Ventricular dilatation and brain atrophy in patients with Parkinson's disease with incipient dementia

Structural neuroimaging markers of normal pressure hydrocephalus versus Alzheimer's dementia and Parkinson's disease, and hydrocephalus versus atrophy in chronic TBI-a narrative review

Introduction

Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem.

Methods

By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans.

Results

Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment.

Conclusion

Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.

Third ventricular width by transcranial sonography is associated with cognitive impairment in Parkinson's disease

BACKGROUND

One-fourth of Parkinson's disease (PD) patients suffer from cognitive impairment. However, few neuroimaging markers have been identified regarding cognitive impairment in PD.

OBJECTIVE

This study aimed to explore the association between third ventricular width by transcranial sonography (TCS) and cognitive decline in PD.

METHOD

Participants with PD were recruited from one medical center in China. Third ventricular width was assessed by TCS, and cognitive function was analyzed by the Mini-Mental State Examination (MMSE). Receiver operating characteristic (ROC) analysis and Cox model analysis were utilized to determine the diagnostic and predictive accuracy of third ventricular width by TCS for cognitive decline in PD patients.

RESULT

A total of 174 PD patients were recruited. Third ventricular width was negatively correlated with MMSE scores. ROC analysis suggested that the optimal cutoff point for third ventricular width in screening for cognitive impairment in PD was 4.75 mm (sensitivity 62.7%; specificity 75.6%). After 21.5 (18.0, 26.0) months of follow-up in PD patients without cognitive impairment, it was found that those with a third ventricular width greater than 4.75 mm exhibited a 7.975 times higher risk of developing cognitive impairment [hazard ratio = 7.975, 95% CI 1.609, 39.532, p = 0.011] compared with patients with a third ventricular width less than 4.75 mm.

CONCLUSION

Third ventricular width based on TCS emerged as an independent predictor of developing cognitive impairment in PD patients.

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.

Identifying key multi-modal predictors of incipient dementia in Parkinson's disease: a machine learning analysis and Tree SHAP interpretation

Background

Persons with Parkinson's disease (PD) differentially progress to cognitive impairment and dementia. With a 3-year longitudinal sample of initially non-demented PD patients measured on multiple dementia risk factors, we demonstrate that machine learning classifier algorithms can be combined with explainable artificial intelligence methods to identify and interpret leading predictors that discriminate those who later converted to dementia from those who did not.

Method

Participants were 48 well-characterized PD patients (M_{baseline age} = 71.6; SD = 4.8; 44% female). We tested 38 multi-modal predictors from 10 domains (e.g., motor, cognitive) in a computationally competitive context to identify those that best discriminated two unobserved baseline groups, PD No Dementia (PDND), and PD Incipient Dementia (PDID). We used Random Forest (RF) classifier models for the discrimination goal and Tree SHapley Additive exPlanation (Tree SHAP) values for deep interpretation.

Results

An excellent RF model discriminated baseline PDID from PDND (AUC = 0.84; normalized Matthews Correlation Coefficient = 0.76). Tree SHAP showed that ten leading predictors of PDID accounted for 62.5% of the model, as well as their relative importance, direction, and magnitude (risk threshold). These predictors represented the motor (e.g., poorer gait), cognitive (e.g., slower Trail A), molecular (up-regulated metabolite panel), demographic (age), imaging (ventricular volume), and lifestyle (activities of daily living) domains.

Conclusion

Our data-driven protocol integrated RF classifier models and Tree SHAP applications to selectively identify and interpret early dementia risk factors in a well-characterized sample of initially non-demented persons with PD. Results indicate that leading dementia predictors derive from multiple complementary risk domains.

Dementia Risk Prediction in a Longitudinal Geriatric Parkinson's Disease Cohort: Evaluation and Application of the Montreal Parkinson Risk of Dementia Scale

Background

Parkinson's disease (PD) increases risk for dementia and cascading adverse outcomes. The eight-item Montreal Parkinson Risk of Dementia Scale (MoPaRDS) is a rapid, in-office dementia screening tool. We examine predictive validity and other characteristics of the MoPaRDS in a geriatric PD cohort by testing a series of alternative versions and modelling risk score change trajectories.

Methods

Participants were 48 initially non-demented PD patients (Mage = 71.6 years, range = 65-84) from a three-year, three-wave prospective Canadian cohort study. A dementia diagnosis at Wave 3 was used to stratify two baseline groups: PD with Incipient Dementia (PDID) and PD with No Dementia (PDND). We aimed to predict dementia three years prior to diagnosis using baseline data for eight indicators that harmonized with the original report, plus education.

Results

Three MoPaRDS items (age, orthostatic hypotension, mild cognitive impairment [MCI]) discriminated the groups both independently and as a composite three-item scale (area under the curve [AUC] = 0.88). The eight-item MoPaRDS reliably discriminated PDID from PDND (AUC = 0.81). Education did not improve predictive validity (AUC = 0.77). Performance of the eight-item MoPaRDS varied across sex (AUCfemales = 0.91; AUCmales = 0.74), whereas the three-item configuration did not (AUCfemales = 0.88; AUCmales = 0.91). Risk scores of both configurations increased over time.

Conclusions

We report new data on the application of the MoPaRDS as a dementia prediction tool for a geriatric PD cohort. Results support the viability of the full MoPaRDS, and indicate that an empirically determined brief version is a promising complement.

A systematic review of brain morphometry related to deep brain stimulation outcome in Parkinson's disease

While the efficacy of deep brain stimulation (DBS) is well-established in Parkinson’s Disease (PD), the benefit of DBS varies across patients. Using imaging features for outcome prediction offers potential in improving effectiveness, whereas the value of presurgical brain morphometry, derived from the routinely used imaging modality in surgical planning, remains under-explored. This review provides a comprehensive investigation of links between DBS outcomes and brain morphometry features in PD. We systematically searched PubMed and Embase databases and retrieved 793 articles, of which 25 met inclusion criteria and were reviewed in detail. A majority of studies (24/25), including 1253 of 1316 patients, focused on the outcome of DBS targeting the subthalamic nucleus (STN), while five studies included 57 patients receiving globus pallidus internus (GPi) DBS. Accumulated evidence showed that the atrophy of motor cortex and thalamus were associated with poor motor improvement, other structures such as the lateral-occipital cortex and anterior cingulate were also reported to correlated with motor outcome. Regarding non-motor outcomes, decreased volume of the hippocampus was reported to correlate with poor cognitive outcomes. Structures such as the thalamus, nucleus accumbens, and nucleus of basalis of Meynert were also reported to correlate with cognitive functions. Caudal middle frontal cortex was reported to have an impact on postsurgical psychiatric changes. Collectively, the findings of this review emphasize the utility of brain morphometry in outcome prediction of DBS for PD. Future efforts are needed to validate the findings and demonstrate the feasibility of brain morphometry in larger cohorts.

