Abstract

Objective To evaluate automated digital speech measures, derived from spontaneous speech (picture descriptions), in assessing bulbar motor impairments in patients with ALS-FTD spectrum disorders (ALS-FTSD). Methods Automated vowel algorithms were employed to extract two vowel acoustic measures: vowel space area (VSA), and mean second formant slope (F2 slope). Vowel measures were compared between ALS with and without clinical bulbar symptoms (ALS + bulbar (n = 49, ALSFRS-r bulbar subscore: x¯ = 9.8 (SD = 1.7)) vs. ALS-nonbulbar (n = 23), behavioral variant frontotemporal dementia (bvFTD, n = 25) without a motor syndrome, and healthy controls (HC, n = 32). Correlations with bulbar motor clinical scales, perceived listener effort, and MRI cortical thickness of the orobuccal primary motor cortex (oral PMC) were examined. We compared vowel measures to speaking rate, a conventional metric for assessing bulbar dysfunction. Results ALS + bulbar had significantly reduced VSA and F2 slope than ALS-nonbulbar (|d|=0.94 and |d|=1.04, respectively), bvFTD (|d|=0.89 and |d|=1.47), and HC (|d|=0.73 and |d|=0.99). These reductions correlated with worse bulbar clinical scores (VSA: R = 0.33, p = 0.043; F2 slope: R = 0.38, p = 0.011), greater listener effort (VSA: R=-0.43, p = 0.041; F2 slope: p > 0.05), and cortical thinning in oral PMC (F2 slope: β = 0.0026, p = 0.017). Vowel measures demonstrated greater sensitivity and specificity for bulbar impairment than speaking rate, while showing independence from cognitive and respiratory impairments. Conclusion Automatic vowel measures are easily derived from a brief spontaneous speech sample, are sensitive to mild-moderate stage of bulbar disease in ALS-FTSD, and may present better sensitivity to bulbar impairment compared to traditional assessments such as speaking rate.

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