scholarly journals Predicting Future Cognitive Impairment in De Novo Parkinson's Disease Using Clinical Data and Structural MRI

2021 ◽  
Author(s):  
Nicola Smith ◽  
Owen A Williams ◽  
Lucia Ricciardi ◽  
Francesca Morgante ◽  
Thomas R Barrick ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Grey Matter ◽  
Temporal Cortex ◽  
Cognitive Status ◽  
Support Vector ◽  
Parkinson’S Disease Dementia ◽  
Lingual Gyrus

BACKGROUND Parkinson's disease is the second most common neurodegenerative condition and associated with increasing cognitive dysfunction as the disease progresses. However, subtle cognitive deficits can be detected at diagnosis in 42% of individuals, suggesting that damage may already be present. Our aim was to determine clinical and structural differences in those recently diagnosed with PD who later develop cognitive impairment, and whether these changes predict future cognitive decline. METHODS Clinical and imaging data was acquired from the Parkinson's Progression Markers Initiative for 318 individuals with a diagnosis of Parkinson's disease and baseline 3T T1-weighted MRI. The cohort was divided according to cognitive status over follow-up, with 9 individuals developing Parkinson's disease dementia, 102 developing mild cognitive impairment and 207 remaining cognitively unaffected. FINDINGS At baseline, those who went on to develop cognitive impairment (mild cognitive impairment or dementia) were older with more severe motor and non-motor symptoms (anosmia, rapid eye movement sleep behaviour disorder, depression). Grey matter loss was present in those destined for Parkinson's disease dementia in the precuneus, hippocampi, primary olfactory cortex, lingual gyrus, temporal cortex and cerebellum. Those who later developed mild cognitive impairment had an attenuated but similar pattern of grey matter loss in the temporal lobe, lingual gyrus and cerebellum. Using support vector machines with a feature selection step, future cognitive impairment could be predicted using 11 clinical variables (AUC = 0.81), structural imaging (AUC = 0.72) or a combination of these two modalities (AUC = 0.85). These models more accurately predicted those who developed dementia (subgroup sensitivity 100%). INTERPRETATION Significant abnormalities in cortical structure is present at least three years before dementia manifests in Parkinson's disease, with associated differences in clinical profiles. Combining this data provides a technique to accurately identify future cognitive impairment, providing a non-invasive way to stratify individuals early on.

scholarly journals Dynamic functional connectivity changes associated with dementia in Parkinson’s disease

Brain ◽  
2019 ◽  
Vol 142 (9) ◽  
pp. 2860-2872 ◽  
Author(s):  
Eleonora Fiorenzato ◽  
Antonio P Strafella ◽  
Jinhee Kim ◽  
Roberta Schifano ◽  
Luca Weis ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Parkinson’S Disease Dementia ◽  
Dynamic Functional Connectivity ◽  
Control Subjects ◽  
Healthy Control ◽  
Normal Cognition

AbstractDynamic functional connectivity captures temporal variations of functional connectivity during MRI acquisition and it may be a suitable method to detect cognitive changes in Parkinson’s disease. In this study, we evaluated 118 patients with Parkinson’s disease matched for age, sex and education with 35 healthy control subjects. Patients with Parkinson’s disease were classified with normal cognition (n = 52), mild cognitive impairment (n = 46), and dementia (n = 20) based on an extensive neuropsychological evaluation. Resting state functional MRI and a sliding-window approach were used to study the dynamic functional connectivity. Dynamic analysis suggested two distinct connectivity ‘States’ across the entire group: a more frequent, segregated brain state characterized by the predominance of within-network connections, State I, and a less frequent, integrated state with strongly connected functional internetwork components, State II. In Parkinson’s disease, State I occurred 13.89% more often than in healthy control subjects, paralleled by a proportional reduction of State II. Parkinson’s disease subgroups analyses showed the segregated state occurred more frequently in Parkinson’s disease dementia than in mild cognitive impairment and normal cognition groups. Further, patients with Parkinson’s disease dementia dwelled significantly longer in the segregated State I, and showed a significant lower number of transitions to the strongly interconnected State II compared to the other subgroups. Our study indicates that dementia in Parkinson’s disease is characterized by altered temporal properties in dynamic connectivity. In addition, our results show that increased dwell time in the segregated state and reduced number of transitions between states are associated with presence of dementia in Parkinson’s disease. Further studies on dynamic functional connectivity changes could help to better understand the progressive dysfunction of networks between Parkinson’s disease cognitive states.

scholarly journals Mild cognitive impairment as a risk factor for Parkinson's disease dementia