Brain ventricles, CSF and cognition: a narrative review

The brain ventricles are structures that have been related to cognition since antiquity. They are essential components in the development and maintenance of brain functions. The aging process runs with the enlargement of ventricles and is related to a less selective blood-cerebrospinal fluid barrier and then a more toxic cerebrospinal fluid environment. The study of brain ventricles as a biological marker of aging is promissing because they are structures easily identified in neuroimaging studies, present good inter-rater reliability, and measures of them can identify brain atrophy earlier than cortical structures. The ventricular system also plays roles in the development of dementia, since dysfunction in the clearance of beta-amyloid protein is a key mechanism in sporadic Alzheimer's disease. The morphometric and volumetric studies of the brain ventricles can help to distinguish between healthy elderly and persons with mild cognitive impairment (MCI) and dementia. Brain ventricle data may contribute to the appropriate allocation of individuals in groups at higher risk for MCI-dementia progression in clinical trials and to measuring therapeutic responses in these studies, as well as providing differential diagnosis, such as normal pressure hydrocephalus. Here, we reviewed the pathophysiology of healthy aging and cognitive decline, focusing on the role of the choroid plexus and brain ventricles in this process.

The Value of Shunt Surgery or Prophylactic Antiepileptic Therapy or Both in the Development of Dementia at Early Stages in Patients With Ventricular Dilatation

The primary purpose of the current study was to determine the value of the shunt surgery and/or prophylactic antiepileptic therapy, in patients after mild traumatic brain injury (mTBI) with ventricular dilatation (VD) and incipient cognitive impairment, in the prevention of cognitive deterioration and probably in the development of dementia.

Based on the following criteria: a) mTBI b) VD detected in CT scan during admission, and c) the presence of one of the following: i) dizziness, ii) headache, and iii) seizures, admitted to the Emergency Department between January 2010 and January 2020, we enrolled 127 of 947 eligible subjects.

The subjects were divided into five groups: Group A (control group): only VD illustration in CT scan, Group B: incipient dementia, who had a more insidious onset presenting with cognitive dysfunctions at indefinite ages, Group C: shunt system (SH)/antiepileptic drugs (AEDs) presenting with cognitive dysfunction and urinary incontinence or gait disturbances or both, that were treated as idiopathic normal-pressure hydrocephalus (iNPH) with the surgical placement of an SH and AED therapy (standard AED phenytoin (1000 mg loading dose followed by 300 mg) daily), and Group D: AED, presenting with cognitive dysfunctions at indefinite ages and one or two episodes of seizures in the past, treated with AED from the very first moment of initiation with a standard AED phenytoin (1000 mg loading dose followed by 300 mg) daily.

Overall, improvement in daily activities was achieved in 14.1% (18 of 127 patients), recording a significantly higher performance in group D (5.5%) rather than in groups A (1.5%), B (3.1%), and C (3.9%), (p < 0.05). We concluded that changes in VD (ΔVD) were associated with improvement in mRS (ΔmRS ≥ 1) - daily activities and mental status. ΔVD was also independently associated with reduced daily activities during the long-term follow-up. Interestingly, therapeutic shunting and AED in patients with a history of epilepsies may have a positive impact on the development of mental status impairment. This is a novel observation that has to be confirmed by more extensive multicenter studies in the future.

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.

Decreased Brain Ventricular Volume in Psychiatric Inpatients with Serotonin Reuptake Inhibitor Treatment

Background

Brain ventricles have been reported to be enlarged in several neuropsychiatric disorders and in aging. Whether human cerebral ventricular volume can decrease over time with psychiatric treatment is not well-studied. The aim of this study was to examine whether inpatients taking serotonin reuptake inhibitors (SRI) exhibited reductions in cerebral ventricular volume.

Methods

Psychiatric inpatients, diagnosed mainly with depression, substance use, anxiety, and personality disorders, underwent two imaging sessions (Time 1 and Time 2, approximately 4 weeks apart). FreeSurfer was used to quantify volumetric features of the brain, and ANOVA was used to analyze ventricular volume differences between Time 1 and Time 2. Inpatients' brain ventricle volumes were normalized by dividing by estimated total intracranial volume (eTIV). Clinical features such as depression and anxiety levels were collected at Time 1, Time 1.5 (approximately 2 weeks apart), and Time 2.

Results

Inpatients consistently taking SRIs (SRI + , n = 44) showed statistically significant reductions of brain ventricular volumes particularly for their left and right lateral ventricular volumes. Reductions in their third ventricular volume were close to significance (p = .068). The inpatients that did not take SRIs (SRI-, n = 25) showed no statistically significant changes in brain ventricular volumes. The SRI + group also exhibited similar brain structural features to the healthy control group based on the 90% confidence interval comparsions on brain ventricular volume parameters, whereas the SRI- group still exhibited relatively enlarged brain ventricular volumes after treatment.

Conclusions

SRI treatment was associated with decreased brain ventricle volume over treatment.

Multilevel Survival Modeling with Structured Penalties for Disease Prediction from Imaging Genetics data

This paper introduces a framework for disease prediction from multimodal genetic and imaging data. We propose a multilevel survival model which allows predicting the time of occurrence of a future disease state in patients initially exhibiting mild symptoms. This new multilevel setting allows modeling the interactions between genetic and imaging variables. This is in contrast with classical additive models which treat all modalities in the same manner and can result in undesirable elimination of specific modalities when their contributions are unbalanced. Moreover, the use of a survival model allows overcoming the limitations of previous approaches based on classification which consider a fixed time frame. Furthermore, we introduce specific penalties taking into account the structure of the different types of data, such as a group lasso penalty over the genetic modality and a L2-penalty over the imaging modality. Finally, we propose a fast optimization algorithm, based on a proximal gradient method. The approach was applied to the prediction of Alzheimer's disease (AD) among patients with mild cognitive impairment (MCI) based on genetic (single nucleotide polymorphisms - SNP) and imaging (anatomical MRI measures) data from the ADNI database. The experiments demonstrate the effectiveness of the method for predicting the time of conversion to AD. It revealed how genetic variants and brain imaging alterations interact in the prediction of future disease status. The approach is generic and could potentially be useful for the prediction of other diseases.

