Early cortical atrophy is related to depression in patients with neuropathologically confirmed Parkinson's disease.

OBJECTIVE: Depression is a common comorbidity in Parkinson's disease (PD) and other synucleinopathies. In non-PD geriatric patients, cortical atrophy has previously been connected to depression. Here, we investigated cortical atrophy and vascular white matter hyperintensities (WMHs) in autopsy-confirmed parkinsonism patients with the focus on clinical depression. METHODS: The sample consisted of 50 patients with a postmortem confirmed neuropathological diagnosis (30 Parkinson's disease [PD], 10 progressive supranuclear palsy [PSP] and 10 multiple system atrophy [MSA]). Each patient had been scanned with brain computerized tomography (CT) antemortem (median motor symptom duration at scanning = 3.0 years), and 19 patients were scanned again after a mean interval of 2.7 years. Medial temporal atrophy (MTA), global cortical atrophy (GCA) and WMHs were evaluated computationally from CT scans using an image quantification tool based on convolutional neural networks. Depression and other clinical parameters were recorded from patient files. RESULTS: Depression was associated with increased MTA after controlling for diagnosis, age, symptom duration, and cognition (p = 0.006). A similar finding was observed with GCA (p = 0.017) but not with WMH (p = 0.47). In PD patients alone, the result was confirmed for MTA (p = 0.021) with the same covariates. In the longitudinal analysis, GCA change per year was more severe in depressed patients than in nondepressed patients (p = 0.029). CONCLUSIONS: Early medial temporal and global cortical atrophy, as detected with automated analysis of CT-images using convolutional neural networks, is associated with clinical depression in parkinsonism patients. Global cortical atrophy seems to progress faster in depressed patients.

Subjective vs informant-reported cognitive complaints have differential clinical significance in covert cerebral small vessel disease.

Objective: Subjective cognitive complaints are common in patients with cerebral small vessel disease (cSVD), yet their relationship with informant evaluations, objective cognitive functions and severity of brain changes are poorly understood. We studied the associations of subjective and informant reports with findings from comprehensive neuropsychological assessment and brain MRI. Method: In the Helsinki SVD Study, 152 older adults with varying degrees of white matter hyperintensities (WMH) but without stroke or dementia were classified as having normal cognition or mild cognitive impairment (MCI) based on neuropsychological criteria. The measures also included continuous domain scores for memory and executive functions. Cognitive complaints were evaluated with the subjective and informant versions of the Prospective and Retrospective Memory Questionnaire (PRMQ) and Dysexecutive Questionnaire (DEX); functional abilities with the Amsterdam Instrumental Activities of Daily Living Questionnaire (A-IADL); and depressive symptoms with the Geriatric Depression Scale (GDS-15). Results: Subjective cognitive complaints correlated significantly with informant reports (r=0.40-0.50, p<0.001). After controlling for demographics, subjective and informant DEX and PRMQ were not related to MCI, memory or executive functions. Instead, subjective DEX and PRMQ significantly associated with GDS-15 and informant DEX and PRMQ with WMH volume and A-IADL. Conclusions: Neither subjective nor informant-reported cognitive complaints associated with objective cognitive performance. Informant-evaluations were related to functional impairment and more severe WMH, whereas subjective complaints only associated with mild depressive symptoms. These findings suggest that awareness of cognitive impairment may be limited in early-stage cSVD and highlight the value of informant assessments in the identification of patients with functional impairment.

Neuropsychiatric symptoms are associated with exacerbated cognitive impairment in covert cerebral small vessel disease.

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 (rs = 0.20, p = 0.019) and inversely with A-IADL score (rs = -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.

Grey matter atrophy in patients with benign multiple sclerosis.

