scholarly journals Is the Random Forest Algorithm Suitable for Predicting Parkinson’s Disease with Mild Cognitive Impairment out of Parkinson’s Disease with Normal Cognition?

2020 ◽  
Vol 17 (7) ◽  
pp. 2594 ◽  
Author(s):  
Haewon Byeon
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Random Forest ◽  
Decision Tree ◽  
Prediction Model ◽  
Prediction Accuracy ◽  
Early Stage ◽  
Normal Cognition

Because it is possible to delay the progression of dementia if it is detected and treated in an early stage, identifying mild cognitive impairment (MCI) is an important primary goal of dementia treatment. The objectives of this study were to develop a random forest-based Parkinson’s disease with mild cognitive impairment (PD-MCI) prediction model considering health behaviors, environmental factors, medical history, physical functions, depression, and cognitive functions using the Parkinson’s Dementia Clinical Epidemiology Data (a national survey conducted by the Korea Centers for Disease Control and Prevention) and to compare the prediction accuracy of our model with those of decision tree and multiple logistic regression models. We analyzed 96 subjects (PD-MCI = 45; Parkinson’s disease with normal cognition (PD-NC) = 51 subjects). The prediction accuracy of the model was calculated using the overall accuracy, sensitivity, and specificity. Based on the random forest analysis, the major risk factors of PD-MCI were, in descending order of magnitude, Clinical Dementia Rating (CDR) sum of boxes, Untitled Parkinson’s Disease Rating (UPDRS) motor score, the Korean Mini Mental State Examination (K-MMSE) total score, and the K- Korean Montreal Cognitive Assessment (K-MoCA) total score. The random forest method achieved a higher sensitivity than the decision tree model. Thus, it is advisable to develop a protocol to easily identify early stage PDD based on the PD-MCI prediction model developed in this study, in order to establish individualized monitoring to track high-risk groups.

Olfactory Function and Diffusion Tensor Imaging as Markers of Mild Cognitive Impairment in Early Stages of Parkinson's Disease

2021 ◽  
pp. 155005942110582
Author(s):  
Sophie A. Stewart ◽  
Laura Pimer ◽  
John D. Fisk ◽  
Benjamin Rusak ◽  
Ron A. Leslie ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Diffusion Tensor Imaging ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Neurodegenerative Disorder ◽  
Diffusion Tensor ◽  
Early Stage ◽  
White Matter Integrity

Parkinson's disease (PD) is a neurodegenerative disorder that is typified by motor signs and symptoms but can also lead to significant cognitive impairment and dementia Parkinson's Disease Dementia (PDD). While dementia is considered a nonmotor feature of PD that typically occurs later, individuals with PD may experience mild cognitive impairment (PD-MCI) earlier in the disease course. Olfactory deficit (OD) is considered another nonmotor symptom of PD and often presents even before the motor signs and diagnosis of PD. We examined potential links among cognitive impairment, olfactory functioning, and white matter integrity of olfactory brain regions in persons with early-stage PD. Cognitive tests were used to established groups with PD-MCI and with normal cognition (PD-NC). Olfactory functioning was examined using the University of Pennsylvania Smell Identification Test (UPSIT) while the white matter integrity of the anterior olfactory structures (AOS) was examined using magnetic resonance imaging (MRI) diffusion tensor imaging (DTI) analysis. Those with PD-MCI demonstrated poorer olfactory functioning and abnormalities based on all DTI parameters in the AOS, relative to PD-NC individuals. OD and microstructural changes in the AOS of individuals with PD may serve as additional biological markers of PD-MCI.

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 Predictors of Mild Cognitive Impairment in Early-Stage Parkinson's Disease

2013 ◽  
Vol 3 (1) ◽  
pp. 168-178 ◽  
Author(s):  
Brenda Hanna-Pladdy ◽  
Katherine Jones ◽  
Romeo Cabanban ◽  
Rajesh Pahwa ◽  
Kelly E. Lyons
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Stage

scholarly journals Topological Abnormalities of Functional Brain Network in Early-Stage Parkinson’s Disease Patients With Mild Cognitive Impairment

2020 ◽  
Vol 14 ◽  
Author(s):  
Xiangbin Chen ◽  
Mengting Liu ◽  
Zhibing Wu ◽  
Hao Cheng
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Information Exchange ◽  
Early Stage ◽  
Brain Network ◽  
Clustering Coefficient ◽  
Functional Brain ◽  
Functional Brain Network

Recent studies have demonstrated structural and functional alterations in Parkinson’s disease (PD) with mild cognitive impairment (MCI). However, the topological patterns of functional brain networks in newly diagnosed PD patients with MCI are unclear so far. In this study, we used functional magnetic resonance imaging (fMRI) and graph theory approaches to explore the functional brain network in 45 PD patients with MCI (PD-MCI), 22 PD patients without MCI (PD-nMCI), and 18 healthy controls (HC). We found that the PD-MCI, PD-nMCI, and HC groups exhibited a small-world architecture in the functional brain network. However, early-stage PD-MCI patients had decreased clustering coefficient, increased characteristic path length, and changed nodal centrality in the default mode network (DMN), control network (CN), somatomotor network (SMN), and visual network (VN), which might contribute to factors for MCI symptoms in PD patients. Our results demonstrated that PD-MCI patients were associated with disrupted topological organization in the functional network, thus providing a topological network insight into the role of information exchange in the underlying development of MCI symptoms in PD patients.

