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Objectives: Neuropsychiatric symptoms are related to disease progression and cognitive decline over time in cerebral small vessel disease (SVD) but their significance is poorly understood in covert SVD. We investigated neuropsychiatric symptoms and their relationships between cognitive and functional abilities in subjects with varying degrees of white matter hyperintensities (WMH), but without clinical diagnosis of stroke, dementia or significant disability. Methods: The Helsinki Small Vessel Disease Study consisted of 152 subjects, who underwent brain magnetic resonance imaging (MRI) and comprehensive neuropsychological evaluation of global cognition, processing speed, executive functions, and memory. Neuropsychiatric symptoms were evaluated with the Neuropsychiatric Inventory Questionnaire (NPI-Q, n = 134) and functional abilities with the Amsterdam Instrumental Activities of Daily Living questionnaire (A-IADL, n = 132), both filled in by a close informant. Results: NPI-Q total score correlated significantly with WMH volume (r s = 0.20, p = 0.019) and inversely with A-IADL score (r s = −0.41, p < 0.001). In total, 38% of the subjects had one or more informant-evaluated neuropsychiatric symptom. Linear regressions adjusted for age, sex, and education revealed no direct associations between neuropsychiatric symptoms and cognitive performance. However, there were significant synergistic interactions between neuropsychiatric symptoms and WMH volume on cognitive outcomes. Neuropsychiatric symptoms were also associated with A-IADL score irrespective of WMH volume. Conclusions: Neuropsychiatric symptoms are associated with an accelerated relationship between WMH and cognitive impairment. Furthermore, the presence of neuropsychiatric symptoms is related to worse functional abilities. Neuropsychiatric symptoms should be routinely assessed in covert SVD as they are related to worse cognitive and functional outcomes. [ABSTRACT FROM AUTHOR]

Background: Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH). Methods: Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation. Results: Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single‐leg stance, timed up‐and‐go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant‐evaluated IADL, but not on self‐evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up‐and‐go performance. Conclusion: The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment. [ABSTRACT FROM AUTHOR]

Background: When MRI images of patients with memory problems are assessed, the presence of lacunar infarcts is evaluated. Lacunar infarcts, fluid‐filled cavities of 3‐15 mm in diameter, are one possible result of cerebral small vessel disease and therefore relevant in dementia diagnostics. In this study, we propose an automated tool for detecting lacunar infarcts on MRI images. Method: We adapted our previous approach [1] in three ways: 1) post‐processing steps were added to the convolutional neural network segmentation pipeline, e.g., to exclude enlarged perivascular spaces and segmentations located inside sulci or ventricles, 2) memory clinic data from the Amsterdam Dementia Cohort and PredictND cohort were included in addition to the LADIS cohort data, and 3) the ground truth was defined by three experienced neuroradiologists (A, B, C) instead of one rater. T1 and T2‐FLAIR images were available for all cases and T2 for a subset in visual rating. The dataset was composed of 393 subjects and each expert rated 1156 potential lacunar infarcts as "1 = no", "2 = probably no", "3 = probably yes" or "4 = yes". A consensus (CO) was created by calculating the average and using a cutoff at 2.5. The agreement was measured between individual raters (A‐B, B‐C, A‐C), between automatic rating and individual raters (AU‐A, AU‐B, AU‐C), and between the automatic rating and the consensus rating (AU‐CO) using Kappa. Correlation coefficient for the number of lacunar infarcts per subject was defined. Cross‐validation was used in training the algorithm. Result: Out of 1156 candidate regions evaluated, 540 were considered as lacunar infarcts based on consensus. The individual raters agreed with each other in 74% of cases whether the shown lesion was lacunar infarct (kappa = 0.48). Correspondingly, automatic rating agreed with the individual raters in 74% of cases (kappa = 0.47). When automatic rating was compared with consensus, agreement/accuracy was 78% (kappa = 0.55). The correlation coefficient for the number of lacunar infarcts detected automatically from the whole image and visually (consensus) was 0.85 (Figure 1). Conclusion: This study suggests that the agreement in detecting lacunar infarcts automatically is comparable to inter‐rater variability between experienced neuroradiologists. [1] Jokinen et al. Stroke 2020 Nov 9; 50(1) [ABSTRACT FROM AUTHOR]