TY - JOUR
T1 - Data-Driven, Visual Framework for the Characterization of Aphasias Across Stroke, Post-resective, and Neurodegenerative Disorders Over Time
AU - Fan, Joline M.
AU - Gorno-Tempini, Maria Luisa
AU - Dronkers, Nina F.
AU - Miller, Bruce L.
AU - Berger, Mitchel S.
AU - Chang, Edward F.
N1 - Funding Information:
Funding. Research reported in this publication was supported by Grants from the National Institute of Health under the Award Numbers (NCATS 5TL1TR001871-05 to JF; NIDCD R01DC016345 to ND; NINDS R01NS050915, NIDCD K24DC015544, NIH UTA17-000879, NIA P01AG019724, NINDS R01 NS100440, NIA R01AG058233, and NIA U01AG052943 to MG-T; R01-DC012379, R00-NS065120, and DP2-OD00862 to EC). The content was solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. In addition, this study was supported by Alzheimer's Disease Research Center of California (03-75271 DHS/ADP/ARCC); Larry L. Hillblom Foundation; John Douglas French Alzheimer's Foundation; Koret Family Foundation; Consortium for Frontotemporal Dementia Research; McBean Family Foundation; and Esther A. and Joseph Klingenstein Fund. We thank the patients and their families for the time and effort they dedicated to the research.
Publisher Copyright:
© Copyright © 2020 Fan, Gorno-Tempini, Dronkers, Miller, Berger and Chang.
PY - 2020/12/29
Y1 - 2020/12/29
N2 - 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.
AB - 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.
KW - aphasia
KW - primary progressive aphasia
KW - principal component analyses
KW - stroke
KW - trajectories
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UR - http://www.scopus.com/inward/citedby.url?scp=85099292465&partnerID=8YFLogxK
U2 - 10.3389/fneur.2020.616764
DO - 10.3389/fneur.2020.616764
M3 - Article
AN - SCOPUS:85099292465
VL - 11
JO - Frontiers in Neurology
JF - Frontiers in Neurology
SN - 1664-2295
M1 - 616764
ER -