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    Positron emission tomography (PET) amyloid imaging has become an important part of the diagnostic workup for patients with primary progressive aphasia (PPA) and uncertain underlying pathology. Here, we employ a semi-automated analysis of connected speech (CS) with a twofold objective. First, to determine if quantitative CS features can help select primary progressive aphasia (PPA) patients with a higher probability of a positive PET amyloid imaging result. Second, to examine the relevant group differences from a clinical perspective. 117 CS samples from a well-characterised cohort of PPA patients who underwent PET amyloid imaging were collected. Expert consensus established PET amyloid status for each patient, and 40% of the sample was amyloid positive. Leave-one-out cross-validation yields 77% classification accuracy (sensitivity: 74%, specificity: 79%). Our results confirm the potential of CS analysis as a screening tool. Discriminant CS features from lexical, syntactic, pragmatic, and semantic domains are discussed. Copyright © 2021 Elsevier Ltd. All rights reserved.

    Citation

    Antoine Slegers, Geneviève Chafouleas, Maxime Montembeault, Christophe Bedetti, Ariane E Welch, Gil D Rabinovici, Philippe Langlais, Maria L Gorno-Tempini, Simona M Brambati. Connected speech markers of amyloid burden in primary progressive aphasia. Cortex; a journal devoted to the study of the nervous system and behavior. 2021 Dec;145:160-168

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    PMID: 34731686

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