Substantia nigra hyperechogenicity is related to decline in verbal memory in healthy elderly adults

Cognition and Activity of Daily Living Function in people with Parkinson's disease

The ability to perform activities of daily living (ADL) function is a multifaceted construct that reflects functionality in different daily life situations. The loss of ADL function due to cognitive impairment is the core feature for the diagnosis of Parkinson's disease dementia (PDD). In contrast to Alzheimer's disease, ADL impairment in PD can be compromised by various factors, including motor and non-motor aspects. This narrative review summarizes the current state of knowledge on the association of cognition and ADL function in people with PD and introduces the concept of "cognitive ADL" impairment for those problems in everyday life that are associated with cognitive deterioration as their primary cause. Assessment of cognitive ADL impairment is challenging because self-ratings, informant-ratings, and performance-based assessments seldomly differentiate between "cognitive" and "motor" aspects of ADL. ADL function in PD is related to multiple cognitive domains, with attention, executive function, and memory being particularly relevant. Cognitive ADL impairment is characterized by behavioral anomalies such as trial-and-error behavior or task step omissions, and is associated with lower engagement in everyday behaviors, as suggested by physical activity levels and prolonged sedentary behavior. First evidence shows that physical and multi-domain interventions may improve ADL function, in general, but the evidence is confounded by motor aspects. Large multicenter randomized controlled trials with cognitive ADL function as primary outcome are needed to investigate which pharmacological and non-pharmacological interventions can effectively prevent or delay deterioration of cognitive ADL function, and ultimately the progression and conversion to PDD.

Predicting the occurrence of mild cognitive impairment in Parkinson's disease using structural MRI data

Introduction

Mild cognitive impairment (MCI) is a common symptom observed in individuals with Parkinson's disease (PD) and a main risk factor for progressing to dementia. Our objective was to identify early anatomical brain changes that precede the transition from healthy cognition to MCI in PD.

Methods

Structural T1-weighted magnetic resonance imaging data of PD patients with healthy cognition at baseline were downloaded from the Parkinson's Progression Markers Initiative database. Patients were divided into two groups based on the annual cognitive assessments over a 5-year time span: (i) PD patients with unstable healthy cognition who developed MCI over a 5-year follow-up (PD-UHC, n = 52), and (ii) PD patients who maintained stable healthy cognitive function over the same period (PD-SHC, n = 52). These 52 PD-SHC were selected among 192 PD-SHC patients using propensity score matching method to have similar demographic and clinical characteristics with PD-UHC at baseline. Seventy-five percent of these were used to train a support vector machine (SVM) algorithm to distinguish between the PD-UHC and PD-SHC groups, and tested on the remaining 25% of individuals. Shapley Additive Explanations (SHAP) feature analysis was utilized to identify the most informative brain regions in SVM classifier.

Results

The average accuracy of classifying PD-UHC vs. PD-SHC was 80.76%, with 82.05% sensitivity and 79.48% specificity using 10-fold cross-validation. The performance was similar in the hold-out test sets with all accuracy, sensitivity, and specificity at 76.92%. SHAP analysis showed that the most influential brain regions in the prediction model were located in the frontal, occipital, and cerebellar regions as well as midbrain.

Discussion

Our machine learning-based analysis yielded promising results in identifying PD individuals who are at risk of cognitive decline from the earliest disease stage and revealed the brain regions which may be linked to the prospective cognitive decline in PD before clinical symptoms emerge.

Cognition in prodromal Parkinson's disease

One characteristic of Parkinson's disease (PD) is a prodromal phase, lasting many years during which both pre-clinical motor and non-motor symptoms occur. Around one-fifth of patients with PD manifest mild cognitive impairment at time of clinical diagnosis. Thus, important challenges are to define the time of onset of cognitive dysfunction in the prodromal phase of PD, and to define its co-occurrence with other specific characteristics. Evidence for cognitive change in prodromal PD comes from various study designs, including both longitudinal and cross-sectional approaches with different target groups. These studies support the concept that changes in global cognitive function and alterations in executive functions occur, and that these changes may be present up to 6 years before clinical PD diagnosis. Notably, this evidence led to including global cognitive impairment as an independent prodromal marker in the recently updated research criteria of the Movement Disorder Society for prodromal PD. Knowledge in this field, however, is still at its beginning, and evidence is sparse about many aspects of this topic. Further longitudinal studies including standardized assessments of global and domain-specific cognitive functions are needed to gain further knowledge about the first appearance, the course, and the interaction of cognitive deficits with other non-motor symptoms in prodromal stage PD. Treatment approaches, including non-pharmacological interventions, in individuals with prodromal PD might help to prevent or delay cognitive dysfunction in early PD.