Comprehensive Serum Lipidomics for Detecting Incipient Dementia in Parkinson's Disease

While a number of methods are available for analyzing lipids, unbiased untargeted lipidomics with high coverage remains a challenge. In this work, we report a study of isotope-standard-assisted liquid chromatography mass spectrometry lipidomics of serum for biomarker discovery. We focus on Parkinson's disease (PD), a neurodegenerative disorder that often progresses to dementia. Currently, the diagnosis of PD is purely clinical and there is limited ability to predict which PD patients will transition to dementia, hampering early interventions. We studied serum samples from healthy controls and PD patients with no clinical signs of dementia. A follow-up 3 years later revealed that a subset of PD patients had transitioned to dementia. Using the baseline samples, we constructed two biomarker panels to differentiate (1) PD patients from healthy controls and (2) PD patients that remained cognitively stable from PD patients with incipient dementia (diagnosed 3 years after sample collection). The proposed biomarker panels displayed excellent performance and may be useful for detecting prodromal PD dementia, allowing early interventions and prevention efforts. The biochemistry of significantly changed lipids is also discussed within the current knowledge of neurological pathologies. Our results are promising and future work using a larger cohort of samples is warranted.

Cognitive impairment in Parkinson's disease: A clinical and pathophysiological overview

Cognitive dysfunction in Parkinson's disease (PD) has received increasing attention, and, together with other non-motor symptoms, exert a significant functional impact in the daily lives of patients. This article aims to compile and briefly summarize selected published data about clinical features, cognitive evaluation, biomarkers, and pathophysiology of PD-related dementia (PDD). The literature search included articles indexed in the MEDLINE/PubMed database, published in English, over the last two decades. Despite significant progress on clinical criteria and cohort studies for PD-mild cognitive impairment (PD-MCI) and PDD, there are still knowledge gaps about its exact molecular and pathological basis. Here we overview the scientific literature on the role of functional circuits, neurotransmitter systems (monoaminergic and cholinergic), basal forebrain, and brainstem nuclei dysfunction in PD-MCI. Correlations between neuroimaging and cerebrospinal fluid (CSF) biomarkers, clinical outcomes, and pathological results are described to aid in uncovering the neurodegeneration pattern in PD-MCI and PDD.

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.

Cognitive and motor correlates of grey and white matter pathology in Parkinson's disease

INTRODUCTION

Previous studies have found associations between grey matter atrophy and white matter hyperintensities (WMH) of vascular origin with cognitive and motor deficits in Parkinson's disease (PD). Here we investigate these relationships in a sample of PD patients and age-matched healthy controls.

METHODS

Data included 50 PD patients and 45 age-matched controls with T1-weighted and FLAIR scans at baseline, 18-months, and 36-months follow-up. Deformation-based morphometry was used to measure grey matter atrophy. SNIPE (Scoring by Nonlocal Image Patch Estimator) was used to measure Alzheimer's disease-like textural patterns in the hippocampi. WMHs were segmented using T1-weighted and FLAIR images. The relationship between MRI features and clinical scores was assessed using mixed-effects models. The motor subscore of the Unified Parkinson's Disease Rating Scale (UPDRSIII), number of steps in a walking trial, and Dementia Rating Scale (DRS) were used respectively as measures of motor function, gait, and cognition.

RESULTS

Substantia nigra atrophy was significantly associated with motor deficits, with a greater impact in PDs (p < 0.05). Hippocampal SNIPE scores were associated with cognitve decline in both PD and controls (p < 0.01). WMH burden was significantly associated with cognitive decline and increased motor deficits in the PD group, and gait deficits in both PD and controls (p < 0.03).

CONCLUSION

While substantia nigra atrophy and WMH burden were significantly associated with additional motor deficits, WMH burden and hippocampal atrophy were associated with cognitive deficits in PD patients. These results suggest an additive contribution of both grey and white matter damage to the motor and cognitive deficits in PD.

Neuroanatomical Changes in Leber's Hereditary Optic Neuropathy: Clinical Application of 7T MRI Submillimeter Morphometry

Leber’s hereditary optic neuropathy (LHON) is one of the mitochondrial diseases that causes loss of central vision, progressive impairment and subsequent degeneration of retinal ganglion cells (RGCs). In recent years, diffusion tensor imaging (DTI) studies have revealed structural abnormalities in visual white matter tracts, such as the optic tract, and optic radiation. However, it is still unclear if the disease alters only some parts of the white matter architecture or whether the changes also affect other subcortical areas of the brain. This study aimed to improve our understanding of morphometric changes in subcortical brain areas and their associations with the clinical picture in LHON by the application of a submillimeter surface-based analysis approach to the ultra-high-field 7T magnetic resonance imaging data. To meet these goals, fifteen LHON patients and fifteen age-matched healthy subjects were examined. For all individuals, quantitative analysis of the morphometric results was performed. Furthermore, morphometric characteristics which differentiated the groups were correlated with variables covering selected aspects of the LHON clinical picture. Compared to healthy controls (HC), LHON carriers showed significantly lower volume of both palladiums (left p = 0.023; right p = 0.018), the right accumbens area (p = 0.007) and the optic chiasm (p = 0.014). Additionally, LHON patients have significantly higher volume of both lateral ventricles (left p = 0.034; right p = 0.02), both temporal horns of the lateral ventricles (left p = 0.016; right p = 0.034), 3rd ventricle (p = 0.012) and 4th ventricle (p = 0.002). Correlation between volumetric results and clinical data showed that volume of both right and left lateral ventricles significantly and positively correlated with the duration of the illness (left R = 0.841, p = 0.002; right R = 0.755, p = 0.001) and the age of the LHON participants (left R = 0.656, p = 0.007; right R = 0.691, p = 0.004). The abnormalities in volume of the LHON patients’ subcortical structures indicate that the disease can cause changes not only in the white matter areas constituting visual tracts, but also in the other subcortical brain structures. Furthermore, the correlation between those results and the illness duration suggests that the disease might have a neurodegenerative nature; however, to fully confirm this observation, longitudinal studies should be conducted.

Progression of grey and white matter brain damage in Parkinson's disease: a critical review of structural MRI literature

The current review summarizes the current knowledge on longitudinal cortical and subcortical grey and white matter MRI findings assessed using T1-weighted and one-tensor diffusion-weighted MRI in Parkinson's disease (PD) patients. Results were reviewed according to disease duration, disease severity and cognitive impairment. The most consistent findings are those showing a progressive cortical atrophy accumulation in caudate, putamen, temporal/hippocampal, frontal and parietal areas in de novo PD cases and in the early/middle phase of the disease, with the achievement of a plateau in the later stage. Analyzing results according to the patient cognitive status, only a few studies used longitudinal MRI metrics to predict mild cognitive impairment or dementia conversion in PD patients, suggesting that atrophy of the hippocampus, fronto-temporal areas, caudate, thalamus and accumbens might play a role in this process. Stratifying patients according to disease severity, findings appear partially controversial, although showing a progressive atrophy of basal ganglia over 1 year of follow up and a widespread cortical thinning over 3-6 years in mild to moderate PD patients. Finally, microstructural damage of the main motor and associative WM tracts seems to be present, and rapidly progress, even in the early phase of PD. The utility of structural MRI metrics as biomarkers of PD progression and their role in improving the accuracy of disease progression prediction is still debated.

