Grey matter atrophy in cognitively impaired Parkinson's disease

Structural and functional brain correlates of socioeconomic status across the life span: A systematic review

It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.

A crazy trio in Parkinson's disease: metabolism alteration, α-synuclein aggregation, and oxidative stress

Parkinson's disease (PD) is an aging-associated neurodegenerative disorder, characterized by the progressive loss of dopaminergic neurons in the pars compacta of the substantia nigra and the presence of Lewy bodies containing α-synuclein within these neurons. Oligomeric α-synuclein exerts neurotoxic effects through mitochondrial dysfunction, glial cell inflammatory response, lysosomal dysfunction and so on. α-synuclein aggregation, often accompanied by oxidative stress, is generally considered to be a key factor in PD pathology. At present, emerging evidences suggest that metabolism alteration is closely associated with α-synuclein aggregation and PD progression, and improvement of key molecules in metabolism might be potentially beneficial in PD treatment. In this review, we highlight the tripartite relationship among metabolic changes, α-synuclein aggregation, and oxidative stress in PD, and offer updated insights into the treatments of PD, aiming to deepen our understanding of PD pathogenesis and explore new therapeutic strategies for the disease.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease

OBJECTIVE

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD).

METHODS

Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies.

RESULTS

A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926.

CONCLUSION

The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Artificial Intelligence Diagnosis of Parkinson's Disease From MRI Scans

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by motor symptoms such as tremors, rigidity, and bradykinesia, affecting approximately 6.1 million people worldwide, according to estimates from the Parkinson's Foundation. Early and accurate diagnosis of PD is crucial for effective management and treatment. In this study, we aimed to develop an artificial intelligence (AI) model capable of distinguishing between magnetic resonance imaging (MRI) scans of individuals with PD and those without PD. A total of 442 MRI scans were utilized for training the AI model, comprising 221 scans of individuals diagnosed with PD and 221 scans of healthy controls. The dataset, obtained from a publicly available image dataset on Kaggle.com, was randomly split into three sets: training, validation, and testing, with 80%, 10%, and 10% of the data allocated to each set, respectively. Leveraging Google's Collaboration platform for model training, the AI model achieved exceptional performance, with accuracy, precision, recall (sensitivity), specificity, and F1-score all measuring at high levels. Additionally, the area under the receiver operating characteristic curve (AUC) for the model was found to be 1, indicating strong discrimination between PD and non-PD cases. This study presents a novel AI model capable of accurately identifying PD from MRI scans with high precision and reliability, offering promise for enhancing early diagnosis and personalized treatment strategies for individuals affected by PD.

Mild Behavioral Impairment in Parkinson's Disease: An Updated Review on the Clinical, Genetic, Neuroanatomical, and Pathophysiological Aspects

Neuropsychiatric symptoms (NPS), including depression, anxiety, apathy, visual hallucinations, and impulse control disorders, are very common during the course of Parkinson's disease (PD), occurring even at the prodromal and premotor stages. Mild behavioral impairment (MBI) represents a recently described neurobehavioral syndrome, characterized by the emergence of persistent and impactful NPS in later life, reflecting arisk of dementia. Accumulating evidence suggests that MBI is highly prevalent in non-demented patients with PD, also being associated with an advanced disease stage, more severe motor deficits, as well as global and multiple-domain cognitive impairment. Neuroimaging studies have revealed that MBI in patients with PD may be related todistinct patterns of brain atrophy, altered neuronal connectivity, and distribution of dopamine transporter (DAT) depletion, shedding more light on its pathophysiological background. Genetic studies in PD patients have also shown that specific single-nucleotide polymorphisms (SNPs) may be associated with MBI, paving the way for future research in this field. In this review, we summarize and critically discuss the emerging evidence on the frequency, associated clinical and genetic factors, as well as neuroanatomical and neurophysiological correlates of MBI in PD, aiming to elucidate the underlying pathophysiology and its potential role as an early "marker" of cognitive decline, particularly in this population. In addition, we aim to identify research gaps, and propose novel relative areas of interest that could aid in our better understanding of the relationship of this newly defined diagnostic entity with PD.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

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.

Structural and molecular cholinergic imaging markers of cognitive decline in Parkinson's disease

Cognitive decline in Parkinson's disease is related to cholinergic system degeneration, which can be assessed in vivo using structural MRI markers of basal forebrain volume and PET measures of cortical cholinergic activity. In the present study we aimed to examine the interrelation between basal forebrain degeneration and PET-measured depletion of cortical acetylcholinesterase activity as well as their relative contribution to cognitive impairment in Parkinson's disease. This cross-sectional study included 143 Parkinson's disease participants without dementia and 52 healthy control participants who underwent structural MRI, PET scanning with 11C-methyl-4-piperidinyl propionate (PMP) as a measure of cortical acetylcholinesterase activity, and a detailed cognitive assessment. Based on the fifth percentile of the overall cortical PMP PET signal from the control group, people with Parkinson's disease were subdivided into a normo-cholinergic (n = 94) and a hypo-cholinergic group (n = 49). Volumes of functionally defined posterior and anterior basal forebrain subregions were extracted using an established automated MRI volumetry approach based on a stereotactic atlas of cholinergic basal forebrain nuclei. We used Bayesian t-tests to compare basal forebrain volumes between controls, and normo- and hypo-cholinergic Parkinson's participants after covarying out age, sex and years of education. Associations between the two cholinergic imaging measures were assessed across all people with Parkinson's disease using Bayesian correlations and their respective relations with performance in different cognitive domains were assessed with Bayesian ANCOVAs. As a specificity analysis, hippocampal volume was added to the analysis. We found evidence for a reduction of posterior basal forebrain volume in the hypo-cholinergic compared to both normo-cholinergic Parkinson's disease [Bayes factor against the null model (BF10) = 8.2] and control participants (BF10 = 6.0), while for the anterior basal forebrain the evidence was inconclusive (BF10 < 3). In continuous association analyses, posterior basal forebrain volume was significantly associated with cortical PMP PET signal in a temporo-posterior distribution. The combined models for the prediction of cognitive scores showed that both cholinergic markers (posterior basal forebrain volume and cortical PMP PET signal) were independently related to multi-domain cognitive deficits, and were more important predictors for all cognitive scores, including memory scores, than hippocampal volume. We conclude that degeneration of the posterior basal forebrain in Parkinson's disease is accompanied by functional cortical changes in acetylcholinesterase activity and that both PET and MRI cholinergic imaging markers are independently associated with multi-domain cognitive deficits in Parkinson's disease without dementia. Comparatively, hippocampal atrophy only seems to have minimal involvement in the development of early cognitive impairment in Parkinson's disease.

Volumetric changes and clinical trajectories in Parkinson's disease: a prospective multicentric study

BACKGROUND

Longitudinal measures of structural brain changes using MRI in relation to clinical features and progression patterns in PD have been assessed in previous studies, but few were conducted in well-defined and large cohorts, including prospective clinical assessments of both motor and non-motor symptoms.

OBJECTIVE

We aimed to identify brain volumetric changes characterizing PD patients, and determine whether regional brain volumetric characteristics at baseline can predict motor, psycho-behavioral and cognitive evolution at one year in a prospective cohort of PD patients.