BACKGROUND: Brain atrophy appears during the progression of multiple sclerosis (MS) and is associated with the disability caused by the disease. METHODS: We investigated global and regional grey matter (GM) and white matter (WM) volumes, WM lesion load, and corpus callosum index (CCI), in benign relapsing-remitting MS (BRRMS, n = 35) with and without any treatment and compared those to aggressive relapsing-remitting MS (ARRMS, n = 46). Structures were analyzed by using an automated MRI quantification tool (cNeuro®). RESULTS: The total brain and cerebral WM volumes were larger in BRRMS than in ARRMS (p = .014, p = .017 respectively). In BRRMS, total brain volumes, regional GM volumes, and CCI were found similar whether or not disease-modifying treatment (DMT) was used. The total (p = .033), as well as subcortical (p = .046) and deep WM (p = .041) lesion load volumes were larger in BRRMS patients without DMT. Cortical GM volumes did not differ between BRRMS and ARRMS, but the volumes of total brain tissue (p = .014) and thalami (p = .003) were larger in patients with BRRMS compared to ARRMS. A positive correlation was found between CCI and whole-brain volume in both BRRMS (r = .73, p < .001) and ARRMS (r = .80, p < .01). CONCLUSIONS: Thalamic volume is the most prominent measure to differentiate BRRMS and ARRMS. Validation of automated quantification of CCI provides an additional applicable MRI biomarker to detect brain atrophy in MS.

Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease.

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.

Neurofilament light level correlates with brain atrophy, and cognitive and motor performance.

Background: The usefulness of neurofilament light (NfL) as a biomarker for small vessel disease has not been established. We examined the relationship between NfL, neuroimaging changes, and clinical findings in subjects with varying degrees of white matter hyperintensity (WMH). Methods: A subgroup of participants (n = 35) in the Helsinki Small Vessel Disease Study underwent an analysis of NfL in cerebrospinal fluid (CSF) as well as brain magnetic resonance imaging (MRI) and neuropsychological and motor performance assessments. WMH and structural brain volumes were obtained with automatic segmentation. Results: CSF NfL did not correlate significantly with total WMH volume (r = 0.278, p = 0.105). However, strong correlations were observed between CSF NfL and volumes of cerebral grey matter (r = -0.569, p < 0.001), cerebral cortex (r = -0.563, p < 0.001), and hippocampi (r = -0.492, p = 0.003). CSF NfL also correlated with composite measures of global cognition (r = -0.403, p = 0.016), executive functions (r = -0.402, p = 0.017), memory (r = -0.463, p = 0.005), and processing speed (r = -0.386, p = 0.022). Regarding motor performance, CSF NfL was correlated with Timed Up and Go (TUG) test (r = 0.531, p = 0.001), and gait speed (r = -0.450, p = 0.007), but not with single-leg stance. After adjusting for age, associations with volumes in MRI, functional mobility (TUG), and gait speed remained significant, whereas associations with cognitive performance attenuated below the significance level despite medium to large effect sizes. Conclusion: NfL was strongly related to global gray matter and hippocampal atrophy, but not to WMH severity. NfL was also associated with motor performance. Our results suggest that NfL is independently associated with brain atrophy and functional mobility, but is not a reliable marker for cerebral small vessel disease.

A novel CT-based automated analysis method provides comparable results with MRI in measuring brain atrophy and white matter lesions.

PURPOSE: Automated analysis of neuroimaging data is commonly based on magnetic resonance imaging (MRI), but sometimes the availability is limited or a patient might have contradictions to MRI. Therefore, automated analyses of computed tomography (CT) images would be beneficial. METHODS: We developed an automated method to evaluate medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and the severity of white matter lesions (WMLs) from a CT scan and compared the results to those obtained from MRI in a cohort of 214 subjects gathered from Kuopio and Helsinki University Hospital registers from 2005 - 2016. RESULTS: The correlation coefficients of computational measures between CT and MRI were 0.9 (MTA), 0.82 (GCA), and 0.86 (Fazekas). CT-based measures were identical to MRI-based measures in 60% (MTA), 62% (GCA) and 60% (Fazekas) of cases when the measures were rounded to the nearest full grade variable. However, the difference in measures was 1 or less in 97-98% of cases. Similar results were obtained for cortical atrophy ratings, especially in the frontal and temporal lobes, when assessing the brain lobes separately. Bland-Altman plots and weighted kappa values demonstrated high agreement regarding measures based on CT and MRI. CONCLUSIONS: MTA, GCA, and Fazekas grades can also be assessed reliably from a CT scan with our method. Even though the measures obtained with the different imaging modalities were not identical in a relatively extensive cohort, the differences were minor. This expands the possibility of using this automated analysis method when MRI is inaccessible or contraindicated.

