Development of a Multi-Modal Neuroimaging Biomarker for Amyotrophic Lateral Scler

描述（由申请人提供）：肌萎缩侧索硬化症（ALS）是一种进行性退行性运动神经元疾病，累及运动皮质、胼胝体、皮质脊髓束和脊髓前角神经元。尽管临床表现和病程相当不均匀，但该疾病具有一致的致死性结局，中位生存时间为2 - 4年。在美国，大约有30，000人患有ALS。ALS没有明确的诊断测试。可靠的诊断主要基于临床评估，并依赖于检测多个身体部位的上运动神经元（UMN）和下运动神经元（LMN）体征，以及症状进展史。LMN病理的评估可以通过肌电图进行补充，但UMN病理可能仍然是隐匿性的，因为它只能使用临床检查进行评估，这可能导致诊断的不确定性。不幸的是，对于这种快速进展的疾病，在症状发作和诊断之间平均有一年的延迟;这种延迟阻止了用新兴的疾病修饰药物的早期治疗。因此，需要可靠的生物标志物用于早期诊断和疾病诊断。 常规磁共振成像技术在ALS患者中提供有限且不一致的信息。因此，人们一直并将继续对使用先进的神经影像学技术来建立改进的疾病标志物产生极大的兴趣。虽然先进的神经成像技术，如磁共振波谱（MRS），扩散张量成像（DTI）和静息状态功能连接（fcMRI）已经确定了ALS患者和健康对照之间的差异，但它们缺乏足够的准确性来可靠地对个体患者进行分类。为了满足这一重要的未满足的需求，拟议的研究将使用新的先进神经影像学技术来开发ALS的多模式生物标志物，并验证鉴别和预测模型，以完善ALS的诊断临床检查。

DESCRIPTION (provided by applicant): Amyotrophic lateral sclerosis (ALS) is a progressive degenerative motor neuron disease involving the motor cortex, corpus callosum, cortical spinal tract and spinal anterior horn neurons. The disease has a uniformly fatal outcome, although the clinical presentation and course is quite heterogeneous, with median survival times between 2 - 4 years. Approximately 30,000 people in the United States are living with ALS. There is no definitive diagnostic test for ALS. Confident diagnosis is primarily based on clinical assessment and relies on the detection of upper motor neuron (UMN) and lower motor neuron (LMN) signs in multiple body segments, together with a history of progression of symptoms. Evaluation of LMN pathology may be supplemented by electromyography, but UMN pathology can remain occult as it is only assessed using clinical examination which can lead to diagnostic uncertainty. Unfortunately, there is on average a one- year delay between the onset of symptoms and diagnosis for this rapidly progressive disease; this delay prevents early treatment with emerging disease-modifying drugs. Thus, reliable biomarkers for the early diagnosis and disease prognostication are needed. Conventional magnetic resonance imaging techniques provide limited and inconsistent information in ALS patients. Therefore, there has been and continues to be great interest in using advanced neuroimaging techniques to establish improved markers of the disease. Although advanced neuroimaging techniques such as magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and resting state functional connectivity (fcMRI) have identified differences between ALS patients and healthy controls, they lack sufficient accuracy to reliably classify individual patients. To meet this important unmet need, the proposed study will use novel advanced neuroimaging techniques to develop a multimodal biomarker of ALS, and validate a discrimination and prediction model to refine the diagnostic clinical workup for ALS.