METHODS

In this multicentric 1 year longitudinal study, PD patients and healthy controls from the MPI-R2* cohort were assessed for demographical, clinical and brain volumetric characteristics. Distinct subgroups of PD patients according to motor, cognitive and psycho-behavioral evolution were identified at the end of follow-up.

RESULTS

One hundred and fifty PD patients and 73 control subjects were included in our analysis. Over one year, there was no significant difference in volume variations between PD and control subjects, regardless of the brain region considered. However, we observed a reduction in posterior cingulate cortex volume at baseline in PD patients with motor deterioration at one year (p = 0.017). We also observed a bilateral reduction of the volume of the amygdala (p = 0.015 and p = 0.041) and hippocampus (p = 0.015 and p = 0.053) at baseline in patients with psycho-behavioral deterioration, regardless of age, dopaminergic treatment and center.

CONCLUSION

Brain volumetric characteristics at baseline may predict clinical trajectories at 1 year in PD as posterior cingulate cortex atrophy was associated with motor decline, while amygdala and hippocampus atrophy were associated with psycho-behavioral decline.

Pathological Correlates of Cognitive Decline in Parkinson's Disease: From Molecules to Neural Networks

Parkinson's disease (PD) is a progressive neurodegenerative disorder caused by the death of dopaminergic neurons in the substantia nigra and appearance of protein aggregates (Lewy bodies) consisting predominantly of α-synuclein in neurons. PD is currently recognized as a multisystem disorder characterized by severe motor impairments and various non-motor symptoms. Cognitive decline is one of the most common and worrisome non-motor symptoms. Moderate cognitive impairments (CI) are diagnosed already at the early stages of PD, usually transform into dementia. The main types of CI in PD include executive dysfunction, attention and memory decline, visuospatial impairments, and verbal deficits. According to the published data, the following mechanisms play an essential role demonstrates a crucial importance in the decline of the motor and cognitive functions in PD: (1) changes in the conformational structure of transsynaptic proteins and protein aggregation in presynapses; (2) synaptic transmission impairment; (3) neuroinflammation (pathological activation of the neuroglia); (4) mitochondrial dysfunction and oxidative stress; (5) metabolic disorders (hypometabolism of glucose, dysfunction of glycolipid metabolism; and (6) functional rearrangement of neuronal networks. These changes can lead to the death of dopaminergic cells in the substantia nigra and affect the functioning of other neurotransmitter systems, thus disturbing neuronal networks involved in the transmission of information related to the regulation of motor activity and cognitive functions. Identification of factors causing detrimental changes in PD and methods for their elimination will help in the development of new approaches to the therapy of PD. The goal of this review was to analyze pathological processes that take place in the brain and underlie the onset of cognitive disorders in PD, as well as to describe the impairments of cognitive functions in this disease.

White matter changes in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease (AD). It is characterized by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) and the formation of Lewy bodies (LBs). Although PD is primarily considered a gray matter (GM) disease, alterations in white matter (WM) have gained increasing attention in PD research recently. Here we review evidence collected by magnetic resonance imaging (MRI) techniques which indicate WM abnormalities in PD, and discuss the correlations between WM changes and specific PD symptoms. Then we summarize transcriptome and genome studies showing the changes of oligodendrocyte (OLs)/myelin in PD. We conclude that WM abnormalities caused by the changes of myelin/OLs might be important for PD pathology, which could be potential targets for PD treatment.

Shrinkage of olfactory amygdala connotes cognitive impairment in patients with Parkinson's disease

During the caudo-rostral progression of Lewy pathology, the amygdala is involved relatively early in Parkinson's disease (PD). However, lesser is known about the volumetric differences at the amygdala subdivisions, although the evidence mainly implicates the olfactory amygdala. We aimed to investigate the volumetric differences between the amygdala's nuclear and sectoral subdivisions in the PD cognitive impairment continuum compared to healthy controls (HC). The volumes of nine nuclei of the amygdala were estimated with FreeSurfer (nuclear parcellation-NP) from T1-weighted images of PD patients with normal cognition (PD-CN), PD with mild cognitive impairment (PD-MCI), PD with dementia (PD-D), and HC. The appropriate nuclei were then merged to obtain three sectors of the amygdala (sectoral parcellation-SP). The nuclear and sectoral volumes were compared among the four groups and between the hyposmic and normosmic PD patients. There was a significant difference in the total amygdala volume among the four groups. In terms of nuclei, the bilateral cortico-amygdaloid transition area (CAT) and sectors superficial cortex-like region (sCLR) volumes of PD-MCI and PD-D were less than those of the PD-CN and HC. A linear discriminant analysis revealed that left CAT and left sCLR volumes classified the PD-CN and cognitively impaired PD (PD-CI: PD-MCI plus PD-D) with 90.7% accuracy according to NP and 85.2% accuracy to SP. Similarly, left CAT and sCLR volumes correctly identified the hyposmic and normosmic PD with 64.8% and 61.1% accuracies. Notably, the left olfactory amygdala volume successfully discriminated cognitive impairment in PD and could be used as neuroimaging-based support for PD-CI diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09887-y.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes.

METHODS

We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD.

RESULTS

149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis.

CONCLUSIONS

These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.

Brain Morphometry Associated With Response to Levodopa and Deep Brain Stimulation in Parkinson Disease

OBJECTIVES

Whether treatment response in patients with Parkinson disease depends on brain atrophy is insufficiently understood. The goal of this study is to identify specific atrophy patterns associated with response to dopaminergic therapy and deep brain stimulation.

MATERIALS AND METHODS

In this study, we analyzed the association of gray matter brain atrophy patterns, as identified by voxel-based morphometry, with acute response to levodopa (N = 118) and subthalamic nucleus deep brain stimulation (N = 39). Motor status was measured as a change in points on the Unified Parkinson's Disease Rating Scale III score. Baseline values were obtained before surgery, after cessation of dopaminergic medication for at least 12 hours; response to medication was assessed after administration of a standardized dose of levodopa. Response to deep brain stimulation was measured three months after surgery in the clinical condition after withdrawal of dopaminergic medication.

RESULTS

Although frontoparietal brain gray matter loss was associated with subpar response to deep brain stimulation, there was no significant link between brain atrophy and response to levodopa.

CONCLUSION

We conclude that response to deep brain stimulation relies on gray matter integrity; hence, gray matter loss may present a risk factor for poor response to deep brain stimulation and may be considered when making decision regarding clinical practice.

Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis

Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo. This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.

Detecting Parkinson's disease and its cognitive phenotypes via automated semantic analyses of action stories

Action-concept outcomes are useful targets to identify Parkinson's disease (PD) patients and differentiate between those with and without mild cognitive impairment (PD-MCI, PD-nMCI). Yet, most approaches employ burdensome examiner-dependent tasks, limiting their utility. We introduce a framework capturing action-concept markers automatically in natural speech. Patients from both subgroups and controls retold an action-laden and a non-action-laden text (AT, nAT). In each retelling, we weighed action and non-action concepts through our automated Proximity-to-Reference-Semantic-Field (P-RSF) metric, for analysis via ANCOVAs (controlling for cognitive dysfunction) and support vector machines. Patients were differentiated from controls based on AT (but not nAT) P-RSF scores. The same occurred in PD-nMCI patients. Conversely, PD-MCI patients exhibited reduced P-RSF scores for both texts. Direct discrimination between patient subgroups was not systematic, but it yielded best outcomes via AT scores. Our approach outperformed classifiers based on corpus-derived embeddings. This framework opens scalable avenues to support PD diagnosis and phenotyping.

