Longitudinal brain atrophy distribution in advanced Parkinson's disease: What makes the difference in "cognitive status" converters?
Martin GorgesMartin S KunzHans-Peter MüllerInga Liepelt-ScarfoneAlexander StorchRichard DodelRüdiger Hilker-Roggendorfnull nullDaniela BergElke KalbeHeiko BraakKelly Del TrediciSimon BaudrexelHans-Jürgen HuppertzJan KassubekPublished in: Human brain mapping (2019)
We investigated the brain atrophy distribution pattern and rate of regional atrophy change in Parkinson's disease (PD) in association with the cognitive status to identify the morphological characteristics of conversion to mild cognitive impairment (MCI) and dementia (PDD). T1-weighted longitudinal 3T MRI data (up to four follow-up assessments) from neuropsychologically well-characterized advanced PD patients (n = 172, 8.9 years disease duration) and healthy elderly controls (n = 85) enrolled in the LANDSCAPE study were longitudinally analyzed using a linear mixed effect model and atlas-based volumetry and cortical thickness measures. At baseline, PD patients presented with cerebral atrophy and cortical thinning including striatum, temporoparietal regions, and primary/premotor cortex. The atrophy was already observed in "cognitively normal" PD patients (PD-N) and was considerably more pronounced in cognitively impaired PD patients. Linear mixed effect modeling revealed almost similar rates of atrophy change in PD and controls. The group comparison at baseline between those PD-N whose cognitive performance remained stable (n = 42) and those PD-N patients who converted to MCI/PDD ("converter" cPD-N, n = 26) indicated suggested cortical thinning in the anterior cingulate cortex in cPD-N patients which was correlated with cognitive performance. Our results suggest that cortical brain atrophy has been already expanded in advanced PD patients without overt cognitive deficits while atrophy progression in late disease did not differ from "normal" aging regardless of the cognitive status. It appears that cortical atrophy begins early and progresses already in the initial disease stages emphasizing the need for therapeutic interventions already at disease onset.
Keyphrases
- mild cognitive impairment
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- prognostic factors
- cognitive decline
- functional connectivity
- resting state
- physical activity
- computed tomography
- artificial intelligence
- deep learning
- brain injury
- blood brain barrier
- big data
- subarachnoid hemorrhage
- contrast enhanced