RT Journal Article
T1 Identification of the main components of spontaneous speech in primary progressive aphasia and their neural underpinnings using multimodal MRI and FDG-PET imaging
A1 Matias-Guiu, Jordi A.
A1 Suárez-Coalla, Paz
A1 Yus, Miguel
A1 Pytel, Vanesa
A1 Hernández Lorenzo, Laura
A1 Delgado-Alonso, Cristina
A1 Delgado Álvarez, Alfonso
A1 Gómez-Ruiz, Natividad
A1 Polidura, Carmen
A1 Cabrera Martín, María Nieves
A1 Matías-Guiu Guía, Jorge
A1 Cuetos, Fernando
AB Background: Primary progressive aphasia (PPA) is a clinical syndrome characterized by gradual loss of language skills. This study aimed to evaluate the diagnostic capacity of a connected speech task for the diagnosis of PPA and its variants, to determine the main components of spontaneous speech, and to examine their neural correlates. Methods: A total of 118 participants (31 patients with nfvPPA, 11 with svPPA, 45 with lvPPA, and 31 healthy controls) were evaluated with the Cookie Theft picture description task and a comprehensive language assessment protocol. Patients also underwent 18F-fluorodeoxyglucose positron emission tomography and magnetic resonance imaging studies. Principal component analysis and machine learning were used to evaluate the main components of connected speech and the accuracy of connected speech parameters for diagnosing PPA. Voxel-based analyses were conducted to evaluate the correlation between spontaneous speech components and brain metabolism, brain volumes, and white matter microstructure. Results: Discrimination between patients with PPA and controls was 91.67%, with 77.78% discrimination between PPA variants. Parameters related to speech rate and lexical variables were the most discriminative for classification. Three main components were identified: lexical features, fluency, and syntax. The lexical component was associated with ventrolateral frontal regions, while the fluency component was associated with the medial superior prefrontal cortex. Number of pauses was more related with the left parietotemporal region, while pauses duration with the bilateral frontal lobe. The lexical component was correlated with several tracts in the language network (left frontal aslant tract, left superior longitudinal fasciculus I, II, and III, left arcuate fasciculus, and left uncinate fasciculus), and fluency was linked to the frontal aslant tract. Conclusion: Spontaneous speech assessment is a useful, brief approach for the diagnosis of PPA andits variants. Neuroimaging correlates suggested a subspecialization within the left frontal lobe, with ventrolateral regions being more associated with lexical production and the medial superior prefrontal cortex with speech rate.
PB Elsevier
SN 0010-9452
YR 2022
FD 2022-01
LK https://hdl.handle.net/20.500.14352/103992
UL https://hdl.handle.net/20.500.14352/103992
LA eng
NO Instituto de Salud Carlos III
NO European Commission
DS Docta Complutense
RD 19 dic 2025