Microstructural but not macrostructural cortical degeneration occurs in Parkinson’s disease with mild cognitive impairment

This study aimed to investigate the cortical microstructural/macrostructural degenerative patterns in Parkinson’s disease (PD) patients with mild cognitive impairment (MCI). Overall, 38 PD patients with normal cognition (PD-NC), 38 PD-MCI, and 32 healthy controls (HC) were included. PD-MCI was diagnosed according to the MDS Task Force level II criteria. Cortical microstructural alterations were evaluated with Neurite Orientation Dispersion and Density Imaging. Cortical thickness analyses were derived from T1-weighted imaging using the FreeSurfer software. For cortical microstructural analyses, compared with HC, PD-NC showed lower orientation dispersion index (ODI) in bilateral cingulate and paracingulate gyri, supplementary motor area, right paracentral lobule, and precuneus (PFWE < 0.05); while PD-MCI showed lower ODI in widespread regions covering bilateral frontal, parietal, occipital, and right temporal areas and lower neurite density index in left frontal area, left cingulate, and paracingulate gyri (PFWE < 0.05). Furthermore, compared with PD-NC, PD-MCI showed reduced ODI in right frontal area and bilateral caudate nuclei (voxel P < 0.01 and cluster >100 voxels) and the ODI values were associated with the Montreal Cognitive Assessment scores (r = 0.440, P < 0.001) and the memory performance (r = 0.333, P = 0.004) in the PD patients. However, for cortical thickness analyses, there was no difference in the between-group comparisons. In conclusion, cortical microstructural alterations may precede macrostructural changes in PD-MCI. This study provides insightful evidence for the degenerative patterns in PD-MCI and contributes to our understanding of the latent biological basis of cortical neurite changes for early cognitive impairment in PD.

Free Water Fraction Predicts Cognitive Decline for Individuals with Idiopathic Parkinson's disease

INTRODUCTION

Free water fraction (FWF) is considered a metric of microstructural integrity and may be useful in predicting cognitive decline in idiopathic Parkinson's Disease (PD). We sought to determine if higher FWF within the dorsal portion of the caudate nucleus and basal nucleus of Meynert, two regions associated with cognitive decline in PD, predict change in cognition over a two-year span. Due to the existence of cognitive and neurophysiological subgroups within PD, we statistically categorized participants based on FWF in these regions.

METHODS

At baseline, participants completed a research cognitive protocol followed by MRI structural and diffusion metrics. We used k-means cluster analysis with average FWF values from bilateral basal nucleus of Meynert and dorsal caudate to create data-driven FWF clusters for baseline. Two-year reliable change indices were calculated for metrics of language, visuospatial, memory, cognitive flexibility, and reasoning domains. Reliable change scores were compared between the clusters and non-PD peers.

RESULTS

Baseline participants included 174 participants (112 PD, 62 non-PD). Cluster analysis yielded three clusters: low FWF in both regions of interest (ROIs), high FWF in both ROIs, and moderate FWF in both ROIs. Reliable change analyses were completed on 93 participants (67 PD, 26 non-PD). After controlling for age and education, the High FWF cluster declined more than non-PD peers in every domain except memory.

CONCLUSION

Individuals with high FWF in regions associated with cognitive decline in PD show significant decline across several cognitive domains compared to non-PD peers. Future research should include FWF in additional cortical regions.

The structural changes of gray matter in Parkinson disease patients with mild cognitive impairments

Objectives

Parkinson disease (PD) is associated with cognitive impairments. However, the underlying neural mechanism of cognitive impairments in PD is still not clear. This study aimed to investigate the anatomic alternations of gray matter in PD patients with mild cognitive impairment (MCI) and their associations with neurocognitive measurements.

Methods

T1-weighted magnetic resonance imaging (MRI) data were acquired from 23 PD patients with MCI, 23 PD patients without MCI, and 23 matched healthy controls. The MRI data were analyzed using voxel-based morphometry (VBM) and surfaced-based morphometry (SBM) methods to assess the structural changes in gray matter volume and cortical thickness respectively. Receiver operating characteristic (ROC) analysis was used to examine the diagnostic accuracies of the indexes of interest. The correlations between the structural metrics and neurocognitive assessments (e.g., Montreal cognitive assessment, MOCA; Mini-mental state examination, MMSE) were further examined.

Results

PD patients with MCI showed reduced gray matter volume (GMV) in the frontal cortex (e.g., right inferior frontal gyrus and middle frontal gyrus) and extended to insula as well as cerebellum compared with the healthy controls and PD patients without MIC. Thinner of cortical thickens in the temporal lobe (e.g., left middle temporal gyrus and right superior temporal gyrus) extending to parietal cortex (e.g., precuneus) were found in the PD patients with MCI relative to the healthy controls and PD patients without MCI.ROC analysis indicated that the area under the ROC curve (AUC) values in the frontal, temporal, and subcortical structures (e.g., insula and cerebellum) could differentiate the PD patients with MCI and without MCI and healthy controls. Furthermore, GMV of the right middle frontal gyrus and cortical thickness of the right superior temporal gyrus were correlated with neurocognitive dysfunctions (e.g., MOCA and MMSE) in PD patients with MCI.

Conclusion

This study provided further evidence that PD with MCI was associated with structural alternations of brain. Morphometric analysis focusing on the cortical and subcortical regions could be biomarkers of cognitive impairments in PD patients.

Altered Prefrontal Blood Flow Related With Mild Cognitive Impairment in Parkinson's Disease: A Longitudinal Study

Cognitive impairment is a common non-motor symptom in Parkinson's disease (PD), with executive dysfunction being an initial manifestation. We aimed to investigate whether and how longitudinal changes in the prefrontal perfusion correlate with mild cognitive impairment (MCI) in patients with PD. We recruited 49 patients with PD with normal cognition and 37 matched healthy control subjects (HCs). Patients with PD completed arterial spin labeling MRI (ASL–MRI) scans and a comprehensive battery of neuropsychological assessments at baseline (V0) and 2-year follow-up (V1). HCs completed similar ASL–MRI scans and neuropsychological assessments at baseline. At V1, 10 patients with PD progressed to MCI (converters) and 39 patients remained cognitively normal (non-converters). We examined differences in the cerebral blood flow (CBF) derived from ASL–MRI and neuropsychological measures (a) between patients with PD and HCs at V0 (effect of the disease), (b) between V1 and V0 in patients with PD (effect of the disease progression), and (c) between converters and non-converters (effect of the MCI progression) using t-tests or ANOVAs with false discovery rate correction. We further analyzed the relationship between longitudinal CBF and neuropsychological changes using multivariate regression models with false discovery rate correction, focusing on executive functions. At V0, no group difference was found in prefrontal CBF between patients with PD and HCs, although patients with PD showed worse performances on executive function. At V1, patients with PD showed significantly reduced CBF in multiple prefrontal regions, including the bilateral lateral orbitofrontal, medial orbitofrontal, middle frontal, inferior frontal, superior frontal, caudal anterior cingulate, and rostral anterior cingulate. More importantly, converters showed a more significant CBF reduction in the left lateral orbitofrontal cortex than non-converters. From V0 to V1, the prolonged completion time of Trail Making Test-B (TMT-B) negatively correlated with longitudinal CBF reduction in the right caudal anterior cingulate cortex. The decreased accuracy of the Stroop Color-Word Test positively correlated with longitudinal CBF reduction in the left medial orbitofrontal cortex. In addition, at V1, the completion time of TMT-B negatively correlated with CBF in the left caudal anterior cingulate cortex. Our findings suggest that longitudinal CBF reduction in the prefrontal cortex might impact cognitive functions (especially executive functions) at the early stages of PD.