Cognitive Performance is Associated with Altered Cerebral Hemodynamics Assessed by Transcranial Ultrasound in Parkinson's Disease

PURPOSE

Cognitive impairment (CI) is a common but debilitating non-motor symptom in Parkinson's disease (PD). Although cerebrovascular functions are related to cognitive performance in healthy individuals, such a relation in PD remains elusive. This study aims to assess the association between cerebrovascular function and cognitive performance in PD individuals.

PATIENTS AND METHODS

Two-hundred-and-one PD individuals were retrospectively included. They were subsequently divided into two groups: PD with normal cognition (PD-NC) and PD with CI (PD-CI). Cerebral hemodynamic characteristics of the middle cerebral arteries were assessed by transcranial ultrasound. The association between scores in each cognitive domain and cerebral hemodynamic parameters was further analyzed using regression analyses. Additionally, a binary logistic regression model with backward stepwise procedure was applied to build the model for discriminating CI in PD individuals. An independent dataset of additional 46 PD individuals was used further.

RESULTS

The PD-CI group showed a relatively lower end-diastolic blood flow velocity (EDV, p < 0.05) and a higher resistive index (RI, p < 0.05) compared to the PD-NC group. RI showed significant associations with the memory item score of Montreal Cognitive Assessment (p < 0.05). A model combining clinical and hemodynamic variables was established with optimal efficiency (area under the curve, AUC = 0.651). Further replication of the model in an independent dataset yielded a great consistency (AUC = 0.704).

CONCLUSION

In our study, cerebrovascular functions were significantly associated with the cognitive performance in PD individuals, especially with the memory task. The established model was effective in identifying CI in PD individuals, which might be a potentially useful tool to screen the cognitive decline in PD individuals at an early stage of the disease. Further studies with larger sample sizes in different populations are warranted.

Neurosonological Findings Related to Non-Motor Features of Parkinson's Disease: A Systematic Review

Non-motor symptoms (NMS) in Parkinson’s disease (PD), including neuropsychiatric or dysautonomic complaints, fatigue, or pain, are frequent and have a high impact on the patient’s quality of life. They are often poorly recognized and inadequately treated. In the recent years, the growing awareness of NMS has favored the development of techniques that complement the clinician’s diagnosis. This review provides an overview of the most important ultrasonographic findings related to the presence of various NMS. Literature research was conducted in PubMed, Scopus, and Web of Science from inception until January 2021, retrieving 23 prospective observational studies evaluating transcranial and cervical ultrasound in depression, dementia, dysautonomic symptoms, psychosis, and restless leg syndrome. Overall, the eligible articles showed good or fair quality according to the QUADAS-2 assessment. Brainstem raphe hypoechogenicity was related to the presence of depression in PD and also in depressed patients without PD, as well as to overactive bladder. Substantia nigra hyperechogenicity was frequent in patients with visual hallucinations, and larger intracranial ventricles correlated with dementia. Evaluation of the vagus nerve showed contradictory findings. The results of this systematic review demonstrated that transcranial ultrasound can be a useful complementary tool in the evaluation of NMS in PD.

Transcranial B-Mode Sonography in Movement Disorders

Applying a 2-4MHz probe at the temporal bone window transcranial B-mode sonography (TCS) enables the depiction of the brain parenchyma through the intact skull. Meanwhile it has been applied for the diagnosis and the differential diagnosis of movement disorders for decades. In the first part of this chapter, we summarize the technical requirements and describe the ultrasound method for optimal TCS examination. Imaging planes and the relevant structures are explained in detail. In the second part of the chapter, we focus on the role of substantia nigra hyperechogenicity for the diagnosis of Parkinson's disease (PD) and prodromal PD. In this part, we also mention the role of TCS in atypical and secondary Parkinsonian syndromes and other movement disorders. Summarizing all these information we explain how TCS can be helpful for the differential diagnosis of movement disorders. The current data show that TCS is an easily applicable and economic imaging method which can be used as an additional tool for the diagnosis of PD with a high sensitivity (>85%), specificity (>80%) and inter-rater reliability (>84%) as well as for the differential diagnosis of movement disorders. Lately, TCS has also been utilized in further areas such as the detection of individuals at risk for PD or the determination of electrode localization in patients with deep brain stimulation. An insufficient temporal bone window especially in the elderly and the necessity of an experienced investigator are limitations of this method.

Transcranial Sonographic Alterations of Substantia Nigra and Third Ventricle in Parkinson's Disease with or without Dementia

Background:

Numerous studies have demonstrated that patients with Parkinson's disease (PD) have a higher prevalence of substantia nigra (SN) hyperechogenicity compared with controls. Our aim was to explore the neuroimaging characteristics of transcranial sonography (TCS) of patients with PD and those with PD with dementia (PDD). The correlation between the echogenicity of the SN and clinical symptoms in Chinese patients with PDD was also assessed.