Ependymal Vps35 Promotes Ependymal Cell Differentiation and Survival, Suppresses Microglial Activation, and Prevents Neonatal Hydrocephalus

Hydrocephalus is a pathologic condition associated with various brain diseases, including Alzheimer's disease (AD). Dysfunctional ependymal cells (EpCs) are believed to contribute to the development of hydrocephalus. It is thus of interest to investigate EpCs' development and function. Here, we report that vacuolar protein sorting-associated protein 35 (VPS35) is critical for EpC differentiation, ciliogenesis, and survival, and thus preventing neonatal hydrocephalus. VPS35 is abundantly expressed in EpCs. Mice with conditional knock-out (cKO) of Vps35 in embryonic (Vps35^GFAP-Cre and Vps35^Emx1-Cre) or postnatal (Vps35^Foxj1-CreER) EpC progenitors exhibit enlarged lateral ventricles (LVs) and hydrocephalus-like pathology. Further studies reveal marked reductions in EpCs and their cilia in both Vps35^GFAP-Cre and Vps35^Foxj1-CreER mutant mice. The reduced EpCs appear to be due to impairments in EpC differentiation and survival. Additionally, both Vps35^GFAP-Cre and Vps35^Foxj1-CreER neonatal pups exhibit increased cell proliferation and death largely in a region close to LV-EpCs. Many microglia close to the mutant LV-EpC region become activated. Depletion of the microglia by PLX3397, an antagonist of colony-stimulating factor 1 receptor (CSF1R), restores LV-EpCs and diminishes the pathology of neonatal hydrocephalus in Vps35^Foxj1-CreER mice. Taken together, these observations suggest unrecognized functions of Vps35 in EpC differentiation, ciliogenesis, and survival in neonatal LV, and reveal pathologic roles of locally activated microglia in EpC homeostasis and hydrocephalus development.SIGNIFICANCE STATEMENT This study reports critical functions of vacuolar protein sorting-associated protein 35 (VPS35) not only in promoting ependymal cell (EpC) differentiation, ciliogenesis, and survival, but also in preventing local microglial activation. The dysfunctional EpCs and activated microglia are likely to induce hydrocephalus.

Impact of the cerebrospinal fluid-mask algorithm on the diagnostic performance of 123I-Ioflupane SPECT: an investigation of parkinsonian syndromes

Background

A cerebrospinal fluid (CSF)-mask algorithm has been developed to reduce the adverse influence of CSF-low-counts on the diagnostic utility of the specific binding ratio (SBR) index calculated with Southampton method. We assessed the effect of the CSF-mask algorithm on the diagnostic performance of the SBR index for parkinsonian syndromes (PS), including Parkinson’s disease, and the influence of cerebral ventricle dilatation on the CSF-mask algorithm.

Methods

We enrolled 163 and 158 patients with and without PS, respectively. Both the conventional SBR (non-CSF-mask) and SBR corrected with the CSF-mask algorithm (CSF-mask) were calculated from ¹²³I-Ioflupane single-photon emission computed tomography (SPECT) images of these patients. We compared the diagnostic performance of the corresponding indices and evaluated whether the effect of the CSF-mask algorithm varied according to the extent of ventricle dilatation, as assessed with the Evans index (EI). A receiver-operating characteristics (ROC) analysis was used for statistical analyses.

Results

ROC analyses demonstrated that the CSF-mask algorithm performed better than the non-CSF-mask (no correction, area under the curve [AUC] = 0.917 [95% confidence interval (CI) 0.887–0.947] vs. 0.895 [95% CI 0.861–0.929], p < 0.001; attenuation correction, AUC = 0.930 [95% CI 0.902–0.957] vs. 0.903 [95% CI 0.870–0.936], p < 0.001). When not corrected for attenuation, no significant difference in the AUC was observed in the low EI group between the non-CSF-mask and CSF-mask algorithms (0.927 [95% CI 0.877–0.978] vs. 0.942 [95% CI 0.898–0.986], p = 0.11); in the middle and high EI groups, the CSF-mask algorithm performed better than the non-CSF-mask algorithm (middle EI group, AUC = 0.894 [95% CI 0.825–0.963] vs. 0.872 [95% CI 0.798–0.947], p < 0.05; high EI group, AUC = 0.931 [95% CI 0.883–0.978] vs. 0.900 [95% CI 0.840–0.961], p < 0.01). When corrected for attenuation, significant differences in the AUC were observed in all three EI groups (low EI group, AUC = 0.961 [95% CI 0.924–0.998] vs. 0.942 [95% CI 0.895–0.988], p < 0.05; middle EI group, AUC = 0.905 [95% CI 0.843–0.968] vs. 0.872 [95% CI 0.800–0.944], p < 0.005; high EI group, AUC = 0.954 [95% CI 0.917–0.991] vs. 0.917 [95% CI 0.862–0.973], p < 0.005).

Conclusion

The CSF-mask algorithm improved the performance of the SBR index in informing the diagnosis of PS, especially in cases with ventricle dilatation.

The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease

There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson’s disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain’s neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in de novo PD patients. To this end, we used MRI, SPECT, and clinical data of de novo drug-naïve PD patients (n = 205, mean age 61 ± 10) and age-, sex-matched healthy controls (n = 105, mean age 58 ± 12) acquired at baseline. Moreover, we employed clinical data acquired at 1 year follow-up for PD patients with or without L-Dopa treatment in order to predict the progression symptoms severity. Voxel-based group comparisons and covariance analyses were applied to characterize baseline disease-related alterations for DAT-SPECT, DTI, and sMRI. Cortical and subcortical alterations in de novo PD patients were found in all evaluated imaging modalities, in line with previously reported midbrain-striato-cortical network alterations. The combination of these imaging alterations was reliably linked to clinical severity and disease progression at 1 year follow-up in this patient population, providing evidence for the potential use of these modalities as imaging biomarkers for disease severity and prognosis that can be integrated into clinical trials.

Thalamic and ventricular volumes predict motor response to deep brain stimulation for Parkinson's disease

BACKGROUND

Brain atrophy frequently occurs with Parkinson's disease (PD) and relates to increased motor symptoms of PD. The predictive value of neuroimaging-based measures of global and regional brain volume on motor outcomes in deep brain stimulation (DBS) remains unclear but potentially could improve patient selection and targeting.

OBJECTIVES

To determine the predictive value of preoperative volumetric MRI measures of cortical and subcortical brain volume on motor outcomes of subthalamic nucleus (STN) DBS in PD.

