Global assessment, cognitive profile, and characteristics of mild cognitive impairment in Parkinson's disease

Yang, Jihyun; Pourzinal, Dana; Byrne, Gerard; McMahon, Katie L.; Copland, David A.; O’Sullivan, John D.; Mitchell, Leander K.; Dissanayaka, N.

doi:10.1002/gps.5955

Cited by 4 publications

(4 citation statements)

References 51 publications

(131 reference statements)

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“…In evaluating cognitive function, MoCA is the most commonly used neuropsychological scale in clinical practice to quickly and easily assess cognitive function. However, it exhibits poor psychological measurement characteristics and low sensitivity and specificity, 28 and as a subjective quantitative measure, it cannot directly reflect changes in neuropathology. In addition, although the diagnostic performance of radiomics model is close to that of a multimodal combinatorial model and can reflect some changes in neuropathology, due to the long course of PD.…”

Section: Discussionmentioning

confidence: 99%

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study

Jian,

Peng,

Wang

et al. 2024

CNS Neurosci Ther

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ObjectiveTo develop and validate a multimodal combinatorial model based on whole‐brain magnetic resonance imaging (MRI) radiomic features for predicting cognitive decline in patients with Parkinson's disease (PD).MethodsThis study included a total of 222 PD patients with normal baseline cognition, of whom 68 had cognitive impairment during a 4‐year follow‐up period. All patients underwent MRI scans, and radiomic features were extracted from the whole‐brain MRI images of the training set, and dimensionality reduction was performed to construct a radiomics model. Subsequently, Screening predictive factors for cognitive decline from clinical features and then combining those with a radiomics model to construct a multimodal combinatorial model for predicting cognitive decline in PD patients. Evaluate the performance of the comprehensive model using the receiver‐operating characteristic curve, confusion matrix, F1 score, and survival curve. In addition, the quantitative characteristics of diffusion tensor imaging (DTI) from corpus callosum were selected from 52 PD patients to further validate the clinical efficacy of the model.ResultsThe multimodal combinatorial model has good classification performance, with areas under the curve of 0.842, 0.829, and 0.860 in the training, test, and validation sets, respectively. Significant differences were observed in the number of cognitive decline PD patients and corpus callosum‐related DTI parameters between the low‐risk and high‐risk groups distinguished by the model (p < 0.05). The survival curve analysis showed a statistically significant difference in the progression time of mild cognitive impairment between the low‐risk and the high‐risk groups.ConclusionsThe building of a multimodal combinatorial model based on radiomic features from MRI can predict cognitive decline in PD patients, thus providing adaptive strategies for clinical practice.

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Section: Discussionmentioning

confidence: 99%

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study

Jian,

Peng,

Wang

et al. 2024

CNS Neurosci Ther

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“…MCI, a transitional stage between normal cognition and dementia, can occur in the presymptomatic phase of PD; it affects 19–30% of newly diagnosed, untreated (de novo) PD patients and has a frequency ranging from 21% to 70% with a mean of 25.8% [ 25 , 57 , 58 , 59 , 60 , 61 ]. About 30% of de novo PD patients complain of memory issues and are more likely to develop MCI after 2 years follow-up [ 50 ], but other factors, such as anxiety and affective symptoms, may contribute to the progression of cognitive deficits [ 62 , 63 ].…”

Section: Epidemiology Of CI In Pdmentioning

confidence: 99%

“…The cognitive phenotype was heterogenous; the most common subtypes were amnestic and non-amnestic MCI (aMCI, naMCI) single domain (11.3% and 8.9%, respectively) [ 76 ]. More recent studies reported 69.3% PD-MCI, 16% PD with normal cognition (PD-NC) and 14.66% PDD [ 77 ] or 34% PD-MCI with 77.8% impaired in multiple cognitive domains [ 59 ].…”

Section: Epidemiology Of CI In Pdmentioning

confidence: 99%

“…MCI, according to current clinical criteria, includes amnestic and non-amnestic types (aMCI and naMCI) [ 127 ], which may involve single or multiple cognitive domains. The latter was observed in 99.8% of the PD-MCI patients [ 59 ]. The heterogeneity of early de novo PD-MCI suggested the existence of three distinct memory phenotypes: cluster A (65.9%) included memory unimpaired patients, cluster B (23.2%) included those with mild episodic memory disorder (prefrontal executive-dependent phenotype), and cluster C (10.9%) included those with severe episodic disorder, which is related to the co-occurrence of hippocampal-dependent deficits with premotor executive memory dysfunctions.…”

Section: Development and Clinical Profile Of CI In Pdmentioning

confidence: 99%

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Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Jellinger

2023

IJMS

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Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

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Mild cognitive impairment in Parkinson's disease: current view

Jellinger

2024

Front. Cognit.

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Parkinson's disease (PD), the most common motor movement disorder and second most common neurodegenerative disorder after Alzheimer's disease (AD), is often preceded by a period of mild cognitive impairment (MCI), which is associated with impairment of a variety of cognitive domains including executive function, attention, visuospatial abilities and memory. MCI, a risk factor for developing dementia, affects around 30% of de novo PD patients and can increase to 75% after more than 10 years. While 30–40% remain in the MCI state, up to 60% will convert to dementia. Characteristic findings are slowing of EEG rhythms, frontotemporal hypoperfusion, decreased functional connectivity in the default mode and attentional networks, prefrontal and basal-ganglia-cortical circuits, which often manifests prior to clinical symptoms and overt brain atrophy. The heterogeneity of cognitive phenotypes suggests that a common neurodegenerative process affects multiple functional neuronal networks and neuromodulatory systems that may be superimposed by Lewy body and Alzheimer's-related or other co-pathologies. Sparse neuropathological data for PD-MCI revealed a heterogenous picture with various morphological changes similar to MCI in other diseases. This review highlights the essential epidemiological, clinical, neuroimaging and morphological changes in PD-MCI, available biomarkers, and discusses the heterogenous pathobiological mechanisms involved in its development. In view of its complex pathogenesis, well-designed longitudinal clinico-pathological studies are warranted to clarify the alterations leading to MCI in PD, which may be supported by fluid and neuroimaging biomarkers as a basis for early diagnosis and future adequate treatment modalities of this debilitating disorder.

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Global assessment, cognitive profile, and characteristics of mild cognitive impairment in Parkinson's disease

Cited by 4 publications

References 51 publications

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Mild cognitive impairment in Parkinson's disease: current view

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