Relaxivity Contrast Imaging as Biomarker of Muscle Degeneration in ALS

弛豫对比成像作为 ALS 肌肉退化的生物标志物

基本信息

批准号：
10783525
负责人：
Christopher Chad Quarles
金额：
$ 68.65万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-03-01 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10783525
关键词：
ALS patients Age Amyotrophic Lateral Sclerosis Antisense Oligonucleotide Therapy Architecture Atypia Biological Biological Markers Cessation of life Characteristics Clinical Clinical Markers Clinical Trials Data Analyses Diameter Disease Disease Marker Disease Progression Edema Exhibits Fatty acid glycerol esters Fiber Foundations Functional Imaging Functional disorder Goals Health Hospitals Human Image Magnetic Resonance Imaging Measures Methods Motor Cortex Motor Neurons Muscle Muscular Atrophy Nerve Degeneration Neurologic Neuromuscular Diseases Pathologic Patient Care Patient-Centered Care Patients Performance Pharmacodynamics Phase II/III Clinical Trial Process Protocols documentation Quality Control Readiness Reproducibility Research Respiratory physiology Rodent Model Sample Size Spinal Therapeutic Intervention Upper Extremity Validation Vertebral column biomarker discovery biophysical properties clinical heterogeneity computer framework contrast imaging cost effective data acquisition density design drug development drug discovery early detection biomarkers imaging approach imaging biomarker improved innovation multidisciplinary muscle degeneration muscle strength nervous system disorder neuroimaging next generation non-invasive imaging novel pre-clinical rate of change research clinical testing response response biomarker sex structural imaging superoxide dismutase 1 treatment effect treatment response

项目摘要

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.

抽象的肌萎缩侧索硬化症 (ALS) 的特点是脊髓和皮质运动神经元丧失，导致进行性肌肉萎缩，最终导致死亡。临床异质性和快速 ALS 的进展继续困扰着治疗反应生物标志物的识别。目前，临床试验（和实践）被迫依赖疾病状态的下游指标例如肌肉力量、呼吸功能和功能评定量表。此类措施虽然经验证，有一定的局限性。首先，它们具有显着的评估者间差异。其次，措施的变化速度通常相对较慢，因此需要数月甚至数年的时间才能检测治疗效果。这些挑战凸显了对敏感、可重复和可重复性的需求尚未得到满足。治疗反应的非侵入性生物标志物。为了克服这些限制，我们建议开发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特别敏感（例如减少的纤维直径和密度，纤维 ALS 患者表现出的异型性。我们假设 RCI 可以作为药效/反应生物标志物，用于显示治疗的功效和生物反应旨在减缓或逆转神经退行性变的药物的 2/3 期临床试验中的干预措施 ALS 患者。为了开发 RCI，我们将使用经过验证的计算框架来系统地在肌肉退化和治疗反应的背景下描述 RCI 的生物物理基础并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 的生物标志物与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来检测对治疗的反应。在人类中，我们将描述性能特征和可重复性健康对照和 ALS 患者的 RCI 方案。为进一步细化RCI，我们将建立质量 RCI 数据采集和分析的控制措施以及年龄和性别依赖性特征健康对照中基于 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，并与其他晚期患者进行比较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 拥有作为早期治疗的定量、肌纤维特异性、基于图像的生物标志物的潜力对 ALS 的响应，可能会实现更小的样本量、更早的 Go/No Go 决策、更高的成本有效的临床试验，并最终改善患者护理。