scholarly journals Dynamic functional connectivity in Parkinson's disease patients with mild cognitive impairment and normal cognition

2018 ◽  
Vol 17 ◽  
pp. 847-855 ◽  
Author(s):  
María Díez-Cirarda ◽  
Antonio P. Strafella ◽  
Jinhee Kim ◽  
Javier Peña ◽  
Natalia Ojeda ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Dynamic Functional Connectivity ◽  
Normal Cognition

scholarly journals Altered Cerebellar Resting-State Functional Connectivity in Early-Stage Parkinson's Disease Patients With Cognitive Impairment

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaojuan Dan ◽  
Yang Hu ◽  
Junyan Sun ◽  
Linlin Gao ◽  
Yongtao Zhou ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Cognitive Deficits ◽  
Resting State ◽  
Early Stage ◽  
Cognitive Status ◽  
Elderly Subjects ◽  
Normal Cognition

Background: Cognitive impairment is one of the most prominent non-motor symptoms in Parkinson's disease (PD), due in part to known cerebellar dysfunctions. Furthermore, previous studies have reported altered cerebellar functional connectivity (FC) in PD patients. Yet whether these changes are also due to the cognitive deficits in PD remain unclear.Methods: A total of 122 non-dementia participants, including 64 patients with early PD and 58 age- and gender-matched elderly controls were stratified into four groups based on their cognitive status (normal cognition vs. cognitive impairment). Cerebellar volumetry and FC were investigated by analyzing, respectively, structural and resting-state functional MRI data among groups using quality control and quantitative measures. Correlation analysis between MRI metrics and clinical features (motor and cognitive scores) were performed.Results: Compared to healthy control subjects with no cognitive deficits, altered cerebellar FC were observed in early PD participants with both motor and cognitive deficits, but not in PD patients with normal cognition, nor elderly subjects showing signs of a cognitive impairment. Moreover, connectivity between the “motor” cerebellum and SMA was positively correlated with motor scores, while intracerebellar connectivity was positively correlated with cognitive scores in PD patients with cognitive impairment. No cerebellar volumetric difference was observed between groups.Conclusions: These findings show that altered cerebellar FC during resting state in early PD patients may be driven not solely by the motor deficits, but by cognitive deficits as well, hence highlighting the interplay between motor and cognitive functioning, and possibly reflecting compensatory mechanisms, in the early PD.

scholarly journals Functional Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment

2020 ◽  
Author(s):  
Qingguang Wang ◽  
Wei He ◽  
Dinghua Liu ◽  
Bojun Han ◽  
Qitao Jiang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Connectivity ◽  
Demographic Data ◽  
Posterior Cingulate Cortex ◽  
Mri Scans ◽  
The Relationship ◽  
Normal Cognition

Abstract Background: To explore the alteration of pattens of anatomical and functional connectivity (FC) of posterior cingulate cortex (PCC) in Parkinson's disease (PD) patients with cognitive dysfunction and the relationship between the connection strengths and cognitive state．Methods: We prospectively enrolled 20 PD patients with mild cognitive impairment (PD-MCI), 13 PD patients with normal cognition (PD-NC) and 13 healthy controls (HCs). All subjects underwent clinical evaluations and MRI scans. By collecting, preprocessing and FC analyzing resting-state functional magnetic resonance imaging (rs-fMRI) data, we extracted default mode network (DMN) patterns, compared the differences in DMN between the three groups and the analyzed the correlation between FC value with the commonly used neuropsychological testing.Results: There were not significant differences with regard to demographic data among the three groups. The PD-MCI showed significant worse performances in general cognition, and PD-NC and HCs showed comparable performances of cognitive function. Cognitive-related differences in DMN were detected in the bilateral precuneus (BPcu). Compared with the HCs, PD-NC and PD-MCI showed significantly decreased FC within BPcu (both P < 0.001). For PD-MCI, the rho of the the Fisher’s Z-transformed FC (zFC) value within BPcu with the TMTA, DSST and CFT-20min were − 0.50, 0.66 and 0.47, respectively. For PD-NC, the rho of the zFC value within BPcu with the MMSE was 0.58.Conclusions: Our research found that BPcu was the cognitive related region in DMN. As cognition declines, FC within BPcu weaken. For PD-MCI, the higher the FC values within BPcu were related to the better the performances of TMTA, DSST and CFT-20 min DR. For PD patients with normal cognition, the FC within BPcu were positively correlated with scores of MMSE.

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