METHODS

Preoperative T1 3D MP-RAGE structural brain MRI images were analyzed for each participant to determine subcortical, ventricular, and cortical volume and thickness. Change in Unified Parkinson's Disease Rating Scale (UPDRS) scores for subsection 3, representing motor outcomes, was computed preoperatively and postoperatively following DBS programming in 86 participants. A multiple linear regression analysis was performed to investigate the relationship between volumetric data and the effect of DBS on UPDRS 3 scores.

RESULTS

Larger ventricular and smaller thalamic volumes predicted significantly less improvement of UPDRS 3 scores after STN DBS.

CONCLUSIONS

Our findings demonstrate in PD that regional brain volumes, in particular thalamic and ventricular volumes, predict motor outcomes after DBS. Differences in regional brain volumes may alter electrode targeting, reflect a specific disease trait such as postoperative progression of subclinical dementia, or directly interfere with the action of DBS.

Progressive Ventricles Enlargement and Cerebrospinal Fluid Volume Increases as a Marker of Neurodegeneration in Patients with Spinal Cord Injury: A Longitudinal Magnetic Resonance Imaging Study

Next to gray and white matter atrophy, cerebrospinal fluid (CSF) volume and ventricular dilation may be surrogate biomarkers for brain atrophy in spinal cord injury (SCI). We therefore aimed to track brain atrophy by means of CSF volume changes and ventricular enlargements over two years after SCI. Fifteen patients with SCI and 18 healthy controls underwent a series of T1-weighted scans during five time points over two years. Changes of CSF/intracranial volume (CSF/ICV) ratio, CSF volume, and ventricular enlargement rate over time were determined. Sample sizes with 80% power and 5% significance were calculated to detect a range of treatment effects for a two-armed trial. There was a significant cross-sectional increased CSF/ICV ratio in patients compared with controls at each time point (p < 0.02). The rate of CSF/ICV changes, however, was not significantly different between groups over time. CSF volume increased linearly over bilateral sensorimotor cortices (left: p = 0.002, right: p = 0.042) and in the supracerebellar space (p < 0.001) within two years. An acceleration of the enlargement within the third (p = 0.017) and the fourth (p = 0.006) ventricles was observed in patients over time. Sample size estimation for six-month trials with CSF volume requires 25 patients per treatment arm to detect a hypothetical treatment effect in terms of slowing of atrophy rate of 30%. This study shows that SCI-induced changes in CSF/ICV ratio and ventricular expansion rate provide additional information on the neurodegenerative processes after injury. The sensitivity to scoring treatment effects speaks to its potential to serve as a sensitive biomarker in addition to local atrophy measures.

Longitudinal white matter microstructural change in Parkinson's disease

Postmortem studies of Parkinson's disease (PD) suggest that Lewy body pathology accumulates in a predictable topographical sequence, beginning in the olfactory bulb, followed by caudal brainstem, substantia nigra, limbic cortex, and neocortex. Diffusion-weighted imaging (DWI) is sensitive, if not specific, to early disease-related white matter (WM) change in a variety of traumatic and degenerative brain diseases. Although numerous cross-sectional studies have reported DWI differences in cerebral WM in PD, only a few longitudinal studies have investigated whether DWI change exceeds that of normal aging or coincides with regional Lewy body accumulation. This study mapped regional differences in the rate of DWI-based microstructural change between 29 PD patients and 43 age-matched controls over 18 months. Iterative within- and between-subject tensor-based registration was completed on motion- and eddy current-corrected DWI images, then baseline versus follow-up difference maps of fractional anisotropy, mean, radial, and axial diffusivity were analyzed in the Biological Parametric Mapping toolbox for MATLAB. This analysis showed that PD patients had a greater decline in WM integrity in the rostral brainstem, caudal subcortical WM, and cerebellar peduncles, compared with controls. In addition, patients with unilateral clinical signs at baseline experienced a greater rate of WM change over the 18-month study than patients with bilateral signs. These findings suggest that rate of WM microstructural change in PD exceeds that of normal aging and is maximal during early stage disease. In addition, the neuroanatomic locations (rostral brainstem and subcortical WM) of accelerated WM change fit with current theories of topographic disease progression.

Anatomical predictors of cognitive decline after subthalamic stimulation in Parkinson's disease

We investigated whether pre-operative MRI measures of focal brain atrophy could predict cognitive decline occurring after deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson's disease (PD). For that purpose, we prospectively collected data of 42 consecutive patients with PD who underwent bilateral STN-DBS. Normalized brain structure volumes and cortical thicknesses were measured on pre-operative T1-weighted MRI. Patients were tested for their cognitive performances before surgery and 1 year after. After controlling for age, gender, pre-operative disease severity, change in dopaminomimetic dose after surgery and contact location, we found correlations: (1) between the variation of the total Mattis dementia rating scale (MDRS) score and left lateral ventricle volume (p = 0.032), (2) between the variation of the initiation/perseveration subscore of the MDRS and the left nucleus accumbens volume (p = 0.042) and the left lateral ventricle volume (p = 0.017) and (3) between the variation of the backward digit-span task and the right and left superior frontal gyrus thickness (p = 0.004 and p = 0.007, respectively). Left nucleus accumbens atrophy was associated with decline in the initiation/perseveration subscore with the largest effect size (d = - 1.64). Pre-operative left nucleus accumbens volume strongly predicted postoperative decline in the initiation/attention subscore (AUC = 0.92, p < 0.001, 96.3% sensitivity, 80.0% specificity, 92.9% PPV and 92.9% NPV). We conclude that the morphometric measures of brain atrophy usually associated with cognitive impairment in PD can also explain or predict a part of cognitive decline after bilateral STN-DBS. In particular, the left accumbens nucleus volume could be considered as a promising marker for guiding surgical decisions.

Parkinson's disease mild cognitive impairment classifications and neurobehavioral symptoms

BACKGROUND

We apply recently recommended Parkinson's disease mild cognitive impairment (PD-MCI) classification criteria from the movement disorders society (MDS) to PD patients and controls and compare diagnoses to that of short global cognitive scales at baseline and over time. We also examine baseline prevalence of neuropsychiatric symptoms across different definitions of MCI.

METHODS

51 PD patients and 50 controls were classified as cognitively normal, MCI, or demented using MDS criteria (1.5 or 2.0 SD below normative values), Clinical Dementia Rating Scale (CDR), and the Dementia Rating Scale (DRS). All subject had parallel assessment with the Neuropsychiatric inventory (NPI).

RESULTS

We confirmed that PD-MCI (a) is frequent, (b) increases the risk of PDD, and (c) affects multiple cognitive domains. We highlight the predictive variability of different criteria, suggesting the need for further refinement and standardization. When a common dementia outcome was used, the Level II MDS optimal testing battery with impairment defined as two SD below norms in 2+ tests performs the best. Neuropsychiatric symptoms were more common in PD across all baseline and longitudinal cognitive classifications.

