Emotion Recognition and Traffic-Related Risk-Taking Behavior in Patients with Neurodegenerative Diseases

Objectives : Neurodegenerative diseases (NDDs), such as Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, and Huntington's disease, inevitably lead to impairments in higher-order cognitive functions, including the perception of emotional cues and decision-making behavior. Such impairments are likely to cause risky daily life behavior, for instance, in traffic. Impaired recognition of emotional expressions, such as fear, is considered a marker of impaired experience of emotions. Lower fear experience can, in turn, be related to risk-taking behavior. The aim of our study was to investigate whether impaired emotion recognition in patients with NDD is indeed related to unsafe decision-making in risky everyday life situations, which has not been investigated yet.  Methods: Fifty-one patients with an NDD were included. Emotion recognition was measured with the Facial Expressions of Emotions: Stimuli and Test (FEEST). Risk-taking behavior was measured with driving simulator scenarios and the Action Selection Test (AST). Data from matched healthy controls were used: FEEST (n = 182), AST (n = 36), and driving simulator (n = 18).   Results: Compared to healthy controls, patients showed significantly worse emotion recognition, particularly of anger, disgust, fear, and sadness. Furthermore, patients took significantly more risks in the driving simulator rides and the AST. Only poor recognition of fear was related to a higher amount of risky decisions in situations involving a direct danger.   Conclusions: To determine whether patients with an NDD are still fit to drive, it is crucial to assess their ability to make safe decisions. Measuring emotion recognition may be a valuable contribution to this judgment

Feasibility of pharmacokinetic parametric PET images in scaled subprofile modelling using principal component analysis

Scaled subprofile model using principal component analysis (SSM/PCA) is a multivariate analysis technique used, mainly in [18F]-2-fluoro-2-deoxy-D-glucose (FDG) PET studies, for the generation of disease-specific metabolic patterns (DP) that may aid with the classification of subjects with neurological disorders, like Alzheimer's disease (AD). The aim of this study was to explore the feasibility of using quantitative parametric images for this type of analysis, with dynamic [11C]-labelled Pittsburgh Compound B (PIB) PET data as an example. Therefore, 15 AD patients and 15 healthy control subjects were included in an SSM/PCA analysis to generate four AD-DPs using relative cerebral blood flow (R1), binding potential (BPND) and SUVR images derived from dynamic PIB and static FDG-PET studies. Furthermore, 49 new subjects with a variety of neurodegenerative cognitive disorders were tested against these DPs. The AD-DP was characterized by a reduction in the frontal, parietal, and temporal lobes voxel values for R1 and SUVR-FDG DPs; and by a general increase of values in cortical areas for BPND and SUVR-PIB DPs. In conclusion, the results suggest that the combination of parametric images derived from a single dynamic scan might be a good alternative for subject classification instead of using 2 independent PET studies

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Background and Objectives 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson’s disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer’s disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory. Methods We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories. Results The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman’s rho =0.62, P=0.004). Conclusion In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages

Widespread white matter aberration is associated with the severity of apathy in amnestic Mild Cognitive Impairment:Tract-based spatial statistics analysis

Apathy is recognized as a prevalent behavioral symptom of amnestic Mild Cognitive Impairment (aMCI). In aMCI, apathy is associated with an increased risk and increases the risk of progression to Alzheimer's Disease (AD). Previous DTI study in aMCI showed that apathy has been associated with white matter alterations in the cingulum, middle and inferior longitudinal fasciculus, fornix, and uncinate fasciculus. However, the underlying white matter correlates associated with apathy in aMCI are still unclear. We investigated this relationship using whole-brain diffusion tensor imaging (DTI). Twenty-nine aMCI patients and 20 matched cognitively healthy controls were included. Apathy severity was assessed using the Apathy Evaluation Scale Clinician version. We applied the tract-based spatial statistics analyses to DTI parameters: fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity to investigate changes in white matter pathways associated with the severity of apathy. No significant difference was found in any of the DTI parameters between aMCI and the control group. In aMCI, higher severity of apathy was associated with lower FA in various white matter pathways including the left anterior part of inferior fronto-occipital fasciculus/uncinate fasciculus, genu and body of the corpus callosum, superior and anterior corona radiata, anterior thalamic radiation of both hemispheres and in the right superior longitudinal fasciculus/anterior segment of arcuate fasciculus (p < .05, TFCE-corrected) after controlling for age, gender and GDS non-apathy. A trend association was observed in the right posterior corona radiata and corticospinal tract/internal capsule, and bilateral forceps minor (p < .065, TFCE-corrected). In conclusion, in aMCI, severity of apathy is associated with aberrant white matter integrity in widely distributed pathways, within and between hemispheres