Methods:

The ratios of SN hyperechogenicity (SN+), maximum sizes of SN+, and widths of third ventricle (TV) were measured using TCS for all the recruited patients. Data were analyzed using one-way analysis of variance, rank-sum test, Chi-square test, and receiver-operating characteristic (ROC) curve analysis.

Results:

The final statistical analysis included 46 PDD patients, 52 PD patients, and 40 controls. There were no significant differences in ratios of SN+ and maximum sizes of SN+ between PDD and PD groups (P > 0.05). TV widths were significantly larger in PDD group (7.1 ± 1.9 mm) than in PD group (6.0 ± 2.0 mm) and controls (5.9 ± 1.5 mm, P < 0.05); however, the ratios of enlarged TV did not differ among the three groups (P = 0.059). When cutoff value was set at 6.8 mm, the TV width had a relatively high sensitivity and specificity in discriminating between PDD and PD groups (P = 0.030) and between PDD group and controls (P = 0.003), based on ROC curve analysis. In PDD patients, SN+ was more frequently detected in akinetic-rigid subgroup, and patients with SN+ showed significantly higher Hoehn and Yahr stage and Nonmotor Symptoms Questionnaire scores (P < 0.05).

Conclusions:

Compared to Chinese patients with PD, patients with PDD had a wider TV, altered SN sonographic features, and more severe clinical symptoms. Our findings suggest that TCS can be used to assess brain atrophy in PD and may be useful in discriminating between PD with and without dementia.

Cognitive changes in prodromal Parkinson's disease: A review

Although other nonmotor phenomena representing possible prodromal symptoms of Parkinson's disease have been described in some detail, the occurrence and characteristics of cognitive decline in this early phase of the disease are less well understood. The aim of this review is to summarize the current state of research on cognitive changes in prodromal PD. Only a small number of longitudinal studies have been conducted that examined cognitive function in individuals with a subsequent PD diagnosis. However, when we consider data from at-risk groups, the evidence suggests that cognitive decline may occur in a substantial number of individuals who have the potential for developing PD. In terms of specific cognitive domains, executive function in particular and, less frequently, memory scores are reduced. Prospective longitudinal studies are thus needed to clarify whether cognitive, and specifically executive, decline might be added to the prodromal nonmotor symptom complex that may precede motor manifestations of PD by years and may help to update the risk scores used for early identification of PD. © 2017 International Parkinson and Movement Disorder Society.

Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential

Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.

Cognitive Performance Patterns in Healthy Individuals with Substantia Nigra Hyperechogenicity and Early Parkinson's Disease

Introduction: Hyperechogenicity of the substantia nigra (SN+) is a risk marker for Parkinson’s disease (PD) which can be detected before the diagnosis. In healthy individuals, SN+ has been associated with slight deficits in specific cognitive functions, suggesting cognitive impairment as a possible pre-diagnostic marker for PD. However, the pattern of cognitive deficits associated with SN+ has not yet been compared with those present in PD.

Methods: Data of 262 healthy individuals with normal echogenicity (SN-) and 48 healthy individuals with SN+ were compared with 82 early stage PD patients using the “Consortium to Establish a Registry for Alzheimer’s disease” test battery. First, the test clusters (factors) were identified using a principal component analysis (PCA). Mean group performance of cognitive tests belonging to distinct factors, according to the PCA, and single subtest performances were compared using analyses of variance. Second, the number of individuals with abnormal cognitive performances (z-score < -1.0) were compared between groups.

Results: Verbal memory, semantic and executive function, and praxis were identified as components of cognitive performances. The SN+ group performed significantly worse than the SN- group in tests assessing semantic and executive function, with a non-significant decrease in verbal memory. On the subtest level, individuals of the SN+ group scored significantly lower than the SN- group on the Boston Naming Test (BNT; p = 0.008). In all subtests, the percentages of PD patients with values below the cut-off for abnormal performance were higher than in the SN- group. Moreover, more individuals from the SN+ group scored below the cut-off in the BNT (SN- = 8.4%, SN+ = 20.8%, p = 0.01) and TMT-B (SN- = 6.9%, SN+ = 16.7%, p = 0.02), compared to the SN- group.

Conclusion: This study confirms poorer performance of healthy individuals with SN+ compared to SN- in specific cognitive domains. However, against the SN- group, the cognitive profile of the SN+ group was not fully consistent with the profile of early PD patients. Our data argues that cognitive impairment associated with SN+ might differ slightly from that seen in early PD. Compensational mechanisms in the early phases of neurodegeneration, and the fact that only a subgroup of SN+ will develop PD, may partly explain these differences.