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

描述(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病，累及运动皮层、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同，中位生存期在2-4年之间，但该病的结局都是致命的。美国约有3万人患有肌萎缩侧索硬化症。目前还没有针对肌萎缩侧索硬化症的明确诊断测试。确凿的诊断主要基于临床评估，依赖于多个身体节段的上运动神经元(UMN)和下运动神经元(LMN)体征的检测，以及症状的进展史。对LMN病理的评估可以通过肌电检查来补充，但UMN的病理可能仍然是隐秘的，因为它只通过临床检查进行评估，这可能导致诊断的不确定性。不幸的是，这种快速发展的疾病在出现症状和诊断之间平均有一年的延迟；这种延迟阻止了使用新出现的疾病修改药物进行早期治疗。因此，需要可靠的生物标志物用于早期诊断和疾病预测。常规磁共振成像技术在ALS患者中提供的信息有限且不一致。因此，使用先进的神经成像技术来建立改进的疾病标志物一直并将继续引起人们的极大兴趣。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患者和健康对照组之间的差异，但它们缺乏足够的准确性来可靠地对单个患者进行分类。为了满足这一重要的未得到满足的需求，拟议的研究将使用新的先进神经成像技术来开发ALS的多模式生物标记物，并验证判别和预测模型以完善ALS的诊断临床工作。

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.