Penn Frontotemporal Degeneration Center Department of Neurology University of Pennsylvania Philadelphia Pennsylvania.
Linguistic Data Consortium Department of Linguistics University of Pennsylvania Philadelphia Pennsylvania.
Ann Clin Transl Neurol. 2018 Nov 24;6(1):4-14. doi: 10.1002/acn3.653. eCollection 2019 Jan.
To automatically extract and quantify specific disease biomarkers of prosody from the acoustic properties of speech in patients with primary progressive aphasia.
We analyzed speech samples from 59 progressive aphasic patients (non-fluent/agrammatic = 15, semantic = 21, logopenic = 23; ages 50-85 years) and 31 matched healthy controls (ages 54-89 years). Using a novel, automated speech analysis protocol, we extracted acoustic measurements of prosody, including fundamental frequency and speech and silent pause durations, and compared these between groups. We then examined their relationships with clinical tests, gray matter atrophy, and cerebrospinal fluid analytes.
We found a narrowed range of fundamental frequency in patients with non-fluent/agrammatic variant aphasia (mean 3.86 ± 1.15 semitones) compared with healthy controls (6.06 ± 1.95 semitones; < 0.001) and patients with semantic variant aphasia (6.12 ± 1.77 semitones; = 0.001). Mean pause rate was significantly increased in the non-fluent/agrammatic group (mean 61.4 ± 20.8 pauses per minute) and the logopenic group (58.7 ± 16.4 pauses per minute) compared to controls. In an exploratory analysis, narrowed fundamental frequency range was associated with atrophy in the left inferior frontal cortex. Cerebrospinal level of phosphorylated tau was associated with an acoustic classifier combining fundamental frequency range and pause rate ( = 0.58, = 0.007). Receiver operating characteristic analysis with this combined classifier distinguished non-fluent/agrammatic speakers from healthy controls (AUC = 0.94) and from semantic variant patients (AUC = 0.86).
Restricted fundamental frequency range and increased pause rate are characteristic markers of speech in non-fluent/agrammatic primary progressive aphasia. These can be extracted with automated speech analysis and are associated with left inferior frontal atrophy and cerebrospinal phosphorylated tau level.
从原发性进行性失语症患者的语音声学特征中自动提取和量化特定的疾病生物标志物。
我们分析了 59 名进行性失语症患者（非流利/语法障碍型=15 名，语义型=21 名，失语法型=23 名；年龄 50-85 岁）和 31 名匹配的健康对照者（年龄 54-89 岁）的语音样本。使用一种新颖的自动化语音分析方案，我们提取了语音韵律的声学测量值，包括基频和言语及无声停顿时长，并比较了组间差异。然后，我们检查了它们与临床测试、灰质萎缩和脑脊液分析物之间的关系。
我们发现非流利/语法障碍型失语症患者的基频范围较健康对照组（6.06±1.95 半音； ＜0.001）和语义型失语症患者（6.12±1.77 半音； ＝0.001）变窄。非流利/语法障碍组（平均 61.4±20.8 个停顿/分钟）和失语法组（58.7±16.4 个停顿/分钟）的平均停顿率明显升高。在一项探索性分析中，基频范围变窄与左侧额下回皮质萎缩有关。脑脊液磷酸化 tau 水平与结合基频范围和停顿率的声学分类器相关（ ＝0.58， ＝0.007）。使用该组合分类器的接收者操作特征分析可将非流利/语法障碍型患者与健康对照组（AUC=0.94）和语义型患者（AUC=0.86）区分开来。
受限的基频范围和增加的停顿率是非流利/语法障碍型原发性进行性失语症患者语音的特征性标志物。这些可通过自动化语音分析提取，与左侧额下回萎缩和脑脊液磷酸化 tau 水平相关。
