Imaging markers of cerebral small vessel disease

Vascular cognitive impairment (VCI) is the second most common cause of cognitive impairment in the elderly population and it very often co-occurs with impairment resulting from other neurodegenerative pathologies. Cognitive impairment due to vascular pathology is potentially treatable; i.e. the progression could be slowed or even stopped by managing the underlying vascular disease. However, there is no specific treatment available for VCI up to date. One of the main reasons for this is an insufficient understanding of the disease pathophysiology. Cerebral small vessel disease is the primary pathology leading to VCI and therefore its study provides the chance to elucidate the mechanisms leading from vascular pathology to cognitive impairment. Understanding the underlying disease mechanisms is crucial for diagnosis, prevention and managing the disease. For this purpose, markers play an important role, as they indicate which disease processes are at play within the brain. This PhD-work aimed at finding optimal imaging markers for diagnosing cerebral small vessel diseases and estimating the vascular disease burden in the brain. Advances in brain imaging tools, in particular diffusion tensor imaging (DTI), have enabled the exploration of microstructural changes in the human brain, which precede the occurrence of lesions that are visible on conventional MRI. The first project focused on developing and establishing a DTI-based imaging marker for small vessel disease that is quantitative, reliable, and fully automated. This marker (peak width of skeletonized mean diffusivity, PSMD) was then systematically investigated - along with conventional imaging markers - in patients with hereditary and sporadic SVD, memory clinic patients as well as in patients with Alzheimer pathology. The results showed that PSMD outperformed the conventional markers in explaining the cognitive impairment scores. Furthermore, in longitudinal analysis, PSMD was more sensitive to disease related changes than any other imaging markers, which resulted in low sample size estimations for a hypothetical clinical trial. Additionally. PSMD showed very high interscanner reproducibility suggesting that it might be especially useful in multicenter studies. Interestingly, increases in PSMD were mostly linked to vascular but not to neurodegenerative disease. Therefore, PSMD could be a valuable tool to disentangle effects caused by these different pathologies, a common challenge in understanding cognitive impairment. This suggests that the newly established marker PSMD could be easily applied to large samples and may be of great utility for both research studies and clinical use. The second project focused on the evaluation of cortical superficial siderosis (cSS) as a potential new marker for cerebral small vessel diseases. cSS emerged recently as a marker for cerebral amyloid angiopathy (CAA). However, the presence of cSS is associated with many other signs of cSVD, such as cerebral microbleeds (CMB) and white matter hyperintensities (WMH), and therefore its specificity for CAA was questionable. The results of the second project revealed that the distribution patterns and frequency of CMB and WMH overlap between different subtypes of cSVD. This clearly demonstrated that these imaging features have limited discriminative value. More importantly, the presence of cSS was found to be strongly indicative of CAA. To summarize, the key findings reported in this PhD-work have important implications for diagnosing patients with cerebral small vessel disease, disentangling underlying pathologies, as well as for managing and treating the disease. The newly established imaging marker PSMD can be utilized to select the target population for clinical studies and may function as a surrogate marker for treatment effects. PSMD can be further used to identify patients who have a low disease burden as targets for prevention and early treatment

Structural lubricity under ambient conditions.

Despite its fundamental importance, physical mechanisms that govern friction are poorly understood. While a state of ultra-low friction, termed structural lubricity, is expected for any clean, atomically flat interface consisting of two different materials with incommensurate structures, some associated predictions could only be quantitatively confirmed under ultra-high vacuum (UHV) conditions so far. Here, we report structurally lubric sliding under ambient conditions at mesoscopic (∼4,000-130,000 nm(2)) interfaces formed by gold islands on graphite. Ab initio calculations reveal that the gold-graphite interface is expected to remain largely free from contaminant molecules, leading to structurally lubric sliding. The experiments reported here demonstrate the potential for practical lubrication schemes for micro- and nano-electromechanical systems, which would mainly rely on an atomic-scale structural mismatch between the slider and substrate components, via the utilization of material systems featuring clean, atomically flat interfaces under ambient conditions

