Integrating Multimodal Brain Imaging Data to Assess Subtle Cognitive Impairment

整合多模态脑成像数据来评估细微的认知障碍

• 批准号: 8229843
• 负责人: Jeffrey S Spence
• 金额: $ 17.31万
• 依托单位: UT SOUTHWESTERN MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8229843
• 关键词: Adjuvant Therapy; Affect; Age; Biological Markers; Brain; Brain imaging; Brain region; Cerebrovascular Circulation; Classification; Clinical; Clinical Management; Clinical Treatment; Cognition; Data; Databases; Degenerative Disorder; Detection; Development; Diagnosis; Diffusion Magnetic Resonance Imaging; Disease; Electroencephalography; Functional Imaging; Functional Magnetic Resonance Imaging; Functional disorder; Future; Goals; Health; Human; Image; Impaired cognition; Impairment; Individual; Injury; Ions; Lead; Linear Models; Machine Learning; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Methodology; Methods; Modality; Modeling; Neurocognitive; Neurotoxins; Outcome; Output; Pathologic Processes; Pathology; Patients; Procedures; Process; Property; Reliance; Research Personnel; Resolution; Sampling; Secondary to; Semantic memory; Sensory Process; Short-Term Memory; Signal Transduction; Source; Spin Labels; Staging; Statistical Methods; Symptoms; Techniques; Technology; Testing; Time; Toxin; Weight; Work; base; behavior measurement; behavior test; cancer therapy; case-based; chemobrain; chemotherapy; data reduction; executive function; image registration; imaging modality; improved; independent component analysis; innovation; insight; mild neurocognitive impairment; neurocognitive test; neuroimaging; neurophysiology; novel; prevent; research study; single photon emission computed tomography; tool; treatment strategy

DESCRIPTION (provided by applicant): Functional neuroimaging studies of the human brain have become increasingly important in the understanding of normal and pathological processes of cognition. Sophisticated statistical analytic frameworks have been developed to locate signal change and define brain networks involved in various tasks. However, in subtle cognitive impairment-e.g., exposure-related illness, early stages of degenerative diseases, injury, secondary illness following adjuvant therapy for cancer-these methods tend to have low sensitivity for detecting small changes in brain states resulting from mild brain dysfunction. An understanding of disease mechanism or progression of subtle cognitive dysfunction requires a novel statistical analytic framework with improved sensitivity to measure small changes in brain states. We have developed an innovative methodology that we successfully applied in measures of regional cerebral blood flow experiments. These methods use well established spatial modeling procedures, new to the functional brain imaging field, to derive statistically optimal spatial summaries within effective resolution groups or "kriging", shown by preliminary studies to improve signal detection sensitivity and mitigate the multiple testing burden. Within this new spatial modeling framework, we propose to extend the kriging methodology to fMRI and EEG, modify existing techniques for characterizing brain networks of connectivity (e.g., kriging-based independent components analysis), and integrate the imaging modalities using a statistical classifier based on derived inputs of data driven effective resolution groups. Our primary goal is to develop this analysis framework to provide insight into the neurophysiological mechanisms of mild cognitive dysfunction. Achieving this goal may suggest treatments to alleviate symptoms, prevent progression, or at minimum, provide an informed clinical management of cognitively impaired patients. PUBLIC HEALTH RELEVANCE: Cognitive impairment is a major health concern, affecting people of all ages. Causes range from traumatic injury to toxin exposures, including chemotherapy for cancer treatment, to degenerative diseases. Mechanisms of damage or disease remain difficult to establish using current methods in functional brain imaging studies due to an inability to measure very small changes in brain states. We propose a new analytic framework using existing technology to improve the ability to measure subtle changes important in the understanding of disease pathology of impaired cognition and to greatly facilitate the integration of information from several imaging modalities with potential implications for clinical management and treatment.

描述(由申请人提供)：人脑的功能神经成像研究在理解认知的正常和病理过程中变得越来越重要。已经开发了复杂的统计分析框架来定位信号变化并定义涉及各种任务的大脑网络。然而，对于轻微的认知障碍--例如，与暴露相关的疾病、退行性疾病的早期阶段、损伤、癌症辅助治疗后的继发性疾病--这些方法往往对检测由轻度脑功能障碍引起的大脑状态的微小变化的敏感性较低。要理解细微认知功能障碍的疾病机制或进展，需要一个新的统计分析框架，具有更高的灵敏度，以衡量大脑状态的微小变化。我们开发了一种创新的方法，并成功地应用于局部脑血流实验的测量。这些方法使用功能脑成像领域新出现的成熟的空间建模程序，在有效分辨率组或“克里格法”内得出统计上最优的空间摘要，初步研究表明，这些方法可以提高信号检测灵敏度并减轻多次测试负担。在这个新的空间建模框架内，我们建议将克里金方法扩展到fMRI和EEG，修改现有的表征脑网络连接的技术(例如，基于克里金的独立分量分析)，并使用基于数据驱动的有效分辨率组的派生输入的统计分类器来集成成像模式。我们的主要目标是开发这个分析框架，为轻度认知功能障碍的神经生理学机制提供洞察力。实现这一目标可能建议进行治疗，以缓解症状，防止进展，或至少为认知受损患者提供知情的临床管理。 公共卫生相关性：认知障碍是一个主要的健康问题，影响到所有年龄段的人。原因从创伤到毒素暴露(包括癌症治疗的化疗)，再到退行性疾病。由于无法测量大脑状态的微小变化，使用目前的脑功能成像研究方法仍然很难建立损伤或疾病的机制。我们提出了一种新的分析框架，利用现有的技术来提高测量细微变化的能力，这些细微变化对于理解认知受损的疾病病理很重要，并极大地促进了来自几种成像模式的信息的集成，这些信息具有潜在的临床管理和治疗意义。