Relaxivity Contrast Imaging as Biomarker of Muscle Degeneration in ALS

摘要 肌萎缩性侧索硬化症（ALS）的特征在于脊髓和皮质运动神经元的丧失， 导致肌肉萎缩最终死亡临床异质性和快速 ALS的进展继续混淆治疗反应生物标志物的鉴定。 目前，临床试验（和实践）被迫依赖于疾病状态的下游指标 例如肌肉力量、呼吸功能和功能评级量表。这些措施虽然 经过验证，有一些限制。首先，他们有显著的评分者间差异。二是 衡量标准的变化速度通常相对较慢，因此需要数月甚至数年的时间来 检测治疗效果。这些挑战强调了对敏感的、可再现的、 治疗反应的非侵入性生物标志物。为了克服这些限制，我们建议制定一个 非侵入性成像方法，称为弛豫对比成像（RCI）。与现有的基于图像的 反映病理生理学下游变化的生物标志物（例如T2 -水肿、脂肪分数），RCI是 对肌纤维结构特征（例如，减小的纤维直径和密度，纤维 ALS患者的症状。我们假设RCI可以作为 药效学/反应生物标志物，以显示治疗的疗效和生物学反应 在旨在减缓或逆转神经退行性变的药物的2/3期临床试验中， ALS患者为了开发RCI，我们将使用经过验证的计算框架， 在肌肉变性和治疗反应的背景下表征RCI的生物物理基础 并使用它来确定在临床试验中应用RCI的最佳采集和分析策略。在 ALS的临床前啮齿动物模型，我们将验证基于RCI的生物标志物和 肌肉结构的病理标志物，并建立基于RCI的生物标志物的实用性，以检测 对治疗的反应。在人类中，我们将描述性能特征和重复性， 健康对照和ALS患者的RCI方案。为了进一步完善RCI，我们将建立质量 RCI数据采集和分析的控制措施，并描述年龄和性别依赖性 健康对照中基于RCI的生物标志物的参考区间。最后，我们将建立灵敏度 基于RCI的生物标志物对ALS患者疾病进展的影响，并与其他晚期 基于图像的生物标志物和疾病状态的常规临床标志物。最终，RCI拥有 作为一种定量的、肌纤维特异性的、基于图像的生物标志物， ALS的响应，可能实现更小的样本量，更早的Go/No Go决策，更多的成本- 有效的临床试验，并最终改善患者护理。

ABSTRACT Amyotrophic Lateral Sclerosis (ALS) is characterized by loss of spinal and cortical motor neurons, resulting in progressive muscle atrophy and eventually, death. The clinical heterogeneity and rapid progression of ALS continues to confound the identification of treatment response biomarkers. Currently, clinical trials (and practice) are forced to rely upon downstream indicators of disease status such as muscle strength, respiratory function and functional rating scales. Such measures, although validated, have a number of limitations. First, they have significant inter-rater variability. Second, the measures usually have relatively slow rates of change and thus, require months and even years to detect a treatment effect. These challenges underscore the unmet need for sensitive, reproducible, and non-invasive biomarkers of therapy response. To overcome these limitations, we propose to develop a non-invasive imaging approach, termed relaxivity contrast imaging (RCI). Unlike existing image-based biomarkers that reflect downstream changes in pathophysiology (e.g. T2 - edema, fat fraction), RCI is uniquely sensitive to myofiber architectural features (e.g. reduced fiber diameter and density, fiber atypia) exhibited by ALS patients. We hypothesize that RCI could serve as a pharmacodynamic/response biomarker to show efficacy of and biological response to therapeutic interventions in Phase 2/3 clinical trials of agents designed to slow or reverse neurodegeneration in ALS patients. To develop RCI, we will use a validated computational framework to systematically characterize the biophysical basis of RCI in the context of muscle degeneration and treatment response and use it to identify optimal acquisition and analysis strategies for applying RCI in a clinical trial. In preclinical rodent models of ALS, we will verify the association between RCI-based biomarkers and pathologic markers of muscle architecture and establish the utility of RCI-based biomarkers to detect response to therapy. In humans, we will characterize performance characteristics and repeatability of RCI protocols in healthy controls and ALS patients. To further refine RCI, we will establish quality control measures for RCI data acquisition and analysis and characterize age- and sex- dependent reference intervals of RCI-based biomarkers in healthy controls. Finally, we will establish the sensitivity of RCI-based biomarkers to disease progression in ALS patients and compare to other advanced image-based biomarkers and routine clinical markers of disease status. Ultimately, RCI has the potential to serve as a quantitative, myofiber-specific, image-based biomarker of early therapeutic response for ALS, potentially enabling smaller sample sizes, earlier Go/No Go decisions, more cost- effective clinical trials and, ultimately, improved patient care.