Simulating the progression of brain structural alterations in Parkinson's disease

Considering brain structural alterations as neurodegenerative consequences of Parkinson's disease (PD), we sought to infer the progression of PD via the ordering of brain structural alterations from cross-sectional MRI observations. Having measured cortical thinning in gray matter (GM) regions and disintegrity in white matter (WM) regions as MRI markers of structural alterations for 130 patients with PD (69 ± 10 years, 72 men), stochastic simulation based on the probabilistic relationship between the brain regions was conducted to infer the ordering of structural alterations across all brain regions and the staging of structural alterations according to changes in clinical status. The ordering of structural alterations represented WM disintegrity tending to occur earlier than cortical thinning. The staging of structural alterations indicated structural alterations happening mostly before major disease complications such as postural instability and dementia. Later disease states predicted by the sequence of structural alterations were significantly related to more severe clinical symptoms. The relevance of the ordering of brain structural alterations to the severity of clinical symptoms suggests the clinical feasibility of predicting PD progression states.

Morphological basis of Parkinson disease-associated cognitive impairment: an update

Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.

Evolution patterns of probable REM sleep behavior disorder predicts Parkinson's disease progression

The course of REM sleep behavior disorder (RBD) variates in the early stage of Parkinson's disease. We aimed to delineate the association between the evolution pattern of probable RBD (pRBD) and the progression of Parkinson's disease (PD). 281 de novo PD patients from the Parkinson's Progression Markers Initiative database were included. Patients were followed up for a mean of 6.8 years and were classified into different groups according to the evolution patterns of pRBD. Disease progression was compared among groups using survival analysis, where the endpoint was defined as progression to Hoehn-Yahr stage 3 or higher for motor progression and progression to mild cognitive impairment for cognitive decline. At the 4th year of follow-up, four types of pRBD evolution patterns were identified: (1) non-RBD-stable (55.5%): patients persistently free of pRBD; (2) late-RBD (12.1%): patients developed pRBD during follow-up; (3) RBD-stable (24.9%): patients showed persistent pRBD, and (4) RBD-reversion (7.5%): patients showed pRBD at baseline which disappeared during follow-up. The RBD-reversion type showed the fastest motor progression while the RBD-stable type showed the fastest cognitive decline. At baseline, the RBD-reversion type showed the most severe gray matter atrophy in the middle frontal gyrus, while the RBD-stable type showed gray matter atrophy mainly in the para-hippocampal gyrus. Four types of early pRBD evolution patterns featured different brain lesions and predicted different courses of motor and cognitive decline in PD.

Midsagittal corpus callosal thickness and cognitive impairment in Parkinson's disease

People diagnosed with Parkinson's disease (PD) can experience significant neuropsychiatric symptoms, including cognitive impairment and dementia, the neuroanatomical substrates of which are not fully characterised. Symptoms associated with cognitive impairment and dementia in PD may relate to direct structural changes to the corpus callosum via primary white matter pathology, or as a secondary outcome due to the degeneration of cortical regions. Using magnetic resonance imaging, the corpus callosum can be investigated at the midsagittal plane, where it converges to a contiguous mass and is not intertwined with other tracts. The objective of this project was thus twofold; first, we investigated possible changes in the thickness of the midsagittal callosum and cortex in patients with PD with varying levels of cognitive impairment; and secondly, we investigated the relationship between the thickness of the midsagittal corpus callosum and the thickness of the cortex. Study participants included cognitively unimpaired PD participants (n = 35), PD participants with mild cognitive impairment (n = 22), PD participants with dementia (n = 17) and healthy controls (n = 27). We found thinning of the callosum in PD-related dementia compared to PD-related mild cognitive impairment and cognitively unimpaired PD participants. Regression analyses found thickness of the left medial orbitofrontal cortex to be positively correlated with thickness of the anterior callosum in PD-related mild cognitive impairment. This study suggests that a midsagittal thickness model can uncover changes to the corpus callosum in PD-related dementia, which occur in line with changes to the cortex in this advanced disease stage.

Metabolic Features of Brain Function with Relevance to Clinical Features of Alzheimer and Parkinson Diseases

Brain metabolism is comprised in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Since the brain primarily relies on metabolism of glucose, ketone bodies, and amino acids, aspects of these metabolic processes in these disorders—and particularly how these altered metabolic processes are related to oxidative and/or nitrosative stress and the resulting damaged targets—are reviewed in this paper. Greater understanding of the decreased functions in brain metabolism in AD and PD is posited to lead to potentially important therapeutic strategies to address both of these disorders, which cause relatively long-lasting decreased quality of life in patients.

Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson’s Disease: Current View

Cognitive impairment (CI) ranging from mild cognitive impairment (MCI) to dementia is a common and disturbing complication in patients with Parkinson’s disease (PD). Numerous studies have focused on neuropathological mechanisms underlying CI in PD, along with the identification of specific biomarkers for CI. Magnetic resonance imaging (MRI), a promising method, has been adopted to examine the changes in the brain and identify the candidate biomarkers associated with CI. In this review, we have summarized the potential biomarkers for CI in PD which have been identified through multi-modal MRI studies. Structural MRI technology is widely used in biomarker research. Specific patterns of gray matter atrophy are promising predictors of the evolution of CI in patients with PD. Moreover, other MRI techniques, such as MRI related to small-vessel disease, neuromelanin-sensitive MRI, quantitative susceptibility mapping, MR diffusion imaging, MRI related to cerebrovascular abnormality, resting-state functional MRI, and proton magnetic resonance spectroscopy, can provide imaging features with a good degree of prediction for CI. In the future, novel combined biomarkers should be developed using the recognized analysis tools and predictive algorithms in both cross-sectional and longitudinal studies.

Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson's disease

Though Parkinson's disease is primarily defined as a movement disorder, it is also characterized by a range of non-motor symptoms, including cognitive decline. The onset and progression of cognitive decline in individuals with Parkinson's disease is variable, and the neurobiological mechanisms that contribute to, or protect against, cognitive decline in Parkinson's disease are poorly understood. Using resting-state functional magnetic resonance imaging data collected from individuals with Parkinson's disease with and without cognitive decline, we examined the relationship between topological brain-network resilience and cognition in Parkinson's disease. By leveraging network attack analyses, we demonstrate that relative to individuals with Parkinson's disease experiencing cognitive decline, the frontoparietal network in cognitively stable individuals with Parkinson's disease is significantly more resilient to network perturbation. Our findings suggest that the topological robustness of the frontoparietal network is associated with the absence of cognitive decline in individuals with Parkinson's disease.

Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease

This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.

In vivo cholinergic basal forebrain degeneration and cognition in Parkinson's disease: Imaging results from the COPPADIS study

INTRODUCTION

We aimed to assess associations between multimodal neuroimaging measures of cholinergic basal forebrain (CBF) integrity and cognition in Parkinson's disease (PD) without dementia.

