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

描述（由申请人提供）：肌萎缩性侧索硬化症（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差异很大，但该疾病的结果一致是致命的，中位生存时间在2 - 4年之间。在美国大约有3万人患有渐冻症。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，以及症状进展史。LMN的病理评估可以通过肌电图来补充，但UMN的病理可能仍然是隐蔽的，因为它只能通过临床检查来评估，这可能导致诊断的不确定性。不幸的是，对于这种迅速发展的疾病，从出现症状到诊断平均有一年的延迟；这种延迟妨碍了新出现的疾病缓解药物的早期治疗。因此，需要可靠的生物标志物进行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记物一直并将继续受到极大的兴趣。尽管先进的神经成像技术，如磁共振波谱（MRS）、弥散张量成像（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，无法可靠地对个体患者进行分类。为了满足这一重要的未被满足的需求，本研究将使用新颖的先进神经影像学技术来开发ALS的多模态生物标志物，并验证一种识别和预测模型，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.