Effects of White Matter Hyperintensities on Verbal Fluency in Healthy Older Adults and MCI/AD.

BACKGROUND: White matter hyperintensities (WMHs) are markers for cerebrovascular pathology, which are frequently seen in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Verbal fluency is often impaired especially in AD, but little research has been conducted concerning the specific effects of WMH on verbal fluency in MCI and AD. OBJECTIVE: Our aim was to examine the relationship between WMH and verbal fluency in healthy old age and pathological aging (MCI/AD) using quantified MRI data. METHODS: Measures for semantic and phonemic fluency as well as quantified MRI imaging data from a sample of 42 cognitively healthy older adults and 44 patients with MCI/AD (total n = 86) were utilized. Analyses were performed both using the total sample that contained seven left-handed/ambidextrous participants, as well with a sample containing only right-handed participants (n = 79) in order to guard against possible confounding effects regarding language lateralization. RESULTS: After controlling for age and education and adjusting for multiple correction, WMH in the bilateral frontal and parieto-occipital areas as well as the right temporal area were associated with semantic fluency in cognitively healthy and MCI/AD patients but only in the models containing solely right-handed participants. CONCLUSION: The results indicate that white matter pathology in both frontal and parieto-occipital cerebral areas may have associations with impaired semantic fluency in right-handed older adults. However, elevated levels of WMH do not seem to be associated with cumulative effects on verbal fluency impairment in patients with MCI or AD. Further studies on the subject are needed.

Associations of cognitive reserve and psychological resilience with cognitive functioning in subjects with cerebral white matter hyperintensities.

BACKGROUND AND PURPOSE: Cerebral small vessel disease is characterized by progressive white matter hyperintensities (WMH) and cognitive decline. However, variability exists in how individuals maintain cognitive capabilities despite significant neuropathology. The relationships between individual cognitive reserve, psychological resilience and cognitive functioning were examined in subjects with varying degrees of WMH. METHODS: In the Helsinki Small Vessel Disease Study, 152 subjects (aged 65-75 years) underwent a comprehensive neuropsychological assessment, evaluation of subjective cognitive complaints and brain magnetic resonance imaging with volumetric WMH evaluation. Cognitive reserve was determined by education (years) and the modified Cognitive Reserve Scale (mCRS). Psychological resilience was evaluated with the Resilience Scale 14. RESULTS: The mCRS total score correlated significantly with years of education (r = 0.23, p < 0.01), but it was not related to age, sex or WMH volume. Together, mCRS score and education were associated with performance in a wide range of cognitive domains including processing speed, executive functions, working memory, verbal memory, visuospatial perception and verbal reasoning. Independently of education, the mCRS score had incremental predictive value on delayed verbal recall and subjective cognitive complaints. Psychological resilience was not significantly related to age, education, sex, WMH severity or cognitive test scores, but it was associated with subjective cognitive complaints. CONCLUSIONS: Cognitive reserve has strong and consistent associations with cognitive functioning in subjects with WMH. Education is widely associated with objective cognitive functioning, whereas lifetime engagement in cognitively stimulating leisure activities (mCRS) has independent predictive value on memory performance and subjective cognitive complaints. Psychological resilience is strongly associated with subjective, but not objective, cognitive functioning.

cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders.

INTRODUCTION: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia. METHODS: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed. Global cognitive score was defined from standard neuropsychological tests and compared to the corresponding estimated score from the cCOG tool containing seven subtasks. The consistency of cCOG was assessed comparing measurements administered in clinical settings and in the home environment. RESULTS: cCOG produced accuracies (receiver operating characteristic-area under the curve [ROC-AUC]) between 0.71 and 0.84 in detecting MCI and 0.86 and 0.94 in detecting dementia when administered at the clinic and at home. The accuracy was comparable to the results of standard neuropsychological tests (AUC 0.69-0.77 MCI/0.91-0.92 dementia). DISCUSSION: cCOG provides a promising tool for detecting MCI and dementia with potential for a cost-effective approach including home-based cognitive assessments.