2017 ◽  
Vol 32 (7) ◽  
pp. 1056-1065 ◽  
Author(s):  
Jeroen Hoogland ◽  
Judith A. Boel ◽  
Rob M.A. de Bie ◽  
Ronald B. Geskus ◽  
Ben A. Schmand ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Risk Factor ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Parkinson’S Disease Dementia

scholarly journals Subjective Cognitive Complaints in Newly-Diagnosed Parkinson’s Disease With and Without Mild Cognitive Impairment

2021 ◽  
Vol 15 ◽  
Author(s):  
Chenxi Pan ◽  
Jingru Ren ◽  
Ping Hua ◽  
Lei Yan ◽  
Miao Yu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Status ◽  
Newly Diagnosed ◽  
Cognitive Complaints ◽  
Subjective Cognitive Complaints

Background: Subjective cognitive complaints (SCCs) and mild cognitive impairment (MCI) are common among patients with Parkinson’s disease (PD). However, the relationship between SCCs and MCI is not well understood. Herein, we aimed to investigate whether there are any differences in the prevalence and risk factors of SCCs between early PD patients with and without MCI.Methods: Overall, 108 newly diagnosed, untreated PD patients underwent comprehensive neuropsychological assessments. PD patients with mild cognitive impairment (PD-MCI) were diagnosed according to the MCI level II criteria. Furthermore, SCCs were measured with the Cognitive Complaints Interview (CCI). Logistic regression analysis, after adjusting for confounding variable, was performed in order to investigate risk factors of SCCs in PD-MCI patients and PD patients with normal cognition (PD-NC).Results: Furthermore, 42 (42.3%) participants reported SCCs and 53 (53.5%) participants were diagnosed with PD-MCI. The prevalence of SCCs in PD-MCI and PD-NC participants was 30.3% and 12.1%, respectively. Logistic regression analyses revealed that the presence of SCCs in PD-MCI group was significantly associated with Non-Motor Symptoms Questionnaire (NMSQ) score (OR = 1.340, 95%CI = 1.115−1.610, p = 0.002), while the presence of SCCs in PD-NC group was significantly associated with time of Stroop Color-Word Test card C (OR = 1.050, 95%CI = 1.009−1.119, p = 0.016).Conclusion: SCCs are frequent among patients with early PD. The prevalence and risk factor of SCCs are distinct in PD with and without MCI. These findings suggest that SCCs in early PD with different cognitive status appear to have different pathogenicity.

Assessment of White Matter Lesions in Parkinson's Disease: Voxel-based Analysis and Tract-based Spatial Statistics Analysis of Parkinson's Disease with Mild Cognitive Impairment

2020 ◽  
Vol 17 (4) ◽  
pp. 480-486
Author(s):  
Wei Pu ◽  
Xudong Shen ◽  
Mingming Huang ◽  
Zhiqian Li ◽  
Xianchun Zeng ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Corpus Callosum ◽  
Fractional Anisotropy ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Tract Based Spatial Statistics

Objective: Application of diffusion tensor imaging (DTI) to explore the changes of FA value in patients with Parkinson's disease (PD) with mild cognitive impairment. Methods: 27 patients with PD were divided into PD with mild cognitive impairment (PD-MCI) group (n = 7) and PD group (n = 20). The original images were processed using voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). Results: The average age of pd-mci group was longer than that of PD group, and the course of disease was longer than that of PD group. Compared with PD group, the voxel based analysis-fractional anisotropy (VBA-FA) values of PD-MCI group decreased in the following areas: bilateral frontal lobe, bilateral temporal lobe, bilateral parietal lobe, bilateral subthalamic nucleus, corpus callosum, and gyrus cingula. Tract-based spatial statistics-fractional anisotropy (TBSS-FA) values in PD-MCI group decreased in bilateral corticospinal tract, anterior cingulum, posterior cingulum, fornix tract, bilateral superior thalamic radiation, corpus callosum(genu, body and splenium), bilateral uncinate fasciculus, bilateral inferior longitudinal fasciculus, bilateral superior longitudinal fasciculus, bilateral superior fronto-occipital fasciculus, bilateral inferior fronto-occipital fasciculus, and bilateral parietal-occipital tracts. The mean age of onset in the PD-MCI group was greater than that in the PD group, and the disease course was longer than that in the PD group. Conclusion: DTI-based VBA and TBSS post-processing methods can detect abnormalities in multiple brain areas and white matter fiber tracts in PD-MCI patients. Impairment of multiple cerebral cortex and white matter fiber pathways may be an important causes of cognitive dysfunction in PD-MCI.

Sign in / Sign up

Export Citation Format

Share Document