Literature DB >> 33447252

Data-Driven, Visual Framework for the Characterization of Aphasias Across Stroke, Post-resective, and Neurodegenerative Disorders Over Time.

Joline M Fan1, Maria Luisa Gorno-Tempini1, Nina F Dronkers2,3, Bruce L Miller1, Mitchel S Berger4, Edward F Chang4.   

Abstract

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.
Copyright © 2020 Fan, Gorno-Tempini, Dronkers, Miller, Berger and Chang.

Entities:  

Keywords:  aphasia; primary progressive aphasia; principal component analyses; stroke; trajectories

Year:  2020        PMID: 33447252      PMCID: PMC7801263          DOI: 10.3389/fneur.2020.616764

Source DB:  PubMed          Journal:  Front Neurol        ISSN: 1664-2295            Impact factor:   4.003


  45 in total

1.  Anatomical correlates of early mutism in progressive nonfluent aphasia.

Authors:  M L Gorno-Tempini; J M Ogar; S M Brambati; P Wang; J H Jeong; K P Rankin; N F Dronkers; B L Miller
Journal:  Neurology       Date:  2006-08-23       Impact factor: 9.910

2.  Is it time to revisit the classification guidelines for primary progressive aphasia?

Authors:  M-Marsel Mesulam; Sandra Weintraub
Journal:  Neurology       Date:  2014-03-05       Impact factor: 9.910

3.  The aphasia quotient: the taxonomic approach to measurement of aphasic disability.

Authors:  A Kertesz; E Poole
Journal:  Can J Neurol Sci       Date:  1974-02       Impact factor: 2.104

4.  Anterior temporal laterality in primary progressive aphasia shifts to the right.

Authors:  Mathieu Vandenbulcke; Ronald Peeters; Paul Van Hecke; Rik Vandenberghe
Journal:  Ann Neurol       Date:  2005-09       Impact factor: 10.422

5.  Quantitative template for subtyping primary progressive aphasia.

Authors:  Marsel Mesulam; Christina Wieneke; Emily Rogalski; Derin Cobia; Cynthia Thompson; Sandra Weintraub
Journal:  Arch Neurol       Date:  2009-12

6.  Connected speech in transient aphasias after left hemisphere resective surgery.

Authors:  Angelica McCarron; Ashley Chavez; Miranda Babiak; Mitchel S Berger; Edward F Chang; Stephen M Wilson
Journal:  Aphasiology       Date:  2017-01-17       Impact factor: 2.773

7.  Altered topology of the functional speech production network in non-fluent/agrammatic variant of PPA.

Authors:  Maria Luisa Mandelli; Ariane E Welch; Eduard Vilaplana; Christa Watson; Giovanni Battistella; Jesse A Brown; Katherine L Possin; Honey I Hubbard; Zachary A Miller; Maya L Henry; Gabe A Marx; Miguel A Santos-Santos; Lynn P Bajorek; Juan Fortea; Adam Boxer; Gil Rabinovici; Suzee Lee; Jessica Deleon; Howard J Rosen; Bruce L Miller; William W Seeley; Maria Luisa Gorno-Tempini
Journal:  Cortex       Date:  2018-08-11       Impact factor: 4.027

8.  Semantic impairment in stroke aphasia versus semantic dementia: a case-series comparison.

Authors:  Elizabeth Jefferies; Matthew A Lambon Ralph
Journal:  Brain       Date:  2006-06-30       Impact factor: 13.501

9.  Using principal component analysis to capture individual differences within a unified neuropsychological model of chronic post-stroke aphasia: Revealing the unique neural correlates of speech fluency, phonology and semantics.

Authors:  Ajay D Halai; Anna M Woollams; Matthew A Lambon Ralph
Journal:  Cortex       Date:  2016-04-29       Impact factor: 4.027

10.  Predicting Early Post-stroke Aphasia Outcome From Initial Aphasia Severity.

Authors:  Alberto Osa García; Simona Maria Brambati; Amélie Brisebois; Marianne Désilets-Barnabé; Bérengère Houzé; Christophe Bedetti; Elizabeth Rochon; Carol Leonard; Alex Desautels; Karine Marcotte
Journal:  Front Neurol       Date:  2020-02-21       Impact factor: 4.003

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