Uptake and effectiveness of a tailor-made online lifestyle programme targeting modifiable risk factors for dementia among middle-aged descendants of people with recently diagnosed dementia:study protocol of a cluster randomised controlled trial (Demin study)

INTRODUCTION: Descendants of patients with dementia have a higher risk to develop dementia. This study aims to investigate the uptake and effectiveness of an online tailor-made lifestyle programme for dementia risk reduction (DRR) among middle-aged descendants of people with recently diagnosed late-onset dementia. METHODS AND ANALYSIS: Demin is a cluster randomised controlled trial, aiming to include 21 memory clinics of which 13 will be randomly allocated to the passive (poster and flyer in a waiting room) and 8 to the active recruitment strategy (additional personal invitation by members of the team of the memory clinic). We aim to recruit 378 participants (40-60 years) with a parent who is recently diagnosed with Alzheimer's disease or vascular dementia at one of the participating memory clinics. All participants receive a dementia risk assessment (online questionnaire, physical examination and blood sample) and subsequently an online tailor-made lifestyle advice regarding protective (Mediterranean diet, low/moderate alcohol consumption and high cognitive activity) and risk factors (physical inactivity, smoking, loneliness, cardiovascular diseases (CVD), hypertension, high cholesterol, diabetes, obesity, renal dysfunction and depression) for dementia. The primary outcome is the difference in uptake between the two recruitment strategies. Secondary outcomes are change(s) in (1) the Lifestyle for Brain Health score, (2) individual health behaviours, (3) health beliefs and attitudes towards DRR and (4) compliance to the tailor-made lifestyle advice. Outcomes will be measured at 3, 6, 9 and 12 months after baseline. The effectiveness of this online tailor-made lifestyle programme will be evaluated by comparing Demin participants to a matched control group (lifelines cohort). ETHICS AND DISSEMINATION: This study has been approved by the Dutch Ministry of Health, Welfare and Sport according to the Population Screening Act. All participants have to give online informed consent using SMS-tan (transaction authentication number delivered via text message). Findings will be disseminated through peer-reviewed journals and (inter)national conferences. TRIAL REGISTRATION NUMBER: NTR7434

Relative cerebral flow from dynamic PIB scans as an alternative for FDG scans in Alzheimer's disease PET studies

In Alzheimer's Disease (AD) dual-tracer positron emission tomography (PET) studies with 2-[F-18]-fluoro-2-deoxy-D-glucose (FDG) and C-11-labelled Pittsburgh Compound B (PIB) are used to assess metabolism and cerebral amyloid-beta deposition, respectively. Regional cerebral metabolism and blood flow (rCBF) are closely coupled, both providing an index for neuronal function. The present study compared PIB-derived rCBF, estimated by the ratio of tracer influx in target regions relative to reference region (R-1) and early-stage PIB uptake (ePIB), to FDG scans. Fifteen PIB positive (+) patients and fifteen PIB negative (-) subjects underwent both FDG and PIB PET scans to assess the use of R-1 and ePIB as a surrogate for FDG. First, subjects were classified based on visual inspection of the PIB PET images. Then, discriminative performance (PIB+ versus PIB-) of rCBF methods were compared to normalized regional FDG uptake. Strong positive correlations were found between analyses, suggesting that PIB-derived rCBF provides information that is closely related to what can be seen on FDG scans. Yet group related differences between method's distributions were seen as well. Also, a better correlation with FDG was found for R-1 than for ePIB. Further studies are needed to validate the use of R-1 as an alternative for FDG studies in clinical applications

Zelfverwaarlozing bij ouderen, een complex probleem

A 76-year-old man presented at the emergency department with functional decline and extreme self-neglect. He died after a few days. The probable cause of death was pneumonia. His family consented to autopsy. Surprisingly, the neuropathological findings showed a tauopathy consistent with fronto-temporal dementia. Self-neglect in the elderly is a common and complex problem associated with high mortality and morbidity. This syndrome requires a thorough workup to detect possible causes. The most common etiologies are neurodegenerative disorders, psychiatric illness and alcohol abuse. It is important to elucidate the cause of self-neglect in order to give the proper treatment and support to the patient and family

Self-neglect in older adults--a complex problem

A 76-year-old man presented at the emergency department with functional decline and extreme self-neglect. He died after a few days. The probable cause of death was pneumonia. His family consented to autopsy. Surprisingly, the neuropathological findings showed a tauopathy consistent with fronto-temporal dementia. Self-neglect in the elderly is a common and complex problem associated with high mortality and morbidity. This syndrome requires a thorough workup to detect possible causes. The most common etiologies are neurodegenerative disorders, psychiatric illness and alcohol abuse. It is important to elucidate the cause of self-neglect in order to give the proper treatment and support to the patient and family.</p