CONCLUSIONS

Our results advance previous findings on the utility of MDS PD-MCI criteria for PD patients and controls at baseline and over time. Additionally, we emphasize the possible utility of other cognitive scales and neuropsychiatric symptoms.

Nonmotor Symptoms of Parkinson's Disease as Predictors of Dementia

Some nonmotor symptoms (NMS) of Parkinson's disease (PD) have been shown to increase the risk of developing dementia. A total of 52 PD patients without dementia at baseline were examined for NMS over 36 months. Mini-Mental State Examination, Dementia Rating Scale-2, and caregiver-derived (Clinical Dementia Rating) scores were employed to rate patients as having either clear progression or not. Some 20 of 48 participants (41.7%) had clear cognitive decline. Univariate binary regression analysis was statistically significant for age (odds ratio [OR] (CI 95%)=1.24, 1.07-1.45, p=0.006) and orthostatic hypotension (OH) (OR (CI 95%)=4.91, 1.24-19.5, p=0.024). Multivariate analysis showed that only age (OR (CI 95%)=1.19, 1.0-1.41, p=0.05) and OH (OR (CI 95%)=5.57, 1.0-30.97, p=0.05) were correlated with an increased risk of cognitive decline. The presence of OH at baseline may be a significant predictor of progression to dementia in PD.

Profiling novel metabolic biomarkers for Parkinson's disease using in-depth metabolomic analysis

OBJECTIVE

To profile the amine/phenol submetabolome to determine potential metabolite biomarkers associated with Parkinson's disease (PD) and PD with incipient dementia.

METHODS

At baseline of a 3-wave (18-month intervals) longitudinal study, serum samples were collected from 42 healthy controls and 43 PD patients. By wave 3 (year 3), 16 PD patients were diagnosed with dementia and were classified as PD with incipient dementia at baseline. Metabolomic profiling using dansylation isotope labeling liquid chromatography mass spectrometry was conducted to compare controls with the full PD, PD with no dementia, and PD with incipient dementia groups.

RESULTS

Metabolomic analyses detected 719 common metabolites in 80% of the samples. Some were significantly altered in pairwise comparison of different groups (fold change of >1.2 or <0.83 with q < 0.05). We discriminated PD and controls by using a 5-metabolite panel, vanillic acid, 3-hydroxykynurenine, isoleucyl-alanine, 5-acetylamino-6-amino-3-methyluracil, and theophylline. The receiver operating characteristic curve produced an area-under-the-curve value of 0.955 with 87.5% sensitivity and 93.0% specificity. In comparing PD with no dementia with PD with incipient dementia, we used an 8-metabolite panel, His-Asn-Asp-Ser, 3,4-dihydroxyphenylacetone, desaminotyrosine, hydroxy-isoleucine, alanyl-alanine, putrescine [-2H], purine [+O] and its riboside. This produced an area-under-the-curve value of 0.862 with 80.0% sensitivity and 77.0% specificity.

CONCLUSIONS

The significantly altered metabolites can be used to differentiate (1) PD patients from healthy controls with high accuracy and (2) the stable PD with no dementia group from those with incipient dementia. Following further validation in larger cohorts, these metabolites could be used for both discrimination and establishing prognosis in PD. © 2017 International Parkinson and Movement Disorder Society.

Longitudinal whole-brain atrophy and ventricular enlargement in nondemented Parkinson's disease

We investigated whole-brain atrophy and ventricular enlargement over 18 months in nondemented Parkinson's disease (PD) and examined their associations with clinical measures and baseline CSF markers. PD subjects (n = 100) were classified at baseline into those with mild cognitive impairment (MCI; PD-MCI, n = 36) and no cognitive impairment (PD-NC, n = 64). Percentage of whole-brain volume change (PBVC) and ventricular expansion over 18 months were assessed with FSL-SIENA and ventricular enlargement (VIENA) respectively. PD-MCI showed increased global atrophy (-1.1% ± 0.8%) and ventricular enlargement (6.9 % ± 5.2%) compared with both PD-NC (PBVC: -0.4 ± 0.5, p < 0.01; VIENA: 2.1% ± 4.3%, p < 0.01) and healthy controls. In a subset of 35 PD subjects, CSF levels of tau, and Aβ42/Aβ40 ratio were correlated with PBVC and ventricular enlargement respectively. The sample size required to demonstrate a 20% reduction in PBVC and VIENA was approximately 1/15th of that required to detect equivalent changes in cognitive decline. These findings suggest that longitudinal MRI measurements have potential to serve as surrogate markers to complement clinical assessments for future disease-modifying trials in PD.

Evolution of deep gray matter volume across the human lifespan

Magnetic resonance imaging of subcortical gray matter structures, which mediate behavior, cognition and the pathophysiology of several diseases, is crucial for establishing typical maturation patterns across the human lifespan. This single site study examines T1-weighted MPRAGE images of 3 healthy cohorts: (i) a cross-sectional cohort of 406 subjects aged 5-83 years; (ii) a longitudinal neurodevelopment cohort of 84 subjects scanned twice approximately 4 years apart, aged 5-27 years at first scan; and (iii) a longitudinal aging cohort of 55 subjects scanned twice approximately 3 years apart, aged 46-83 years at first scan. First scans from longitudinal subjects were included in the cross-sectional analysis. Age-dependent changes in thalamus, caudate, putamen, globus pallidus, nucleus accumbens, hippocampus, and amygdala volumes were tested with Poisson, quadratic, and linear models in the cross-sectional cohort, and quadratic and linear models in the longitudinal cohorts. Most deep gray matter structures best fit to Poisson regressions in the cross-sectional cohort and quadratic curves in the young longitudinal cohort, whereas the volume of all structures except the caudate and globus pallidus decreased linearly in the longitudinal aging cohort. Males had larger volumes than females for all subcortical structures, but sex differences in trajectories of change with age were not significant. Within subject analysis showed that 65%-80% of 13-17 year olds underwent a longitudinal decrease in volume between scans (∼4 years apart) for the putamen, globus pallidus, and hippocampus, suggesting unique developmental processes during adolescence. This lifespan study of healthy participants will form a basis for comparison to neurological and psychiatric disorders. Hum Brain Mapp 38:3771-3790, 2017. © 2017 Wiley Periodicals, Inc.

