Abstract

Neuroimaging studies have described the brain alterations in primary progressive aphasia (PPA) variants (semantic, logopenic, nonfluent/agrammatic). However, few studies combined T1, FDG-PET, and diffusion MRI techniques to study atrophy, hypometabolism, and tract alterations across the three PPA main variants. We therefore explored a large early-stage cohort of semantic, logopenic and nonfluent/agrammatic variants (N = 86) and of 23 matched healthy controls with anatomical MRI (cortical thickness), FDG PET (metabolism) and diffusion MRI (white matter tracts analyses), aiming at identifying cortical and sub-cortical brain alterations, and confronting these alterations across imaging modalities and aphasia variants. In the semantic variant, there was cortical thinning and hypometabolism in anterior temporal cortices, with left-hemisphere predominance, extending toward posterior temporal regions, and affecting tracts projecting to the anterior temporal lobes (inferior longitudinal fasciculus, uncinate fasciculus) and tracts projecting to or running nearby posterior temporal cortices: (superior longitudinal fasciculus, inferior frontal-occipital fasciculus). In the logopenic variant metabolic alterations were more extensive than atrophy affecting mainly the left temporal-parietal junction and extending toward more anterior temporal cortices. Metabolic and tract data were coherent given the alterations of the left superior and inferior longitudinal fasciculus and the left inferior frontal-occipital fasciculus. In the nonfluent/agrammatic variant cortical thinning and hypometabolism were located in the left frontal cortex but Broca's area was only affected on metabolic measures. Metabolic and tract alterations were coherent as reflected by damage to the left uncinate fasciculus connecting with Broca's area. Our findings provide a full-blown statistically robust picture of brain alterations in early-stage variants of primary progressive aphasia which has implications for diagnosis, classification and future therapeutic strategies. They demonstrate that in logopenic and semantic variants patterns of brain damage display a non-negligible overlap in temporal regions whereas they are substantially distinct in the nonfluent/agrammatic variant (frontal regions). These results also indicate that frontal networks (combinatorial syntax/phonology) and temporal networks (lexical/semantic representations) constitute distinct anatomo-functional entities with differential vulnerability to degenerative processes in aphasia variants. Finally, the identification of the specific damage patterns could open an avenue for trans-cranial stimulation approaches by indicating the appropriate target-entry into the damaged language system.

Highlights

  • Primary Progressive Aphasia (PPA) is a group of neurodegenerative diseases affecting language abilities

  • Lv-PPA patients showed alterations in the left temporal-parietal junction and left inferior, middle, and superior temporal regions extending toward anterior temporal cortices

  • We found alterations in tracts connecting or passing close to posterior temporal regions: the left superior longitudinal fasciculus (SLF) for Fractional Anisotropy (FA) and the left inferior frontal-occipital fasciculus (IFOF) for FA

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Summary

INTRODUCTION

Primary Progressive Aphasia (PPA) is a group of neurodegenerative diseases affecting language abilities. Lv-PPA is associated with cortical atrophy of the left temporo-parietal junction [3] extending in some studies to more anterior temporal regions [10,11,12,13]. Despite the growing body of literature on brain damage in PPA only few studies combined MRI-T1, FDG-PET and MRIdiffusion-weighted-imaging to assess atrophy patterns, metabolic profiles and tract alterations in the three PPA variants. The present investigation addressed these issues studying structural (cortical thickness), microstructural (tract parameters) and metabolic alterations in a large population of early-stage patients of the three PPA variants using structural MRI, diffusion-weighted imaging (DWI) and FDG-PET imaging, while applying a rigorously corrected statistical approach

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