Thalamic Atrophy Predicts 5-Year Disability Progression in Multiple Sclerosis.

Purpose: Thalamus is among the first brain regions to become atrophic in multiple sclerosis (MS). We studied whether thalamic atrophy predicts disability progression at 5 years in a cohort of Finnish MS patients. Methods: Global and regional brain volumes were measured from 24 newly diagnosed relapsing MS (RMS) patients 6 months after initiation of therapy and from 36 secondary progressive MS (SPMS) patients. The patients were divided into groups based on baseline whole brain parenchymal (BP) and thalamic atrophy. Standard scores (z scores) were computed by comparing individual brain volumes with healthy controls. A z score cutoff of -1.96 was applied to separate atrophic from normal brain volumes. The Expanded Disability Status Scale (EDSS), brain magnetic resonance imaging (MRI) findings, and relapses were assessed at baseline and at 2 years and EDSS progression at 5 years. Results: Baseline thalamus volume predicted disability in 5 years in a logistic regression model (p = 0.031). At 5 years, EDSS was same or better in 12 of 18 patients with no brain atrophy at baseline but only in 5 of 18 patients with isolated thalamic atrophy [odds ratio (OR) (95% CI) = 5.2 (1.25, 21.57)]. The patients with isolated thalamic atrophy had more escalations of disease-modifying therapies during follow-up. Conclusion: Patients with thalamic atrophy at baseline were at a higher risk for 5-year EDSS increase than patients with no identified brain atrophy. Brain volume measurement at a single time point could help predict disability progression in MS and complement clinical and routine MRI evaluation in therapeutic decision-making.

Prognostic value of complementary biomarkers of neurodegeneration in a mixed memory clinic cohort.

BACKGROUND: Biomarkers of neurodegeneration, e.g. MRI brain atrophy and [18F]FDG-PET hypometabolism, are often evaluated in patients suspected of neurodegenerative disease. OBJECTIVE: Our primary objective was to investigate prognostic properties of atrophy and hypometabolism. METHODS: From March 2015-June 2016, 149 patients referred to a university hospital memory clinic were included. The primary outcome was progression/stable disease course as assessed by a clinician at 12 months follow-up. Intracohort defined z-scores of baseline MRI automatic quantified volume and [18F]FDG-PET standardized uptake value ratios were calculated for all unilaterally defined brain lobes and dichotomized as pronounced atrophy (+A)/ pronounced hypometabolism (+H) at z-score <0. A logistic regression model with progression status as the outcome was carried out with number of lobes with the patterns +A/-H, -A/+H, +A/+H respectively as predictors. The model was mutually adjusted along with adjustment for age and sex. A sensitivity analysis with a z-score dichotomization at -0.1 and -0.5 and dichotomization regarding number of lobes affected at one and three lobes was done. RESULTS: Median follow-up time was 420 days [IQR: 387-461 days] and 50 patients progressed. Patients with two or more lobes affected by the pattern +A/+H compared to patients with 0-1 lobes affected had a statistically significant increased risk of progression (odds ratio, 95 % confidence interval: 4.33, 1.90-9.86) in a multivariable model. The model was partially robust to the applied sensitivity analysis. CONCLUSION: Combined atrophy and hypometabolism as assessed by MRI and [18F]FDG-PET in patients under suspicion of neurodegenerative disease predicts progression over 1 year.

Evaluating 2-[18F]FDG-PET in differential diagnosis of dementia using a data-driven decision model.