METHODS

The study included a total of 180 non-demented PD patients and 45 healthy controls, who underwent structural MRI acquisitions and standardized neurocognitive assessment through the PD-Cognitive Rating Scale (PD-CRS) within the multicentric COPPADIS-2015 study. A subset of 73 patients also had Diffusion Tensor Imaging (DTI) acquisitions. Volumetric and microstructural (mean diffusivity, MD) indices of CBF degeneration were automatically extracted using a stereotactic CBF atlas. For comparison, we also assessed multimodal indices of hippocampal degeneration. Associations between imaging measures and cognitive performance were assessed using linear models.

RESULTS

Compared to controls, CBF volume was not significantly reduced in PD patients as a group. However, across PD patients lower CBF volume was significantly associated with lower global cognition (PD-CRS_total: r = 0.37, p < 0.001), and this association remained significant after controlling for several potential confounding variables (p = 0.004). Analysis of individual item scores showed that this association spanned executive and memory domains. No analogue cognition associations were observed for CBF MD. In covariate-controlled models, hippocampal volume was not associated with cognition in PD, but there was a significant association for hippocampal MD (p = 0.02).

CONCLUSIONS

Early cognitive deficits in PD without dementia are more closely related to structural MRI measures of CBF degeneration than hippocampal degeneration. In our multicentric imaging acquisitions, DTI-based diffusion measures in the CBF were inferior to standard volumetric assessments for capturing cognition-relevant changes in non-demented PD.

Visual hallucinations

Visual hallucinations have intrigued neurologists and physicians for generations due to patients' vivid and fascinating descriptions. They are most commonly associated with Parkinson's disease and dementia with Lewy bodies, but also occur in people with visual loss, where they are known as Charles Bonnet syndrome. More rarely, they can develop in other neurological conditions, such as thalamic or midbrain lesions, when they are known as peduncular hallucinosis. This review considers the mechanisms underlying visual hallucinations across diagnoses, including visual loss, network dysfunction across the brain and changes in neurotransmitters. We propose a framework to explain why visual hallucinations occur most commonly in Parkinson's disease and dementia with Lewy bodies, and discuss treatment approaches to visual hallucinations in these conditions.

Visual Dysfunction Predicts Cognitive Impairment and White Matter Degeneration in Parkinson's Disease

BACKGROUND

Visual dysfunction predicts dementia in Parkinson's disease (PD), but whether this translates to structural change is not known. The objectives of this study were to identify longitudinal white matter changes in patients with Parkinson's disease and low visual function and also in those who developed mild cognitive impairment.

METHODS

We used fixel-based analysis to examine longitudinal white matter change in PD. Diffusion MRI and clinical assessments were performed in 77 patients at baseline (22 low visual function/55 intact vision and 13 PD-mild cognitive impairment/51 normal cognition) and 25 controls and again after 18 months. We compared microstructural changes in fiber density, macrostructural changes in fiber bundle cross-section and combined fiber density and cross-section, across white matter, adjusting for age, sex, and intracranial volume.

RESULTS

Patients with PD and visual dysfunction showed worse cognitive performance at follow-up and were more likely to develop mild cognitive impairment compared with those with normal vision (P = 0.008). Parkinson's with poor visual function showed diffuse microstructural and macrostructural changes at baseline, whereas those with mild cognitive impairment showed fewer baseline changes. At follow-up, Parkinson's with low visual function showed widespread macrostructural changes, involving the fronto-occipital fasciculi, external capsules, and middle cerebellar peduncles bilaterally. No longitudinal change was seen in those with mild cognitive impairment at baseline or converters, even when the 2 groups were combined.

CONCLUSION

Parkinson's patients with poor visual function show increased white matter damage over time, providing further evidence for visual function as a marker of imminent cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prefrontal and hippocampal atrophy using 7-tesla magnetic resonance imaging in patients with Parkinson's disease

Background

The pathology of Parkinson's disease leads to morphological changes in brain structure. Currently, the progressive changes in gray matter volume that occur with time and are specific to patients with Parkinson's disease, compared to healthy controls, remain unclear. High-tesla magnetic resonance imaging might be useful in differentiating neurological disorders by brain cortical changes.

Purpose

We aimed to investigate patterns in gray matter changes in patients with Parkinson's disease by using an automated segmentation method with 7-tesla magnetic resonance imaging.

Material and Methods

High-resolution T1-weighted 7 tesla magnetic resonance imaging volumes of 24 hemispheres were acquired from 12 Parkinson's disease patients and 12 age- and sex-matched healthy controls with median ages of 64.5 (range, 41-82) years and 60.5 (range, 25-74) years, respectively. Subgroup analysis was performed according to whether axial motor symptoms were present in the Parkinson's disease patients. Cortical volume, cortical thickness, and subcortical volume were measured using a high-resolution image processing technique based on the Desikan-Killiany-Tourville atlas and an automated segmentation method (FreeSurfer version 6.0).

Results

After cortical reconstruction, in 7 tesla magnetic resonance imaging volume segmental analysis, compared with the healthy controls, the Parkinson's disease patients showed global cortical atrophy, mostly in the prefrontal area (rostral middle frontal, superior frontal, inferior parietal lobule, medial orbitofrontal, rostral anterior cingulate area), and subcortical volume atrophy in limbic/paralimbic areas (fusiform, hippocampus, amygdala).

Conclusion

We first demonstrated that 7 tesla magnetic resonance imaging detects structural abnormalities in Parkinson's disease patients compared to healthy controls using an automated segmentation method. Compared with the healthy controls, the Parkinson's disease patients showed global prefrontal cortical atrophy and hippocampal area atrophy.

Neuroanatomical changes in early Parkinson's disease with mild cognitive impairment: a VBM study; the Parkinson's Disease Cognitive Impairment Study (PaCoS)

INTRODUCTION

Mild cognitive impairment (MCI) is common in Parkinson's disease (PD), but the underlying pathological mechanism has not been fully understood. Voxel-based morphometry could be used to evaluate regional atrophy and its relationship with cognitive performances in early PD-MCI.

PATIENTS AND METHODS

One hundred and six patients with PD were recruited from a larger cohort of patients, the Parkinson's Disease Cognitive Impairment Study (PaCoS). Subject underwent a T1-3D MRI and a complete clinical and neuropsychological evaluation. Patients were divided into PD with normal cognition (PD-NC) and PD-MCI according to the MDS level II criteria-modified for PD-MCI. A subgroup of early patients with short disease duration (≤ 2 years) was also identified. VBM analysis between PD-NC and PD-MCI and between early PD-NC and PD-MCI was performed using two-sample t tests with whole-brain statistical threshold of p < 0.001 uncorrected in the entire PD group and p < 0.05 FWE inside ROIs, in the early PD.

RESULTS

Forty patients were diagnosed with MCI and 66 were PD-NC. PD-MCI patients showed significant gray matter (GM) reduction in several brain regions, including frontal gyrus, precuneus, angular gyrus, temporal lobe, and cerebellum. Early PD-MCI showed reduction in GM density in superior frontal gyrus and cerebellum. Moreover, correlation analysis between neuropsychological performances and GM volume of early PD-MCI patients showed associations between performances of Raven and superior frontal gyrus volume, Stroop time and inferior frontal gyrus volume, accuracy of Barrage and volume of precuneus.