Imaging markers of cerebral small vessel disease

Vascular cognitive impairment (VCI) is the second most common cause of cognitive impairment in the elderly population and it very often co-occurs with impairment resulting from other neurodegenerative pathologies. Cognitive impairment due to vascular pathology is potentially treatable; i.e. the progression could be slowed or even stopped by managing the underlying vascular disease. However, there is no specific treatment available for VCI up to date. One of the main reasons for this is an insufficient understanding of the disease pathophysiology. Cerebral small vessel disease is the primary pathology leading to VCI and therefore its study provides the chance to elucidate the mechanisms leading from vascular pathology to cognitive impairment. Understanding the underlying disease mechanisms is crucial for diagnosis, prevention and managing the disease. For this purpose, markers play an important role, as they indicate which disease processes are at play within the brain. This PhD-work aimed at finding optimal imaging markers for diagnosing cerebral small vessel diseases and estimating the vascular disease burden in the brain. Advances in brain imaging tools, in particular diffusion tensor imaging (DTI), have enabled the exploration of microstructural changes in the human brain, which precede the occurrence of lesions that are visible on conventional MRI. The first project focused on developing and establishing a DTI-based imaging marker for small vessel disease that is quantitative, reliable, and fully automated. This marker (peak width of skeletonized mean diffusivity, PSMD) was then systematically investigated - along with conventional imaging markers - in patients with hereditary and sporadic SVD, memory clinic patients as well as in patients with Alzheimer pathology. The results showed that PSMD outperformed the conventional markers in explaining the cognitive impairment scores. Furthermore, in longitudinal analysis, PSMD was more sensitive to disease related changes than any other imaging markers, which resulted in low sample size estimations for a hypothetical clinical trial. Additionally. PSMD showed very high interscanner reproducibility suggesting that it might be especially useful in multicenter studies. Interestingly, increases in PSMD were mostly linked to vascular but not to neurodegenerative disease. Therefore, PSMD could be a valuable tool to disentangle effects caused by these different pathologies, a common challenge in understanding cognitive impairment. This suggests that the newly established marker PSMD could be easily applied to large samples and may be of great utility for both research studies and clinical use. The second project focused on the evaluation of cortical superficial siderosis (cSS) as a potential new marker for cerebral small vessel diseases. cSS emerged recently as a marker for cerebral amyloid angiopathy (CAA). However, the presence of cSS is associated with many other signs of cSVD, such as cerebral microbleeds (CMB) and white matter hyperintensities (WMH), and therefore its specificity for CAA was questionable. The results of the second project revealed that the distribution patterns and frequency of CMB and WMH overlap between different subtypes of cSVD. This clearly demonstrated that these imaging features have limited discriminative value. More importantly, the presence of cSS was found to be strongly indicative of CAA. To summarize, the key findings reported in this PhD-work have important implications for diagnosing patients with cerebral small vessel disease, disentangling underlying pathologies, as well as for managing and treating the disease. The newly established imaging marker PSMD can be utilized to select the target population for clinical studies and may function as a surrogate marker for treatment effects. PSMD can be further used to identify patients who have a low disease burden as targets for prevention and early treatment

Validation of the Remote Automated ki:e Speech Biomarker for Cognition in Mild Cognitive Impairment:Verification and Validation following DiME V3 Framework

INTRODUCTION: Progressive cognitive decline is the cardinal behavioral symptom in most dementia-causing diseases such as Alzheimer's disease. While most well-established measures for cognition might not fit tomorrow's decentralized remote clinical trials, digital cognitive assessments will gain importance. We present the evaluation of a novel digital speech biomarker for cognition (SB-C) following the Digital Medicine Society's V3 framework: verification, analytical validation, and clinical validation. METHODS: Evaluation was done in two independent clinical samples: the Dutch DeepSpA (N = 69 subjective cognitive impairment [SCI], N = 52 mild cognitive impairment [MCI], and N = 13 dementia) and the Scottish SPeAk datasets (N = 25, healthy controls). For validation, two anchor scores were used: the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating (CDR) scale. RESULTS: Verification: The SB-C could be reliably extracted for both languages using an automatic speech processing pipeline. Analytical Validation: In both languages, the SB-C was strongly correlated with MMSE scores. Clinical Validation: The SB-C significantly differed between clinical groups (including MCI and dementia), was strongly correlated with the CDR, and could track the clinically meaningful decline. CONCLUSION: Our results suggest that the ki:e SB-C is an objective, scalable, and reliable indicator of cognitive decline, fit for purpose as a remote assessment in clinical early dementia trials

Do We Adopt the Intentional Stance Toward Humanoid Robots?

