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Multiparametric Classification of Muscle Damage in Inflammatory Myopathy

Multiparametric Classification of Muscle Damage in Inflammatory Myopathy
炎症性肌病肌肉损伤的多参数分类
批准号:
7741024
负责人:
BRUCE M. DAMON
金额:
$34.88万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-05 至 2014-06-30

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中文摘要
翻译
描述(由申请人提供):特发性炎症性肌病(IIM),包括皮肌炎(DM)、多发性肌炎(PM)和包体体肌炎(IBM),是导致肌肉炎症、无力和疼痛的自身免疫性疾病。通常进行实验室和成像(MRI)研究,但并不总是与疾病严重程度良好相关;患者管理必须基于主观临床表现。因此,本研究的总体目标是发展和阐明一系列MRI检查的病理基础,这些检查将客观定量地跟踪IIM的特定方面。这些测试将包括典型的结构图像;肌内脂肪定量Dixon成像;利用弥散张量MRI评估肌肉质量和结构;用短tau反转恢复法评估炎症;动态增强MRI灌注定量;使用血氧水平依赖的MRI和31P磁共振光谱来评估运动期间的代谢。在Aim 1中,这些测试将应用于越来越复杂的IIM小鼠模型。首先,我们将研究1)对照C57/Bl6小鼠;2)小鼠过表达水通道蛋白-4,增加膜通透性;3)小鼠注射λ -卡拉胶致水肿;4)两种情况。然后,随着时间的推移,我们将用转基因诱导的PM形式研究治疗和未治疗的小鼠。先进的多维图像分析方法将用于将所有或部分MRI结果与肌肉损伤的定量组织学测量相关联。在目标2中,MRI测试将应用于1)遭受控制肌肉损伤的人类和2)DM, PM和IBM患者以及年龄和性别匹配的对照受试者。将采用多维影像分析方法,将影像结果与病人自我报告的疾病严重程度和临床表现联系起来。总之,我们期望这些研究将为IIM的肌肉结构和功能的定量表征提供新的工具和方法。这些工具将有助于改善个体患者的临床管理,并在群体研究中对拟议治疗的反应进行表征。此外,这些研究将为更广泛地评估神经肌肉疾病的肌肉功能提供新的工具。公共卫生相关性:肌肉炎症性疾病引起疼痛、肿胀、无力和生活质量下降。然而,典型的临床试验并不总是与疾病的严重程度相对应。在这项研究中,我们希望开发基于非侵入性成像方法的新工具,使临床医生能够以更具体和定量的方式描述炎症性肌肉疾病带来的肌肉损伤。
英文摘要
DESCRIPTION (provided by applicant): The idiopathic inflammatory myopathies (IIM), including dermatomyositis (DM), polymyositis (PM), and inclusion body myositis (IBM), are autoimmune diseases resulting in muscle inflammation, weakness, and pain. Laboratory and imaging (MRI) studies are typically performed, but are not always well correlated with disease severity; patient management must be based on subjective clinical findings. Therefore, the overall objective of this study is to develop and elucidate the pathological basis of a battery of MRI tests that will objectively and quantitatively track specific aspects of IIM. These tests will include typical structural images; intramuscular adipose quantification using Dixon imaging; assessment of muscle quality and architecture using diffusion-tensor MRI; assessment of inflammation using short-tau inversion recovery; quantification of perfusion using dynamic-contrast enhanced MRI; metabolic assessments during exercise using blood oxygenation-level dependent MRI and 31P MR spectroscopy. In Aim 1, these tests will be applied to increasingly complex mouse models of IIM. First, we will study 1) control C57/Bl6 mice; 2) mice overexpressing aquaporin-4, to increase membrane permeability; 3) mice injected with lambda-carageenan, to cause edema; and 4) both conditions. Then, we will study treated and untreated mice with a transgenically induced form of PM, over time. Advanced, multi-dimensional image analysis approaches will be used to correlate all of or a subset of the MRI findings with quantitative histological measures of muscle damage. In Aim 2, the MRI tests will be applied to 1) humans undergoing controlled muscle damage and 2) DM, PM, and IBM patients and age- and gender- matched control subjects. Multidimensional image analysis approaches will be employed in order to correlate imaging findings with patient self-report of disease severity and clinical findings. Overall, we expect that these studies will provide new tools and approaches for quantitative characterization of muscle structure and function in IIM. These tools will allow for improved clinical management of individual patients and allow for characterization of responses to proposed treatments in group studies. Moreover, these studies will provide new tools for assessing muscle function i neuromuscular disorders more generally. PUBLIC HEALTH RELEVANCE: Inflammatory diseases of muscle cause pain, swelling, weakness, and reduced quality of life. Typical clinical tests do not always correspond to disease severity, however. In this study, we would like to develop new tools, based on non-invasive imaging methods, that will allow clinicians to describe muscle damage brought about inflammatory muscle disease in a more specific and quantitative fashion.
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Development and Application of Muscle Diffusion Tensor MRI
  • 批准号:
    10400490
  • 项目类别:
  • 资助金额:
    $38.89万
  • 财政年份:
    2019
  • 负责人:
    BRUCE M. DAMON
  • 依托单位:
Development and Application of Muscle Diffusion Tensor MRI
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