fMRI Resting State Networks in Chronic Pain

慢性疼痛中的功能磁共振成像静息态网络

• 批准号: 7905701
• 负责人: DANTE R CHIALVO
• 金额: $ 27.57万
• 依托单位: BRENTWOOD BIOMEDICAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7905701
• 关键词: Anxiety; Area; Brain; Brain imaging; Brain region; Chronic low back pain; Complement; Control Groups; Data; Decision Making; Dependence; Depressed mood; Diagnosis; Disease; Eating; Emotional; Exhibits; Female; Functional Magnetic Resonance Imaging; Functional disorder; Gender; Health; Healthcare; Hormonal; Human; Knowledge; Label; Lead; Linear Models; Location; Low Back Pain; Memory; Mental Depression; Mental Processes; Methods; Modeling; Molecular Conformation; Nature; Pain; Patients; Pattern; Plastics; Prevalence; Reporting; Rest; Sex Characteristics; Sleeplessness; Structure; Techniques; Testing; Thinking; Validation; Work; base; chronic pain; immune function; independent component analysis; novel; public health relevance; sex; spontaneous pain; therapy outcome; tool

DESCRIPTION (provided by applicant): Chronic pain remains a primary reason for people seeking health care, which, if untreated, can lead to depression, insomnia, depressed immune function, changes in eating patterns, and other long-term deleterious effects. Chronic pain patients have a fluctuating but persistent spontaneous pain percept and therefore their brain, compared with healthy subjects, is never truly at rest. The overall objective of this project is to identify the nature and long-term consequences of the burden imposed by this unrest condition on the well being of the brain. This objective is greatly facilitated by recent fMRI results in healthy subjects which have identified the subset of cortical areas active during idle or passive mental processes engaged in the so called "Resting State Networks" (RSN). Aim I is to identify the brain regions comprising the RSNs in chronic low back pain patients as compared with those in healthy subjects. Aim II will determine the functional interactions between the components of each RSN in patients and normal subjects to better understand the basic cortical mechanisms at work in chronic pain. Finally Aim III will determine gender differences and hormonal dependence in the organization of these Resting State Networks, both in health and disease. FMRI data will be collected from healthy subjects and pain patients and analyzed with multivariate techniques such as Probabilistic Independent Component Analysis, which as shown in our preliminary results is able to unambiguously identify the major components involved in the RSN. The validation of the composition of each resting state and chronic pain networks will be conducted by hypothesis-driven General Linear Model bivariate analysis based on the current understanding of the cortical involvement in chronic pain. Since the identification of the spatio-temporal components of resting state network in chronic pain patients equals to a precise knowledge of "where the pain is in the brain", its successful uncovering will dramatically change our understanding of the brain areas responsible for chronic pain. This knowledge should impact both the experimental approach in the study of pain using fMRI, and the diagnosis and therapy outcome of this invalidating disease. PUBLIC HEALTH RELEVANCE There is accumulated evidence indicating that chronic pain if untreated, can lead to depression, insomnia, depressed immune function, changes in eating patterns, and other long- term deleterious effects. Chronic pain patients have a fluctuating but persistent spontaneous pain percept and therefore their brain, compared with healthy subjects, is never truly at rest. The project will isolate the components of the brain network subserving the resting state in chronic pain patients such us to identify the effect of the burden imposed by this unrest condition on the long term well being of the brain. This precise knowledge of "where the pain is in the brain", will dramatically change our understanding of the brain areas responsible for chronic pain, impacting both the experimental approaches in the study of pain using fMRI, and the diagnosis and therapy outcome of this invalidating disease.

描述（由申请人提供）：慢性疼痛仍然是人们寻求医疗保健的主要原因，如果不治疗，可能会导致抑郁、失眠、免疫功能低下、饮食模式改变以及其他长期有害影响。慢性疼痛患者的自发疼痛感知波动但持续，因此与健康受试者相比，他们的大脑从未真正休息过。该项目的总体目标是确定这种不稳定状况对大脑健康造成的负担的性质和长期后果。最近在健康受试者中的功能磁共振成像结果极大地促进了这一目标，这些结果已经确定了在参与所谓的“静息状态网络”（RSN）的闲置或被动心理过程期间活跃的皮质区域的子集。目标 I 是确定慢性腰痛患者与健康受试者中包含 RSN 的大脑区域。目标 II 将确定患者和正常受试者中每个 RSN 组成部分之间的功能相互作用，以更好地了解慢性疼痛中起作用的基本皮质机制。最后，目标 III 将确定这些静息状态网络组织中健康和疾病方面的性别差异和荷尔蒙依赖性。 FMRI 数据将从健康受试者和疼痛患者中收集，并使用概率独立成分分析等多变量技术进行分析，如我们的初步结果所示，该技术能够明确识别 RSN 中涉及的主要成分。每个静息状态和慢性疼痛网络的组成的验证将通过基于当前对慢性疼痛皮质参与的理解的假设驱动的一般线性模型双变量分析来进行。由于识别慢性疼痛患者静息状态网络的时空成分相当于精确了解“疼痛在大脑中的位置”，它的成功揭示将极大地改变我们对导致慢性疼痛的大脑区域的理解。这些知识应该会影响使用功能磁共振成像研究疼痛的实验方法，以及这种无效疾病的诊断和治疗结果。公共健康相关性 积累的证据表明，慢性疼痛如果不加以治疗，可能导致抑郁、失眠、免疫功能低下、饮食模式改变以及其他长期有害影响。慢性疼痛患者的自发疼痛感知波动但持续，因此与健康受试者相比，他们的大脑从未真正休息过。该项目将隔离有助于慢性疼痛患者静息状态的大脑网络组件，以确定这种不稳定状态所造成的负担对大脑长期健康的影响。这种对“疼痛在大脑中的位置”的精确了解，将极大地改变我们对导致慢性疼痛的大脑区域的理解，影响使用功能磁共振成像研究疼痛的实验方法，以及这种致残疾病的诊断和治疗结果。