CONCLUSION

The detection of frontal and cerebellar atrophy, even at an early stage, could be used as an early marker of PD-related cognitive impairment.

The corticolimbic structural covariance network as an early predictive biosignature for cognitive impairment in Parkinson's disease

Structural covariance assesses similarities in gray matter between brain regions and can be applied to study networks of the brain. In this study, we explored correlations between structural covariance networks (SCNs) and cognitive impairment in Parkinson’s disease patients. 101 PD patients and 58 age- and sex-matched healthy controls were enrolled in the study. For each participant, comprehensive neuropsychological testing using the Wechsler Adult Intelligence Scale-III and Cognitive Ability Screening Instrument were conducted. Structural brain MR images were acquired using a 3.0T whole body GE Signa MRI system. T1 structural images were preprocessed and analyzed using Statistical Parametric Mapping software (SPM12) running on Matlab R2016a for voxel-based morphometric analysis and SCN analysis. PD patients with normal cognition received follow-up neuropsychological testing at 1-year interval. Cognitive impairment in PD is associated with degeneration of the amygdala/hippocampus SCN. PD patients with dementia exhibited increased covariance over the prefrontal cortex compared to PD patients with normal cognition (PDN). PDN patients who had developed cognitive impairment at follow-up exhibited decreased gray matter volume of the amygdala/hippocampus SCN in the initial MRI. Our results support a neural network-based mechanism for cognitive impairment in PD patients. SCN analysis may reveal vulnerable networks that can be used to early predict cognitive decline in PD patients.

The Human Hippocampus in Parkinson's Disease: An Integrative Stereological and Proteomic Study

BACKGROUND

Parkinson's disease (PD) is a prevalent neurodegenerative disease that is pathologically described as a six-stage α-synucleinopathy. In stage 4, α-synuclein reaches the hippocampus, inducing cognitive deficits, from which it progresses to the isocortex, leading to dementia. Among hippocampal fields, cornu ammonis 2 is particularly affected by this α-synucleinopathy and critical for cognitive decline. Volumetric studies using magnetic resonance imaging have produced controversial results, with only some reporting volume loss, whereas stereological data obtained using nonspecific markers do not reveal volume changes, neural or glial loss. Proteomic analysis has not been carried out in the hippocampus of patients with PD.

OBJECTIVE

This study aims to explain hippocampal changes in patients with PD at the cellular and proteomic levels.

METHODS

α-Synuclein inclusions, volume and neural (NeuN), microglial (Iba-1) and astroglial (GFAP) populations were stereologically analyzed. SWATH-MS quantitative proteomic analysis was also conducted.

RESULTS

Area fraction fractionator probe revealed a higher area fraction α-synucleinopathy in cornu ammonis 2. No volume change, neurodegeneration, microgliosis or astrogliosis was detected. Proteomic analysis identified 1,634 proteins, of which 83 were particularly useful for defining differences among PD and non-PD groups. Among them, upregulated (PHYIP, CTND2, AHSA1 and SNTA1) and downregulated (TM163, REEP2 and CSKI1) proteins were related to synaptic structures in the diseased hippocampus.

CONCLUSION

The distribution of α-synuclein in the hippocampus is not associated with volumetric, neural or glial changes. Proteomic analysis, however, reveals a series of changes in proteins associated with synaptic structures, suggesting that hippocampal changes occur at the synapse level during PD.

Differential Changes in Arteriolar Cerebral Blood Volume between Parkinson's Disease Patients with Normal and Impaired Cognition and Mild Cognitive Impairment (MCI) Patients without Movement Disorder - An Exploratory Study

Cognitive impairment amongst Parkinson's disease (PD) patients is highly prevalent and associated with an increased risk of dementia. There is growing evidence that altered cerebrovascular functions contribute to cognitive impairment. Few studies have compared cerebrovascular changes in PD patients with normal and impaired cognition and those with mild-cognitive-impairment (MCI) without movement disorder. Here, we investigated arteriolar-cerebral-blood-volume (CBVa), an index reflecting the homeostasis of the most actively regulated segment in the microvasculature, using advanced MRI in various brain regions in PD and MCI patients and matched controls. Our goal is to find brain regions with altered CBVa that are specific to PD with normal and impaired cognition, and MCI-without-movement-disorder, respectively. In PD patients with normal cognition (n=10), CBVa was significantly decreased in the substantia nigra, caudate and putamen when compared to controls. In PD patients with impaired cognition (n=6), CBVa showed a decreasing trend in the substantia nigra, caudate and putamen, but was significantly increased in the presupplementary motor area and intracalcarine gyrus compared to controls. In MCI-patients-without-movement-disorder (n=18), CBVa was significantly increased in the caudate, putamen, hippocampus and lingual gyrus compared to controls. These findings provide important information for efforts towards developing biomarkers for the evaluation of potential risk of PD dementia (PDD) in PD patients. The current study is limited in sample size and therefore is exploratory in nature. The data from this pilot study will serve as the basis for power analysis for subsequent studies to further investigate and validate the current findings.

Altered Functional Network Associated With Cognitive Performance in Early Parkinson Disease Measured by Eigenvector Centrality Mapping

Objective: To investigate relationships between whole-brain functional changes and the performance of multiple cognitive functions in early Parkinson’s disease (PD).

Methods: In the current study, we evaluated resting-state functional MRI (rsfMRI) data and neuropsychological assessments for various cognitive functions in a cohort with 84 early PD patients from the Parkinson’s Progression Markers Initiative (PPMI). Eigenvector centrality (EC) mapping based on rsfMRI was used to identify the functional connectivity of brain areas correlated with different neuropsychological scores at a whole-brain level.

Results: Our study demonstrated that in the early PD patients, scores of Letter Number Sequencing (LNS) were positively correlated with EC in the left inferior occipital gyrus (IOG) and lingual gyrus. The immediate recall scores of Hopkins Verbal Learning Test-Revised (HVLT-R) were positively correlated with EC in the left superior frontal gyrus. No correlation was found between the EC and other cognitive performance scores.

Conclusions: Functional alternations in the left occipital lobe (inferior occipital and lingual gyrus) and left superior frontal gyrus may account for the performance of working memory and immediate recall memory, respectively in early PD. These results may broaden the understanding of the potential mechanism of cognitive impairments in early PD.

Dementia risk in Parkinson's disease is associated with interhemispheric connectivity loss and determined by regional gene expression

Parkinson's dementia is a common and devastating part of Parkinson's disease. Whilst timing and severity vary, dementia in Parkinson's is often preceded by visual dysfunction. White matter changes, representing axonal loss, occur early in the disease process. Clarifying which white matter connections are affected in Parkinson's with visual dysfunction and why specific connections are vulnerable will provide important mechanistic insights. Here, we use diffusion tractography in 100 Parkinson's patients (33 low visual performers) and 34 controls to identify patterns of connectivity loss in Parkinson's with visual dysfunction. We examine the relationship between regional transcription and connectivity loss, using the Allen Institute for Brain Science transcriptome atlas. We show that interhemispheric connections are preferentially affected in Parkinson's low visual performers. Interhemispheric connection loss was associated with downweighted genes related to the smoothened signalling pathway (enriched in glutamatergic neurons) and upweighted metabolic genes. Risk genes for Parkinson's but not Alzheimer's or Dementia with Lewy bodies were over-represented in upweighted genes associated with interhemispheric connection loss. Our findings suggest selective vulnerability in Parkinson's patients at highest risk of dementia (those with visual dysfunction), where differences in gene expression and metabolic dysfunction, affecting longer connections with higher metabolic burden, drive connectivity loss.