In daily social interactions, we need to be able to navigate efficiently through our social environment. According to Dennett (1971), explaining and predicting others’ behavior with reference to mental states (adopting the intentional stance) allows efficient social interaction. Today we also routinely interact with artificial agents: from Apple’s Siri to GPS navigation systems. In the near future, we might start casually interacting with robots. This paper addresses the question of whether adopting the intentional stance can also occur with respect to artificial agents. We propose a new tool to explore if people adopt the intentional stance toward an artificial agent (humanoid robot). The tool consists in a questionnaire that probes participants’ stance by requiring them to choose the likelihood of an explanation (mentalistic vs. mechanistic) of a behavior of a robot iCub depicted in a naturalistic scenario (a sequence of photographs). The results of the first study conducted with this questionnaire showed that although the explanations were somewhat biased toward the mechanistic stance, a substantial number of mentalistic explanations were also given. This suggests that it is possible to induce adoption of the intentional stance toward artificial agents, at least in some contexts

Structural lubricity under ambient conditions.

Despite its fundamental importance, physical mechanisms that govern friction are poorly understood. While a state of ultra-low friction, termed structural lubricity, is expected for any clean, atomically flat interface consisting of two different materials with incommensurate structures, some associated predictions could only be quantitatively confirmed under ultra-high vacuum (UHV) conditions so far. Here, we report structurally lubric sliding under ambient conditions at mesoscopic (∼4,000-130,000 nm(2)) interfaces formed by gold islands on graphite. Ab initio calculations reveal that the gold-graphite interface is expected to remain largely free from contaminant molecules, leading to structurally lubric sliding. The experiments reported here demonstrate the potential for practical lubrication schemes for micro- and nano-electromechanical systems, which would mainly rely on an atomic-scale structural mismatch between the slider and substrate components, via the utilization of material systems featuring clean, atomically flat interfaces under ambient conditions

Do we adopt the Intentional Stance towards humanoid robots?

In daily social interactions, we need to be able to navigate efficiently through our social environment. According to Dennett (1971), explaining and predicting others’ behavior with reference to mental states (adopting the intentional stance) allows efficient social interaction. Today we also routinely interact with artificial agents: from Apple’s Siri to GPS navigation systems. In the near future, we might start casually interacting with robots. This paper addresses the question of whether adopting the intentional stance can also occur with respect to artificial agents. We propose a new tool to explore if people adopt the intentional stance toward an artificial agent (humanoid robot). The tool consists in a questionnaire that probes participants’ stance by requiring them to choose the likelihood of an explanation (mentalistic vs. mechanistic) of a behavior of a robot iCub depicted in a naturalistic scenario (a sequence of photographs). The results of the first study conducted with this questionnaire showed that although the explanations were somewhat biased toward the mechanistic stance, a substantial number of mentalistic explanations were also given. This suggests that it is possible to induce adoption of the intentional stance toward artificial agents, at least in some contexts

Bilateral Choroidal Metastases from Lung Adenocarcinoma: A Case Report

The most common malignancy of the eye is metastatic tumors, with choroidal metastases being the majority of them. In women, breast cancer is the most common cause of orbital metastases, and in men, it is lung cancer. Despite the fact that there are efficient treatment options for orbital metastases, the benefit of procedures to detect choroidal metastases is debatable due to the quick progression and poor prognosis of lung cancer. In choroidal metastases resulting from lung cancer, patients are usually presented with decreased sight. Defects in the field of vision, flashes of light and floating bodies generally follow. Treatment options of choroidal metastases include many methods including laser photocoagulation, cryotherapy, chemotherapy, radiotherapy, surgical resection, enucleation and photodynamic therapy. There are reports emphasizing radiotherapy as the most efficient treatment option. In this case report, we sum up the case of a male patient presenting with blurry vision in both eyes, who was subsequently detected to have bilateral choroidal metastatic tumor and was diagnosed with primary lung adenocarcinoma. (C) 2016 The Author(s) Published by S. Karger AG, Base

A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms

Objective: To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD. Methods: We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study. Results: PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10-3 and 1.8 × 10-10). PSMD explained most of the variance in processing speed (R2 ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers. Interpretation: PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use