A novel framework for quantifying metabolic brain health

量化大脑代谢健康的新框架

• 批准号: 10244835
• 负责人: Candace C. Fleischer
• 金额: $ 140.85万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10244835
• 关键词: Award; Biomedical Engineering; Chemistry; Clinical; Clinical/Radiologic; Data Collection; Development; Diagnosis; Disease; Disease Progression; Image; Immersion; Institutes; Left; Magnetic Resonance; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Medical Imaging; Metabolic; Metabolic Marker; Metabolic dysfunction; Metabolism; Methods; Mission; Modeling; Morphology; Onset of illness; Play; Prognosis; Research; Research Personnel; Resources; Role; United States National Institutes of Health; Vision; base; brain health; clinical decision-making; computerized tools; high risk; improved; injury recovery; innovation; metabolic imaging; non-invasive imaging; novel; novel strategies; personalized medicine; therapy resistant; treatment response

Project Summary An emerging theme in personalized medicine is the central role of metabolic dysfunction in disease and treatment response. As metabolic changes occur earlier than morphological changes, there are significant and untapped opportunities to incorporate metabolic markers into medical imaging. While medical imaging is an indispensable resource for the diagnosis and prognosis of disease, we do not have a way to reliably, repeatably, and non- invasively image metabolic abnormalities. Despite the mounting evidence that metabolism is involved in disease onset, treatment response and resistance, and prognosis, crucial metabolic information is left unexplored and uncharacterized. To facilitate a new paradigm in medical imaging and clinical decision making, I propose the development of a novel investigative approach termed “metaboloradiomics.” Metaboloradiomics will incorporate non-invasive metabolic imaging with conventional morphological imaging into a metabolism driven -omics model. By overcoming the existing challenges of clinical magnetic resonance spectroscopy data collection, analysis, and integration, combined with a suite of innovative computational tools, my vision is to enable an entirely new approach to magnetic resonance imaging that will enable researchers and clinicians to routinely characterize the role of metabolism in disease. The proposed research will facilitate a paradigm shift in magnetic resonance- based medical imaging and is ideally suited to the New Innovator Award mechanism. These methods will be applicable to a wide range of diseases, spanning the missions of multiple NIH Institutes and Centers. As a new investigator, my cross-disciplinary background in chemistry and biomedical engineering, combined with immersion in a clinical radiology department, has provided me with a unique skillset and specific expertise to execute this high-risk and high-impact research.

项目摘要 个性化医疗的一个新兴主题是代谢功能障碍在疾病和治疗中的核心作用 反应由于代谢变化发生早于形态变化， 将代谢标记物纳入医学成像的机会。虽然医学成像是不可或缺的 对于疾病的诊断和预后的资源，我们没有一种可靠的方法，可重复的，和非- 侵入性成像代谢异常。尽管越来越多的证据表明新陈代谢与疾病有关 发病、治疗反应和抗性以及预后，关键的代谢信息未被探索， 没有特征的为了促进医学成像和临床决策的新范式，我提出了 发展一种新的研究方法，称为“代谢放射组学”。代谢放射组学将结合 将非侵入性代谢成像与常规形态学成像结合到代谢驱动组学模型中。 通过克服临床磁共振波谱数据收集、分析的现有挑战， 和集成，结合一套创新的计算工具，我的愿景是实现一个全新的 磁共振成像的方法，使研究人员和临床医生能够定期表征 代谢在疾病中的作用。这项拟议中的研究将促进磁共振的范式转变- 基于医学成像，非常适合新创新奖机制。这些方法将 适用于广泛的疾病，跨越多个NIH研究所和中心的使命。作为一种新 调查员，我在化学和生物医学工程的跨学科背景，结合 沉浸在临床放射科，为我提供了独特的技能和具体的专业知识， 执行这项高风险和高影响力的研究。

项目成果

Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging.

• DOI: 10.1021/cbmi.3c00019
• 发表时间: 2023-05-22
• 期刊: Chemical & biomedical imaging
• 作者: Wu, Tianhe;Liu, Claire;Thamizhchelvan, Anbu Mozhi;Fleischer, Candace;Peng, Xingui;Liu, Guanshu;Mao, Hui
• 通讯作者: Mao, Hui