Discrete changes in brain volume after deep brain stimulation in patients with Parkinson's disease

OBJECTIVES

Deep brain stimulation (DBS), targeting the subthalamic nucleus (STN) and globus pallidus interna, is a surgical therapy with class 1 evidence for Parkinson's disease (PD). Bilateral DBS electrodes may be implanted within a single operation or in separate staged surgeries with an interval of time that varies patient by patient. In this study, we used the variation in the timing of implantation from the first to the second implantation allowing for examination of potential volumetric changes of the basal ganglia in patients with PD who underwent staged STN DBS.

METHODS

Thirty-two patients with a mean time interval between implantations of 141.8 (±209.1; range: 7-700) days and mean duration of unilateral stimulation of 244.7 (±227.7; range: 20-672) days were included in this study. Using volumetric analysis of whole hemisphere and subcortical structures, we observed whether implantation or stimulation affected structural volume.

RESULTS

We observed that DBS implantation, but not the duration of stimulation, induced a significant reduction of volume in the caudate, pallidum, putamen and thalamus ipsilateral to the implanted hemisphere. These findings were not dependent on the trajectory of the implanted electrode nor on first surgery pneumocephalus (0.07%: %Δ for intracranial volume between first and second surgery). In addition, unique regional atrophy differences were evident in each of the structures.

CONCLUSION

Our results demonstrate that DBS implantation surgery may affect hemisphere volume at the level of subcortical structures connected to the surgical target.

Progressive brain atrophy and clinical evolution in Parkinson's disease

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Cortical and subcortical atrophy is accelerated early after the onset of PD.

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Brain atrophy in PD progressed with cognitive, non-motor and mood deficits.

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Structural MRI may be useful for predicting disease progression in PD.

Clinical manifestations and evolution are very heterogeneous among individuals with Parkinson’s disease (PD). The aims of this study were to investigate the pattern of progressive brain atrophy in PD according to disease stage and to elucidate to what extent cortical thinning and subcortical atrophy are related to clinical motor and non-motor evolution. 154 patients at different PD stages were assessed over time using motor, non-motor and structural MRI evaluations for a maximum of 4 years. Cluster analysis defined clinical subtypes. Cortical thinning and subcortical atrophy were assessed at baseline in patients relative to 60 healthy controls. Longitudinal trends of brain atrophy progression were compared between PD clusters. The contribution of brain atrophy in predicting motor, non-motor, cognitive and mood deterioration was explored. Two main PD clusters were defined: mild (N = 87) and moderate-to-severe (N = 67). Two mild subtypes were further identified: mild motor-predominant (N = 43) and mild-diffuse (N = 44), with the latter group being older and having more severe non-motor and cognitive symptoms. The initial pattern of brain atrophy was more severe in patients with moderate-to-severe PD. Over time, mild-diffuse PD patients had the greatest brain atrophy accumulation in the cortex and the left hippocampus, while less distributed atrophy progression was observed in moderate-to-severe and mild motor-predominant patients. Baseline and 1-year cortical thinning was associated with long-term progression of motor, cognitive, non-motor and mood symptoms. Cortical and subcortical atrophy is accelerated early after the onset of PD and becomes prominent in later stages of disease according to the development of cognitive, non-motor and mood dysfunctions. Structural MRI may be useful for monitoring and predicting disease progression in PD.

Effects of Levodopa on Impairments to High-Level Vision in Parkinson's Disease

Studies have reported that Parkinson's disease (PD) is associated with impairments on cognitive visual tasks. However, the effects of dopamine on cognitive vision remain equivocal. The purpose of this study was to examine performance on cognitive vision tasks in persons with PD and the effects of levodopa on these tasks. Fourteen individuals with PD and 14 age- and sex-matched healthy older adults completed the study. Participants with PD completed the visual tasks following a 12-h withdrawal of dopaminergic medication and again 1 h after taking 1.5 times their normal dose of levodopa. Healthy older adults completed the visual tasks twice using the same session format. Five complex visual tasks were completed, including line discrimination, object discrimination, facial discrimination, visual working memory, and object rotation. The Unified Parkinson's Disease Rating Scale was also collected off and on medication. Participants with PD performed significantly worse than the healthy older adults across all five visual tasks. There were no significant differences in performance between the off and on medication state in persons with PD. This finding indicates either that dopamine deficiency may not be responsible for cognitive visual impairments in PD or that cognitive visual impairments in PD might simply be the result of deficits in more basic visual processing.

[Clinical and neurophysiological effects of dual-target high-frequency rTMS over the primary motor and prefrontal cortex in Parkinson's disease]

OBJECTIVE

To evaluate therapeutic effects of navigational dual-target high-frequency rTMS over the primary motor (M1, bilateral) and the left dorsolateral prefrontal cortex (DLPFC) on clinical dynamics of Parkinson's disease (PD) symptoms in a parallel placebo-controlled study.

MATERIAL AND METHODS

The study included 46 patients randomized into equal therapeutic and placebo rTMS groups. Navigational therapeutic and placebo10 Hz rTMS was applied over the M1 and DLPFC areas (20 daily sessions, for 3 weeks). Assessment of the dynamics of clinical symptoms was performed using the MDS UPDRS scale (Parts I-IV) before the first session, immediately after 20 sessions, and 4-6 weeks after the rTMS course. Non-motor and mental symptoms were assessed using the Hamilton Depression Rating Scale (HDRS-17), Beck depression inventory (BDI-II), Depression, Anxiety and Stress (DASS-21) scales and the Mini Mental State Examination (MMSE).

RESULTS

Significant therapeutic effects of rTMS compared to placebo were established: a greater decrease in overall score on the MDS-UPDRS scale (parts I-IV), a decrease in the severity of non-motor (part I) and motor symptoms (part III, with a large therapeutic effect for the symptoms of rigidity, bradykinesia and postural instability), as well as the severity of motor complications of dopamine replacement therapy (part IV). The effects of rTMS on motor symptoms persisted 4 weeks after the end of the stimulation course. It is also important to note significant positive dynamics in both rTMS and placebo groups in the form of comparable reduction in the severity of everyday motor symptoms (MDS-UPDRS part II), improvement of the total scores on MMSE, HDRS, BDI-II, DASS-21.

CONCLUSIONS

The dual-target high-frequency rTMS over the primary motor cortex (bilateral) and the left dorsolateral prefrontal cortex has positive therapeutic effects on the motor and affective symptoms of Parkinson's disease, which are significantly stronger than that of the placebo stimulation.