2-[18F]fluoro-2-deoxy-d-glucose positron emission tomography (2-[18F]FDG-PET) has an emerging supportive role in dementia diagnostic as distinctive metabolic patterns are specific for Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). Previous studies have demonstrated that a data-driven decision model based on the disease state index (DSI) classifier supports clinicians in the differential diagnosis of dementia by using different combinations of diagnostic tests and biomarkers. Until now, this model has not included 2-[18F]FDG-PET data. The objective of the study was to evaluate 2-[18F]FDG-PET biomarkers combined with commonly used diagnostic tests in the differential diagnosis of dementia using the DSI classifier. We included data from 259 subjects diagnosed with AD, DLB, FTD, vascular dementia (VaD), and subjective cognitive decline from two independent study cohorts. We also evaluated three 2-[18F]FDG-PET biomarkers (anterior vs. posterior index (API-PET), occipital vs. temporal index, and cingulate island sign) to improve the classification accuracy for both FTD and DLB. We found that the addition of 2-[18F]FDG-PET biomarkers to cognitive tests, CSF and MRI biomarkers considerably improved the classification accuracy for all pairwise comparisons of DLB (balanced accuracies: DLB vs. AD from 64% to 77%; DLB vs. FTD from 71% to 92%; and DLB vs. VaD from 71% to 84%). The two 2-[18F]FDG-PET biomarkers, API-PET and occipital vs. temporal index, improved the accuracy for FTD and DLB, especially as compared to AD. Moreover, different combinations of diagnostic tests were valuable to differentiate specific subtypes of dementia. In conclusion, this study demonstrated that the addition of 2-[18F]FDG-PET to commonly used diagnostic tests provided complementary information that may help clinicians in diagnosing patients, particularly for differentiating between patients with FTD, DLB, and AD.

Evaluating severity of white matter lesions from computed tomography images with convolutional neural network.

PURPOSE: Severity of white matter lesion (WML) is typically evaluated on magnetic resonance images (MRI), yet the more accessible, faster, and less expensive method is computed tomography (CT). Our objective was to study whether WML can be automatically segmented from CT images using a convolutional neural network (CNN). The second aim was to compare CT segmentation with MRI segmentation. METHODS: The brain images from the Helsinki University Hospital clinical image archive were systematically screened to make CT-MRI image pairs. Selection criteria for the study were that both CT and MRI images were acquired within 6 weeks. In total, 147 image pairs were included. We used CNN to segment WML from CT images. Training and testing of CNN for CT was performed using 10-fold cross-validation, and the segmentation results were compared with the corresponding segmentations from MRI. RESULTS: A Pearson correlation of 0.94 was obtained between the automatic WML volumes of MRI and CT segmentations. The average Dice similarity index validating the overlap between CT and FLAIR segmentations was 0.68 for the Fazekas 3 group. CONCLUSION: CNN-based segmentation of CT images may provide a means to evaluate the severity of WML and establish a link between CT WML patterns and the current standard MRI-based visual rating scale.

Brain volumes in relation to loneliness and social competence in preadolescents born very preterm.

INTRODUCTION: The aim of the present study was to assess how regional brain volumes associate with self-experienced social and emotional loneliness and social competence in very preterm and term-born preadolescents. MATERIALS AND METHODS: Thirty-four very preterm subjects (birthweight ≤1,500 g and/or gestational age <32 weeks) without neurodevelopmental impairments and/or major brain pathologies and 31 term-born subjects underwent magnetic resonance imaging at 12 years of age. Regional brain volumes were measured using an automated image quantification tool. At 11 years of age, social and emotional loneliness were assessed with the Peer Network and Dyadic Loneliness Scale-self-report questionnaire and cooperating skills, empathy, impulsivity, and disruptiveness with the Multisource Assessment of Children's Social Competence Scale-self-report questionnaire. RESULTS: In the very preterm group, a number of significant associations were found between smaller regional brain volumes and self-experienced emotional loneliness, more impulsivity and more disruptiveness. In the control group, brain volumes and loneliness were not associated, and brain volumes and social competence were associated with a lesser degree than in the very preterm group. CONCLUSION: Experiences of emotional loneliness and poorer social competence appear to be more related to brain volumes in very preterm preadolescents than in those born full-term. It also appears that in very preterm preadolescents, emotional loneliness may be more reflected in brain development than social loneliness.

Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic accuracy.

INTRODUCTION: An accurate and timely diagnosis for Alzheimer's disease (AD) is important, both for care and research. The current diagnostic criteria allow the use of CSF biomarkers to provide pathophysiological support for the diagnosis of AD. How these criteria should be operationalized by clinicians is unclear. Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination. METHODS: We included 535 subjects (139 controls, 286 Alzheimer's disease dementia, 82 frontotemporal dementia and 28 vascular dementia) from three clinical cohorts. Positive (AD like) and negative (normal) CSF biomarker profiles were simulated to estimate whether knowledge of CSF biomarkers would impact (confidence in) diagnosis. We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients. RESULTS: The computerized decision support approach recommended CSF testing in 140 (26%) patients, which yielded a diagnosis with sufficient confidence in 379 (71%) of all patients. This approach was more efficient than CSF in none (0% CSF, 308 (58%) diagnosed), CSF selected based on AUC (295 (55%) CSF, 350 (65%) diagnosed) or CSF in all (100% CSF, 348 (65%) diagnosed). CONCLUSIONS: We used a computerized decision support with simulated CSF results in controls and patients with different types of dementia. This approach can support clinicians in making a balanced decision in ordering additional biomarker testing. Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.

Global Burden of Small Vessel Disease-Related Brain Changes on MRI Predicts Cognitive and Functional Decline.

Background and Purpose- Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple types of small vessel disease-related brain changes and examined their individual and combined predictive value on cognitive and functional abilities. Methods- Magnetic resonance imaging scans of 560 older individuals from LADIS (Leukoaraiosis and Disability Study) were analyzed using automated atlas- and convolutional neural network-based segmentation methods yielding volumetric measures of white matter hyperintensities, lacunes, enlarged perivascular spaces, chronic cortical infarcts, and global and regional brain atrophy. The subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years. Results- The strongest predictors of cognitive performance and functional outcome over time were the total volumes of white matter hyperintensities, gray matter, and hippocampi (P<0.001 for global cognitive function, processing speed, executive functions, and memory and P<0.001 for poor functional outcome). Volumes of lacunes, enlarged perivascular spaces, and cortical infarcts were significantly associated with part of the outcome measures, but their contribution was weaker. In a multivariable linear mixed model, volumes of white matter hyperintensities, lacunes, gray matter, and hippocampi remained as independent predictors of cognitive impairment. A combined measure of these markers based on Z scores strongly predicted cognitive and functional outcomes (P<0.001) even above the contribution of the individual brain changes. Conclusions- Global burden of small vessel disease-related brain changes as quantified by an image segmentation tool is a powerful predictor of long-term cognitive decline and functional disability. A combined measure of white matter hyperintensities, lacunar, gray matter, and hippocampal volumes could be used as an imaging marker associated with vascular cognitive impairment.

The Association Between Distinct Frontal Brain Volumes and Behavioral Symptoms in Mild Cognitive Impairment, Alzheimer's Disease, and Frontotemporal Dementia.

Our aim was to investigate the association between behavioral symptoms of agitation, disinhibition, irritability, elation, and aberrant motor behavior to frontal brain volumes in a cohort with various neurodegenerative diseases. A total of 121 patients with mild cognitive impairment (MCI, n = 58), Alzheimer's disease (AD, n = 45) and behavioral variant frontotemporal dementia (bvFTD, n = 18) were evaluated with a Neuropsychiatric Inventory (NPI). A T1-weighted MRI scan was acquired for each participant and quantified with a multi-atlas segmentation method. The volumetric MRI measures of the frontal lobes were associated with neuropsychiatric symptom scores with a linear model. In the regression model, we included CDR score and TMT B time as covariates to account for cognitive and executive functions. The brain volumes were corrected for age, gender and head size. The total behavioral symptom score of the five symptoms of interest was negatively associated with the volume of the subcallosal area (ß = -0.32, p = 0.002). High disinhibition scores were associated with reduced volume in the gyrus rectus (ß = -0.30, p = 0.002), medial frontal cortex (ß = -0.30, p = 0.002), superior frontal gyrus (ß = -0.28, p = 0.003), inferior frontal gyrus (ß = -0.28, p = 0.005) and subcallosal area (ß = -0.28, p = 0.005). Elation scores were associated with reduced volumes of the medial orbital gyrus (ß = -0.30, p = 0.002) and inferior frontal gyrus (ß = -0.28, p = 0.004). Aberrant motor behavior was associated with atrophy of frontal pole (ß = -0.29, p = 0.005) and the subcallosal area (ß = -0.39, p < 0.001). No significant associations with frontal brain volumes were found for agitation and irritability. We conclude that the subcallosal area may be common neuroanatomical area for behavioral symptoms in neurodegenerative diseases, and it appears to be independent of disease etiology.

