Validated automatic speech biomarkers in primary progressive aphasia

Abstract

ObjectiveTo automatically extract and quantify specific disease biomarkers of prosody from the acoustic properties of speech in patients with primary progressive aphasia.MethodsWe 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.ResultsWe 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; P < 0.001) and patients with semantic variant aphasia (6.12 ± 1.77 semitones; P = 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 (r = 0.58, P = 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).InterpretationRestricted 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.

Primary Progressive Aphasia: Toward a Pathophysiological Synthesis

“…Identification and stratification into clinical trials at the very earliest stage of disease will be vital if treatments are to be effective. The use of ecologically relevant measures that quantify aspects of speech output have garnered recent interest in terms of both diagnosis and disease tracking from early stages [30][31][32][33], leading to the suggestion that automated analysis of speech might be used as a 'verbal thermometer' for PPA and FTD [34]. There is also considerable interest in the use of 'wet biomarkers' in measuring disease burden and intensity.…”

Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations

“…Other forms of clinical validation of speech-based measures include measuring disease severity and tracking changes over time as a measure of disease progression, prognosis, or the response to treatment. Various studies have shown how speech measures relate to disease severity by demonstrating associations between speech features and the presence of pathology in primary progressive aphasia [56] as well as between clinician-rated symptoms and speech features in depression and schizophrenia [57][58][59]. Several longitudinal case studies suggest that speech features may have prognostic validity for predicting the onset of Alzheimer's disease and show changes in years prior to the diagnosis [60][61][62][63][64][65].…”

Automated analysis of lexical features in Frontotemporal Degeneration

“…Patients with svPPA, also known as semantic dementia, are characterized by semantic impairment and difficulties in confrontation naming and lexical retrieval (Amici et al, 2007;Hodges & Patterson, 2007). Previous studies reveal that svPPA patients have difficulty in processing words denoting concrete objects (Bonner, Price, Peelle, & Grossman, 2016;Bonner et al, 2009;Breedin, Saffran, & Coslett, 1994;Cousins, York, Bauer, & Grossman, 2016;Cousins, Ash, Irwin, & Grossman, 2017;Macoir, 2009), but their prosody and syntax are less disrupted (Adlam, Bozeat, Arnold, Watson, & Hodges, 2006, Ash et al 2006Ash et al, 2009;Nevler, Ash, Irwin, Liberman, & Grossman, 2019;Thompson & Mack, 2014). It has also been observed that svPPA patients' lexical retrieval is related to word familiarity and frequency (Bird et al, 2000;Hodges & Patterson, 2007;Rogers, Patterson, Jefferies, & Lambon Ralph, 2015).…”