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Texture Features of Magnetic Resonance Images: A Marker of Slight Cognitive Deficits in Parkinson's Disease
Author(s) -
Betrouni Nacim,
Lopes Renaud,
Defebvre Luc,
Leentjens Albert F. G.,
Dujardin Kathy
Publication year - 2020
Publication title -
movement disorders
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.352
H-Index - 198
eISSN - 1531-8257
pISSN - 0885-3185
DOI - 10.1002/mds.27931
Subject(s) - caudate nucleus , putamen , psychology , neuropsychology , thalamus , cognition , magnetic resonance imaging , atrophy , audiology , parkinson's disease , dementia , functional magnetic resonance imaging , hippocampus , effects of sleep deprivation on cognitive performance , disease , neuroscience , medicine , radiology
Background Cognitive impairment is a frequent nonmotor symptom of Parkinson's disease. Depending on severity, patients are considered to have mild cognitive impairment or dementia. However, among the cognitively intact patients, some may have deficits in a less severe range. The early detection of such subtle symptoms may be important for the initiation of care strategies. Objective To identify imaging markers of early cognitive symptoms, potentially before usual signs, such as atrophy, become manifest. Methods A total of 102 patients with Parkinson's disease and 17 age‐matched cognitively intact healthy controls underwent extensive neuropsychological assessment and T1‐weighted magnetic resonance imaging. Parkinson's disease patients were separated into 3 groups according to their cognitive status: intact, with slight slowing, and with mild deficits in executive functions. Texture features as measured by first‐order and second‐order statistics were computed in the following 6 brain regions: the hippocampus, thalamus, amygdala, putamen, caudate nucleus, and pallidum. They were tested between the groups, and their correlation with cognition was examined. Volumetric measurements were made for comparison. Results Texture analysis showed significant between‐group differences for 2 features—skewness and entropy in the hippocampus, the thalamus, and the amygdala—and the volume analysis revealed no between‐group difference. These features were significantly correlated with cognitive performance. Conclusion These results support the assumption that signal alterations associated with Parkinson's disease–related cognitive decline can be captured very early by texture analysis. As these changes appear to reflect clinical phenomena, texture analysis may be a promising marker for helping cognitive phenotyping in Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society