PDF(Pubmed)
Abstract：
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that severely impacts affected persons\' speech and motor functions, yet early detection and tracking of disease progression remain challenging. The current gold standard for monitoring ALS progression, the ALS functional rating scale - revised (ALSFRS-R), is based on subjective ratings of symptom severity, and may not capture subtle but clinically meaningful changes due to a lack of granularity. Multimodal speech measures which can be automatically collected from patients in a remote fashion allow us to bridge this gap because they are continuous-valued and therefore, potentially more granular at capturing disease progression. Here we investigate the responsiveness and sensitivity of multimodal speech measures in persons with ALS (pALS) collected via a remote patient monitoring platform in an effort to quantify how long it takes to detect a clinically-meaningful change associated with disease progression. We recorded audio and video from 278 participants and automatically extracted multimodal speech biomarkers (acoustic, orofacial, linguistic) from the data. We find that the timing alignment of pALS speech relative to a canonical elicitation of the same prompt and the number of words used to describe a picture are the most responsive measures at detecting such change in both pALS with bulbar (n = 36) and non-bulbar onset (n = 107). Interestingly, the responsiveness of these measures is stable even at small sample sizes. We further found that certain speech measures are sensitive enough to track bulbar decline even when there is no patient-reported clinical change, i.e. the ALSFRS-R speech score remains unchanged at 3 out of a total possible score of 4. The findings of this study have the potential to facilitate improved, accelerated and cost-effective clinical trials and care.
摘要：
肌萎缩侧索硬化症（ALS）是一种进行性神经退行性疾病，严重影响受影响的人的言语和运动功能，然而早期发现和追踪疾病进展仍然具有挑战性.当前监测ALS进展的黄金标准，ALS功能评定量表-修订(ALSFRS-R)，基于症状严重程度的主观评分，由于缺乏粒度，可能无法捕获细微但有临床意义的变化。可以远程自动从患者那里收集的多模态语音测量使我们能够弥合这一差距，因为它们具有连续的价值，因此，在捕捉疾病进展方面可能更有颗粒。在这里，我们研究了通过远程患者监测平台收集的ALS（pALS）患者的多模态语音测量的响应性和敏感性，以量化检测与疾病进展相关的临床意义变化所需的时间。我们记录了278名参与者的音频和视频，并自动提取了多模态语音生物标志物(声学，口面,语言)来自数据。我们发现，pALS语音相对于同一提示的规范启发的时间对齐以及用于描述图片的单词数量是检测到pALS在延髓（n=36）和非延髓发作（n=107）中的这种变化的最敏感措施。有趣的是,这些措施的反应是稳定的，即使在小样本量。我们进一步发现，即使没有患者报告的临床变化，某些语音测量也足以跟踪延髓下降。即,ALSFRS-R语音得分在总可能得分4中的3处保持不变。这项研究的结果有可能促进改进，加速和具有成本效益的临床试验和护理。