Abnormal Echogenicity of the Substantia Nigra, Raphe Nuclei, and Third-Ventricle Width as Markers of Cognitive Impairment in Parkinsonian Disorders: A Cross-Sectional Study

Background. Patients with Parkinson's disease (PD) have a high risk of cognitive problems. Objective. This study assesses whether abnormal echogenicity of the substantia nigra (SN) and raphe nuclei (RN) and the diameter of third ventricle are markers of cognitive impairment in patients with PD and other forms of parkinsonism. Methods. 126 outpatients with early signs of parkinsonism underwent transcranial sonography (TCS). The scales for the outcome of Parkinson's disease cognition (SCOPA-COG) were used as cognitive measure. Definite neurological diagnosis was established after two-year follow-up. Results. One-third of the patients with PD and half of those with APS had signs of cognitive impairment. The echogenicity of the SN was not related to cognitive impairment. The diameter of the third ventricle was significantly larger in PD patients with cognitive impairment compared to those without. In patients with APS we found a significantly higher frequency of hypoechogenic RN in patients with cognitive problems. Conclusions. Cognitive impairment is already present in a substantial proportion of patients with PD and APS at first referral. In patients with APS the frequency of hypoechogenic RN points to the direction of other pathophysiology with more emphasis on deficits in the serotonergic neurotransmitter system. The larger diameter of the third ventricle in PD patients with cognitive impairment may reflect Alzheimer like brain atrophy, as has been reported in earlier studies.

The pattern of gray matter atrophy in Parkinson's disease differs in cortical and subcortical regions

Cortical and subcortical gray matter (GM) atrophy may progress differently during the course of Parkinson's disease (PD). We delineated and compared the longitudinal pattern of these PD-related changes. Structural MRIs and clinical measures were obtained from 76 PD with different disease durations and 70 Controls at baseline, 18-, and 36 months. Both cortical and subcortical (putamen, caudate, and globus pallidus) GM volumes were obtained, compared, and associated with PD clinical measures at baseline. Their volumes and rates of change also were compared among Controls, PDs, and PD subgroups based on duration of illness [≤1 year (PD(E)), 1-5 years (PD(M)), and >5 years (PD(L))]. Compared to Controls, PD subjects displayed smaller cortical GM and striatal(putamen, caudate, ps ≤0.001), volumes at baseline. Cortical GM volumes were negatively associated with disease duration at baseline, whereas striatal volumes were not. PD subjects demonstrated accelerated volume loss in cortical GM (p = 0.006), putamen (p = 0.034), and caudate (p = 0.008) compared to Controls. Subgroup analyses demonstrated that accelerated cortical atrophy reached statistical significance in PD subjects with duration of illness 1-5 years (PD(M), ps<0.001) and the trend of accelerated atrophy seemed to persist until later stages, whereas striatal atrophy occurred in PD subjects with PD(E) (p = 0.021 for putamen, p = 0.005 for caudate) and PD(M) (p = 0.002 for putamen, p = 0.001 for caudate) that significantly slowed down in PD(L) (ps for PD(L) vs PD(E) or PD(M): <0.01). The pattern of GM loss in PD differs in cortical and subcortical regions, with striatal atrophy occurring earlier and extra-striatal cortical atrophy later.

Tracking Parkinson's Disease over One Year with Multimodal Magnetic Resonance Imaging in a Group of Older Patients with Moderate Disease

Background & Objectives

Cross-sectional magnetic resonance imaging (MRI) suggests that Parkinson’s disease (PD) is associated with changes in cerebral tissue volume, diffusion tensor imaging metrics, and perfusion values. Here, we performed a longitudinal multimodal MRI study—including structural, diffusion tensor imaging (DTI), and perfusion MRI—to investigate progressive brain changes over one year in a group of older PD patients at a moderate stage of disease.

Methods

Twenty-three non-demented PD (mean age (SD) = 69.5 (6.4) years, disease duration (SD) = 5.6 (4.3) years) and 23 matched control participants (mean age: 70.6 (6.8)) completed extensive neuropsychological and clinical assessment, and multimodal 3T MRI scanning at baseline and one year later. We used a voxel-based approach to assess change over time and group-by-time interactions for cerebral structural and perfusion metrics.

Results

Compared to controls, in PD participants there was localized grey matter atrophy over time in bilateral inferior and right middle temporal, and left orbito-frontal cortices. Using a voxel-based approach that focused on the centers of principal white matter tracts, the PD and control cohorts exhibited similar levels of change in DTI metrics. There was no significant change in perfusion, cognitive, or motor severity measures.

Conclusions

In a cohort of older, non-demented PD participants, macrostructural MRI detected atrophy in the PD group compared with the control group in temporal and orbito-frontal cortices. Changes in diffusion MRI along principal white matter tracts over one year were found, but this was not differentially affected by PD.

Biomarkers of cognitive decline in Parkinson's disease

Cognitive impairment is a frequent and devastating non-motor symptom of Parkinson's disease (PD). Impaired cognition has a major impact on either quality of life or mortality in patients with PD. Notably, the rate of cognitive decline and pattern of early cognitive deficits in PD are highly variable between individuals. Given that the underlying mechanisms of cognitive decline or dementia associated with PD remain unclear, there is currently no mechanism-based treatment available. Identification of biological markers, including neuroimaging, biofluids and common genetic variants, that account for the heterogeneity of PD related cognitive decline could provide important insights into the pathological processes that underlie cognitive impairment in PD. These combined biomarker approaches will enable early diagnosis and provide indicators of cognitive progression in PD patients. This review summarizes recent advances in the development of biomarkers for cognitive impairments in PD.

MR image texture in Parkinson's disease: a longitudinal study

BACKGROUND

Few of the structural changes caused by Parkinson's disease (PD) are visible in magnetic resonance imaging (MRI) with visual inspection but there is a need for a method capable of observing the changes beyond the human eye. Texture analysis offers a technique that enables the quantification of the image gray-level patterns.

PURPOSE

To investigate the value of quantitative image texture analysis method in diagnosis and follow-up of PD patients.

MATERIAL AND METHODS

Twenty-six PD patients underwent MRI at baseline and after 2 years of follow-up. Four co-occurrence matrix-based texture parameters, describing the image homogeneity and complexity, were calculated within clinically interesting areas of the brain. In addition, correlations with clinical characteristics (Unified Parkinson's Disease Ranking Scales I-III and Mini-Mental State Examination score) along with a comparison to healthy controls were evaluated.

RESULTS

Patients at baseline and healthy volunteers differed in their brain MR image textures mostly in the areas of substantia nigra pars compacta, dentate nucleus, and basilar pons. During the 2-year follow-up of the patients, textural differences appeared mainly in thalamus and corona radiata. Texture parameters in all the above mentioned areas were also found to be significantly related to clinical scores describing the severity of PD.

CONCLUSION

Texture analysis offers a quantitative method for detecting structural changes in brain MR images. However, the protocol and repeatability of the method must be enhanced before possible clinical use.

