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.
Highlights
Aphasias are acquired language disorders that are caused by injury to language areas of the brain
The aphasia quotient (AQ) is a weighted average of Western Aphasia Battery (WAB) subscores and represents aphasia severity [26]
principal component analysis (PCA) was performed on the aggregated data in Table 1 to arrive at a common basis representing the most salient aphasia features across three disease etiologies
Summary
Aphasias are acquired language disorders that are caused by injury to language areas of the brain. While each of these conditions can lead to dysfunction of language processing, an outstanding question is how the behavioral symptoms of these conditions relate to one another. The understanding of language networks has predominantly been developed from stroke and neurodegenerative cases, which have largely been studied independently [1,2,3]. Given the unique language profile and selective vulnerability of specific language networks in neurodegenerative disorders, a separate clinical classification scheme has been developed for PPA [7,8,9]. Transient aphasias have been found to occur in over 70% of patients undergoing left hemisphere peri-sylvian resection [13,14,15], offering yet another approach for studying language dysfunction
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