Voxel-wise meta-analysis of structural changes in gray matter of Parkinson's disease patients with mild cognitive impairment

Evidence from previous voxel-based morphometry (VBM) studies indicates that widespread brain regions are involved in Parkinson’s disease with mild cognitive impairment (PD-MCI). However, the spatial localization reported for gray matter (GM) abnormalities is heterogeneous. The aim of the present study was to quantitatively integrate studies on GM abnormalities observed in PD-MCI in order to determine whether a pattern exists. Eligible whole-brain VBM studies were identified by a systematic search of articles in PubMed and EMBASE databases spanning from 1995 to January 1, 2019. A meta-analysis was performed to investigate regional GM abnormalities in PD-MCI. The anisotropic effect size version of seed-based d mapping (AES-SDM) meta-analysis was conducted to explore the GMV differences of PD-MCI compared with PD patients with normal cognitive function (PD-NC). A total of 12 studies comprising 243 PD-MCI patients and 326 PD-NC were included in the meta-analysis. PD-MCI patients showed a robust GM decrease in the left insula and left superior temporal gyrus. Moreover, meta-regression analysis demonstrated that age, PD duration and stage, and Unified Parkinson’s Disease Rating Scale III and Mini-Mental State Examination scores might be partly correlated with the GM abnormalities observed in PD-MCI patients. The convergent findings of this quantitative meta-analysis revealed a characteristic neuroanatomical pattern in PD-MCI. The findings provide some evidence that MCI in PD may result in the breakdown of the insula and temporal gyrus, which may serve as specific regions of interest for further investigations.

Increased CSF NFL in Non-demented Parkinson's Disease Subjects Reflects Early White Matter Damage

Parkinson's disease (PD) is a chronic neurodegenerative disorder with various underlying pathological processes. Until now, no fluid biomarkers have been established for PD. Given recent biochemical and neuroimaging evidence for the presence of white matter damage in PD, which may even precede neuronal loss, we investigated whether neurofilament light (NFL) was increased in the cerebrospinal fluid (CSF) of PD patients in comparison to controls. NFL is located mainly in large myelinated axons, and increased CSF levels of this protein reflect axonal injury. CSF levels of NFL in 58 early PD patients and 28 controls were quantified by ELISA (Uman Diagnostics). Measures of PD severity included disease duration, UPDRS-III, and Hoehn-Yahr stage. Statistically significant differences in CSF NFL levels were found between PD patients and controls [median with interquartile range 524.82 (393.28-678.34) vs. 271.84 (198.09-335.24) ng/l; p < 0.05)]. In PD patients, there were no correlations between CSF NFL level and the measures of disease severity. The CSF NFL turned out to have a high discriminatory value (AUC 0.850) for differentiating between PD subjects and healthy controls, with 84% sensitivity and 85.2% specificity. The study indirectly demonstrates that axonal damage is present in early PD in addition to neuronal loss. Interestingly, white matter damage was observed in non-demented PD patients. In the light of the results of recent MRI studies which confirm early white matter damage in PD, our data may turn out to be potentially useful in the diagnosis of early, or even preclinical, stages of the disease.

Test-retest reliability and sample size estimates after MRI scanner relocation

OBJECTIVE

Many factors can contribute to the reliability and robustness of MRI-derived metrics. In this study, we assessed the reliability and reproducibility of three MRI modalities after an MRI scanner was relocated to a new hospital facility.

METHODS

Twenty healthy volunteers (12 females, mean age (standard deviation) ​= ​41 (11) years, age range [25-66]) completed three MRI sessions. The first session (S1) was one week prior to the 3T GE HDxt scanner relocation. The second (S2) occurred nine weeks after S1 and at the new location; a third session (S3) was acquired 4 weeks after S2. At each session, we acquired structural T1-weighted, pseudo-continuous arterial spin labelled, and diffusion tensor imaging sequences. We used longitudinal processing streams to create 12 summary MRI metrics, including total gray matter (GM), cortical GM, subcortical GM, white matter (WM), and lateral ventricle volume; mean cortical thickness; total surface area; average gray matter perfusion, and average diffusion tensor metrics along principal white matter pathways. We compared mean MRI values and variance at the old scanner location to multiple sessions at the new location using Bayesian multi-level regression models. K-fold cross validation allowed identification of important predictors. Whole-brain analyses were used to investigate any regional differences. Furthermore, we calculated within-subject coefficient of variation (wsCV), intraclass correlation coefficient (ICC), and dice similarity index (SI) of cortical segmentations across scanner relocation and within-site. Additionally, we estimated sample sizes required to robustly detect a 4% difference between two groups across MRI metrics.

RESULTS

All global MRI metrics exhibited little mean difference and small variability (bar cortical gray matter perfusion) both across scanner relocation and within-site repeat. T1- and DTI-derived tissue metrics showed ​< ​|0.3|% mean difference and <1.2% variance across scanner location and <|0.4|% mean difference and <0.8% variance within the new location, with between-site intraclass correlation coefficient (ICC) ​> ​0.80 and within-subject coefficient of variation (wsCV) ​< ​1.4%. Mean cortical gray matter perfusion had the highest between-session variability (6.7% [0.3, 16.7], estimate [95% uncertainty interval]), and hence the smallest ICC (0.71 [0.44,0.92]) and largest wsCV (13.4% [5.4, 18.1]). No global metric exhibited evidence of a meaningful mean difference between scanner locations. However, surface area showed evidence of a mean difference within-site repeat (between S2 and S3). Whole-brain analyses revealed no significant areas of difference between scanner relocation or within-site. For all metrics, we found no support for a systematic difference in variance across relocation sites compared to within-site test-retest reliability. Necessary sample sizes to detect a 4% difference between two independent groups varied from a maximum of n ​= ​362 per group (cortical gray matter perfusion), to total gray matter volume (n ​= ​114), average fractional anisotropy (n ​= ​23), total gray matter volume normalized by intracranial volume (n ​= ​19), and axial diffusivity (n ​= ​3 per group).

CONCLUSION

Cortical gray matter perfusion was the most variable metric investigated (necessitating large sample sizes to identify group differences), with other metrics showing substantially less variability. Scanner relocation appeared to have a negligible effect on variability of the global MRI metrics tested. This manuscript reports within-site test-retest variability to act as a tool for calculating sample size in future investigations. Our results suggest that when all other parameters are held constant (e.g., sequence parameters and MRI processing), the effect of scanner relocation is indistinguishable from within-site variability, but may need to be considered depending on the question being investigated.

Dynamical Role of Pivotal Brain Regions in Parkinson Symptomatology Uncovered with Deep Learning

BACKGROUND

The release of a broad, longitudinal anatomical dataset by the Parkinson's Progression Markers Initiative promoted a surge of machine-learning studies aimed at predicting disease onset and progression. However, the excessive number of features used in these models often conceals their relationship to the Parkinsonian symptomatology.

OBJECTIVES

The aim of this study is two-fold: (i) to predict future motor and cognitive impairments up to four years from brain features acquired at baseline; and (ii) to interpret the role of pivotal brain regions responsible for different symptoms from a neurological viewpoint.

METHODS

We test several deep-learning neural network configurations, and report our best results obtained with an autoencoder deep-learning model, run on a 5-fold cross-validation set. Comparison with Existing Methods: Our approach improves upon results from standard regression and others. It also includes neuroimaging biomarkers as features.

RESULTS

The relative contributions of pivotal brain regions to each impairment change over time, suggesting a dynamical reordering of culprits as the disease progresses. Specifically, the Putamen is initially the most critical region accounting for the overall cognitive state, only being surpassed by the Substantia Nigra in later years. The Pallidum is the first region to influence motor scores, followed by the parahippocampal and ambient gyri, and the anterior orbital gyrus.

CONCLUSIONS

While the causal link between regional brain atrophy and Parkinson symptomatology is poorly understood, our methods demonstrate that the contributions of pivotal regions to cognitive and motor impairments are more dynamical than generally appreciated.