Midlife Insulin Resistance as a Predictor for Late-Life Cognitive Function and Cerebrovascular Lesions.

BACKGROUND: Type 2 diabetes (T2DM) increases the risk for Alzheimer's disease (AD) but not for AD neuropathology. The association between T2DM and AD is assumed to be mediated through vascular mechanisms. However, insulin resistance (IR), the hallmark of T2DM, has been shown to associate with AD neuropathology and cognitive decline. OBJECTIVE: To evaluate if midlife IR predicts late-life cognitive performance and cerebrovascular lesions (white matter hyperintensities and total vascular burden), and whether cerebrovascular lesions and brain amyloid load are associated with cognitive functioning. METHODS: This exposure-to-control follow-up study examined 60 volunteers without dementia (mean age 70.9 years) with neurocognitive testing, brain 3T-MRI and amyloid-PET imaging. The volunteers were recruited from the Finnish Health 2000 survey (n = 6062) to attend follow-up examinations in 2014-2016 according to their insulin sensitivity in 2000 and their APOE genotype. The exposure group (n = 30) had IR in 2000 and the 30 controls had normal insulin sensitivity. There were 15 APOEɛ4 carriers per group. Statistical analyses were performed with multivariable linear models. RESULTS: At follow-up the IR+group performed worse on executive functions (p = 0.02) and processing speed (p = 0.007) than the IR- group. The groups did not differ in cerebrovascular lesions. No associations were found between cerebrovascular lesions and neurocognitive test scores. Brain amyloid deposition associated with slower processing speed. CONCLUSION: Midlife IR predicted poorer executive functions and slower processing speed, but not cerebrovascular lesions. Brain amyloid deposition was associated with slower processing speed. The association between midlife IR and late-life cognition might not be mediated through cerebrovascular lesions measured here.

Association between Deep Gray Matter Changes and Neurocognitive Function in Mild Cognitive Impairment and Alzheimer's Disease: A Tensor-Based Morphometric MRI Study.

BACKGROUND: Atrophy of the deep gray matter (DGM) has been associated with a risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and the degree of cognitive impairment. However, specific knowledge of the associations between degenerative DGM changes and neurocognitive functions remains limited. OBJECTIVE: To examine degenerative DGM changes and evaluate their association with neurocognitive functions. METHOD: We examined DGM volume changes with tensor-based morphometry (TBM) and analyzed the relationships between DGM changes and neurocognitive functions in control (n = 58), MCI (n = 38), and AD (n = 58) groups with multiple linear regression analyses. RESULTS: In all DGM areas, the AD group had the largest changes in TBM volume. The differences in TBM volume changes were larger between the control group and the AD group than between the other pairs of groups. In the AD group, volume changes of the right thalamus were significantly associated with episodic memory, learning, and semantic processing. Significant or trend-level associations were identified between bilateral caudate nucleus changes and episodic memory as well as semantic processing. In the control and MCI groups, very few significant associations emerged. CONCLUSIONS: Atrophy of the DGM structures, especially the thalamus and caudate nucleus, is related to cognitive impairment in AD. DGM atrophy is associated with tests reflecting both subcortical and cortical cognitive functions.