; Complex; Coronary artery; Corpus striatum structure; Data; Development; Diabetes Mellitus; Diagnosis; Diagnostic tests; Disease; Disease remission; Escitalopram; Evaluation; Family Physicians; Functional Magnetic Resonance Imaging; Genetic; Goals; Health Professional; Hippocampus (Brain); Hyperlipidemia; Hypertension; Hypothalamic structure; Image; Individual; Intervention; Lateral; Life Style; Magnetic Resonance Imaging; Major Depressive Disorder; Measurement; Measures; Medial; Medical; Mental Health; Methods; Modeling; Multivariate Analysis; Myocardial Ischemia; Organ; Outcome; Patients; Pattern; Pharmaceutical Preparations; Pharmacotherapy; Psychiatrist; Psychologist; Psychosocial Factor; Psychotherapy; Randomized; Recording of previous events; Research Project Grants; Rest; Risk Factors; Role; Scanning; Selection Bias; Selective Serotonin Reuptake Inhibitor; Smoking; Testing; Time; Training; Treatment outcome; base; clinical remission; cognitive behavior therapy; cohort; college; depressed; depression; diet and exercise; duloxetine; effective therapy; interest; research study; response; response marker; single episode major depressive disorder; standard care; tool; treatment response

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.

虽然有几种有效的治疗重度抑郁发作的方法， 缓解、应答或无应答可能性的可靠预测因子， 抗抑郁药物或心理治疗。在优先考虑直接措施的作用时， 脑功能在抑郁症临床管理新算法的发展 患者，预处理模式的系统表征预测明确的 缓解到标准治疗是必要的第一步。该项目将以成像为基础 大脑亚型，区分从未接受治疗的抑郁症患者群体， 随后分别对药物治疗或认知行为治疗（CBT）有反应。一 400名从未接受过治疗的抑郁症患者随机接受以下治疗： 依他普仑、度洛沙坦或CBT治疗1.2周将确定这些亚型。静止状态BOLD 在开始之前，将采集功能性磁共振成像（fMRI）扫描 抗抑郁药治疗，并在每个治疗特定的固定的早期时间点。预处理 使用多变量分析导出的扫描模式，并与六种可能的响应相关联 结果（3种类型的响应; 3种类型的无响应）将用于确定是否 治疗前的大脑模式可以区分结果组。第二次功能磁共振扫描， 在治疗过程的早期获得的，将用于评估反应的可能性 指定的具体治疗。这些研究是定义基于大脑的 亚型预测重性抑郁症的不同治疗结果这些数据 研究还将进入更复杂的算法，将成像结果与 行为、环境、生化和遗传信息。