Progression of brain atrophy in the early stages of Parkinson's disease: a longitudinal tensor-based morphometry study in de novo patients without cognitive impairment

The presence of brain atrophy and its progression in early Parkinson's disease (PD) are still a matter of debate, particularly in patients without cognitive impairment. The aim of this longitudinal study was to assess whether PD patients who remain cognitively intact develop progressive atrophic changes in the early stages of the disease. For this purpose, we employed high-resolution T1-weighted MR imaging to compare 22 drug-naïve de novo PD patients without cognitive impairment to 17 age-matched control subjects, both at baseline and at three-year follow-up. We used tensor-based morphometry to explore the presence of atrophic changes at baseline and to compute yearly atrophy rates, after which we performed voxel-wise group comparisons using threshold-free cluster enhancement. At baseline, we did not observe significant differences in regional atrophy in PD patients with respect to control subjects. In contrast, PD patients showed significantly higher yearly atrophy rates in the prefrontal cortex, anterior cingulum, caudate nucleus, and thalamus when compared to control subjects. Our results indicate that even cognitively preserved PD patients show progressive cortical and subcortical atrophic changes in regions related to cognitive functions and that these changes are already detectable in the early stages of the disease.

Predicting dementia development in Parkinson's disease using Bayesian network classifiers

Parkinson's disease (PD) has broadly been associated with mild cognitive impairment (PDMCI) and dementia (PDD). Researchers have studied surrogate, neuroanatomic biomarkers provided by magnetic resonance imaging (MRI) that may help in the early diagnosis of this condition. In this article, four classification models (naïve Bayes, multivariate filter-based naïve Bayes, filter selective naïve Bayes and support vector machines, SVM) have been applied to evaluate their capacity to discriminate between cognitively intact patients with Parkinson's disease (PDCI), PDMCI and PDD. For this purpose, the MRI studies of 45 subjects (16 PDCI, 15 PDMCI and 14 PDD) were acquired and post-processed with Freesurfer, obtaining 112 variables (volumes of subcortical structures and thickness of cortical parcels) per subject. A multivariate filter-based naïve Bayes model was found to be the best classifier, having the highest cross-validated sensitivity, specificity and accuracy. Additionally, the most relevant variables related to dementia in PD, as predicted by our classifiers, were cerebral white matter, and volumes of the lateral ventricles and hippocampi.

Magnetic resonance imaging: a biomarker for cognitive impairment in Parkinson's disease?

Dementia is a frequent and disabling complication of Parkinson's disease (PD). Clinicians and researchers lack a biomarker capable of tracking the structural and functional changes that underlie the evolution of cognitive dysfunction in PD. Magnetic resonance imaging (MRI) has been adopted as a biomarker in natural history and interventional studies of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), but its utility as a biomarker for PD and Parkinson's disease dementia (PDD) is unclear. In this review, the authors summarize the studies that have used MRI to investigate cognitive decline in PD, outline limitations of those studies, and suggest directions for future research. PD dementia is associated with extensive cortical atrophy, which may be quantified with structural MRI. More promisingly, patterns of atrophy may be present in those who have PD with MCI (PD-MCI). Subcortical white matter tract degeneration is detectable early in the disease with diffusion tensor imaging and may precede changes observed on conventional structural MRI. Although less well studied, other MR techniques, such as functional MRI, MR perfusion imaging with arterial spin labeling, and MR spectroscopy, have demonstrated differences in activation and metabolism between PD and PDD. In this review, the ability to compare studies was limited by the heterogeneity of study populations, cognitive testing methods, and imaging protocols. Future work should adopt agreed scan protocols, should be adequately powered, and should use carefully phenotyped patients to fully maximize the contribution of MRI as a biomarker for PDD.

Progression of cortical thinning in early Parkinson's disease

The aim of this study was to investigate the progression of cortical thinning and gray-matter (GM) volume loss in early Parkinson's disease (PD). MRI and neuropsychological assessment were obtained at baseline and follow-up (mean ± standard deviation = 35.50 ± 1.88 months) in a group of 16 early-PD patients (H & Y stage ≤II and disease duration ≤5 years) and 15 healthy controls matched for age, gender, and years of education. FreeSurfer software was used for the analysis of cortical thickness as well as for cortical and subcortical volumetric analyses. Voxel-based morphometry analysis was performed using SPM8. Compared to controls, PD patients showed greater regional cortical thinning in bilateral frontotemporal regions as well as greater over-time total GM loss and amygdalar volume reduction. PD patients and controls presented similar over-time changes in cognitive functioning. In early-PD patients, global GM loss, amygdalar atrophy, and cortical thinning in frontotemporal regions are specifically associated with the PD-degenerative process.

Neurocognitive speed and inconsistency in Parkinson's disease with and without incipient dementia: an 18-month prospective cohort study

We examined two-wave longitudinal changes in two indicators of neurocognitive speed (i.e., mean rate, intraindividual variability) using one simple and three complex reaction time tasks. Participants included idiopathic Parkinson's disease (PD) patients, with and without incipient dementia, and normal controls. At baseline, there were 45 patients (26 men, 19 women) with idiopathic PD who ranged from 65 to 84 years (M = 71.3; SD = 4.5) and 47 matched controls (27 men, 20 women) who ranged from 65 to 84 years (M = 71.4; SD = 4.9). The 18-month longitudinal sample comprised of 74 returning participants (43 controls; 31 PD patients) who had no cognitive impairment or dementia at both waves. Ten of the 31 PD patients returning for Time 3 had dementia or cognitive impairment. These constituted the PD with incipient dementia (PDID) group. Repeated measures analyses of variance showed that the PD and PDID groups were slower over time on the reaction time tasks, whereas the controls improved their performance over time on all tasks. Inconsistency distinguished the two clinical groups (i.e., the PDID group but not the PD group became more inconsistent over time). Changes in neurocognitive speed and inconsistency may be valid clinical markers of PDID.

An update on brain imaging in parkinsonian dementia

Disturbances of cognition are frequent in Parkinson's disease (PD). Unlike severe loss of dopamine early in PD, extensive cholinergic losses have been consistently reported in PD with dementia. Cholinergic imaging suggests that basal forebrain cholinergic system degeneration appears early in PD and worsens with dementia development. Cortical cholinergic denervation is similar in PD with dementia and dementia with Lewy bodies, supporting a common disease spectrum, at least with respect to cholinergic pathology. Presence of cerebral amyloidopathy in the setting of parkinsonism may accelerate cognitive decline. Novel MRI techniques illustrate the widespread presence of neurodegeneration in PD with dementia, affecting white matter tracts and connectivity functions. This review will outline current concepts regarding dementia development in PD and discuss their correlation with functional and structural neuroimaging including PET and MRI.