Automated Detection of Speech Timing Alterations in Autopsy-Confirmed Nonfluent/Agrammatic Variant Primary Progressive Aphasia

被引:16
|
作者
Garcia, Adolfo M. [1 ,2 ,3 ,4 ]
Welch, Ariane E. [5 ]
Luisa Mandelli, Maria [5 ]
Henry, Maya L. [6 ]
Lukic, Sladjana [5 ,7 ]
Torres Prioris, Maria Jose [8 ,9 ,10 ,11 ]
Deleon, Jessica [5 ]
Ratnasiri, Buddhika M. [5 ]
Lorca-Puls, Diego L. [5 ,12 ]
Miller, Bruce L. [5 ]
Seeley, William [5 ]
Vogel, Adam P. [13 ,14 ]
Luisa Gorno-Tempini, Maria [5 ]
机构
[1] Univ Calif San Francisco, Global Brain Hlth Inst, San Francisco, CA 94143 USA
[2] Univ San Andres, Cognit Neurosci Ctr, Buenos Aires, DF, Argentina
[3] Natl Sci & Tech Res Coundl CONICET, Buenos Aires, DF, Argentina
[4] Univ Santiago Chile, Fac Humanidades, Dept Lingaist & Literatura, Santiago, Spain
[5] Univ Calif San Francisco, Dept Neurol, Memory & Aging Ctr, San Francisco, CA 94118 USA
[6] Univ Texas Austin, Dept Commun Sci & Disorders, Austin, TX 78712 USA
[7] Adelphi Univ, Dept Commun Sci & Disorders, Garden City, NY USA
[8] Univ Malaga, Cognit Neurol & Aphasia Unit, Malaga, Spain
[9] Univ Malaga, Ctr Invest Med Sanitarias, Malaga, Spain
[10] Inst Invest Biomed Malaga IBIMA, Malaga, Spain
[11] Univ Malaga, Fac Psychol & Speech Therapy, Area Psychobiol, Malaga, Spain
[12] Univ Concepcion, Fac Med, Dept Especialidades, Secc Neurol, Concepcion, Chile
[13] Univ Melbourne, Dept Audiol & Speech Pathol, Ctr Neurosci Speech, Melbourne, Vic, Australia
[14] Redenlab, Melbourne, Vic, Australia
关键词
SUPRANUCLEAR PALSY; NONFLUENT APHASIA; PATHOLOGY; APRAXIA; DEMENTIA;
D O I
10.1212/WNL.0000000000200750
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background and Objectives Motor speech function, including speech timing, is a key domain for diagnosing nonfluent/agrammatic variant primary progressive aphasia (nfvPPA). Yet, standard assessments use subjective, specialist-dependent evaluations, undermining reliability and scalability. Moreover, few studies have examined relevant anatomo-clinical alterations in patients with pathologically confirmed diagnoses. This study overcomes such caveats using automated speech timing analyses in a unique cohort of autopsy-proven cases. Methods In a cross-sectional study, we administered an overt reading task and quantified articulation rate, mean syllable and pause duration, and syllable and pause duration variability. Neuroanatomical disruptions were assessed using cortical thickness and white matter (WM) atrophy analysis. Results We evaluated 22 persons with nfvPPA (mean age: 67.3 years; 13 female patients) and confirmed underlying 4-repeat tauopathy, 15 persons with semantic variant primary progressive aphasia (svPPA; mean age: 66.5 years; 8 female patients), and 10 healthy controls (HCs; 70 years; 5 female patients). All 5 speech timing measures revealed alterations in persons with nfvPPA relative to both the HC and svPPA groups, controlling for dementia severity. The articulation rate robustly discriminated individuals with nfvPPA from HCs (area under the ROC curve [AUC] = 0.95), outperforming specialist-dependent perceptual measures of dysarthria and apraxia of speech severity. Patients with nfvPPA exhibited structural abnormalities in left precentral and middle frontal as well as bilateral superior frontal regions, including their underlying WM. The articulation rate correlated with atrophy of the left pars opercularis and supplementary/presupplementary motor areas. Secondary analyses showed that, controlling for dementia severity, all measures yielded greater deficits in patients with nfvPPA and corticobasal degeneration (nfvPPA-CBD, n = 12) than in those with progressive supranuclear palsy pathology (nfvPPA-PSP, n = 10). The articulation rate robustly discriminated between individuals in each subgroup (AUC = 0.82). More widespread cortical thinning was observed for the nfvPPA-CBD than the nfvPPA-PSP group across frontal regions. Discussion Automated speech timing analyses can capture specific markers of nfvPPA while potentially discriminating between patients with different tauopathies. Thanks to its objectivity and scalability; this approach could support standard speech assessments. Classification of Evidence This study provides Class III evidence that automated speech analysis can accurately differentiate patients with nonfluent PPA from normal controls and patients with semantic variant PPA.
引用
收藏
页码:E500 / E511
页数:12
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