Search

Background: Cognitive impairment is common in patients with heart failure (HF) and impacts patients' life. Sex differences in HF-characteristics are well-established. We hypothesized that women and men with HF also differ in cognitive functioning and that this may be related to sex differences in HF-characteristics and vascular brain injury., Methods: In the Heart-Brain Connection Study, 162 clinically stable HF patients (mean age 69.7 ± 10.0, 33 % women) underwent neuropsychological assessments and brain-MRI. Test results were standardized into z-scores for memory, language, attention/speed, executive functioning, and global cognition. Using linear models adjusted for age and education, we calculated sex differences (women-to-men: W-M∆) in cognitive functioning and examined effects of HF- and vascular brain injury-characteristics on these differences., Results: Men more often had an ischemic cause of HF and lower NYHA-classes, whereas women more often had preserved left ventricular ejection fractions (LVEF). Women had a higher volume of white matter hyperintensities (WMHs) whereas non-lacunar infarcts and microbleeds were more prevalent in men. Women performed better on global cognition than men (W-M∆ in z-score 0.20, 95 %CI 0.03-0.37), predominantly on memory (0.40, 0.02-0.78). These differences were associated with ischemic HF-etiology, as adjustment attenuated these sex differences. After adjustment for non-lacunar infarcts, global cognition difference persisted, but the difference in memory functioning attenuated. Adjustments for NYHA-class, LVEF, WMHs, and microbleeds did not change the results., Conclusion: Women and men with HF differ in cognitive functioning, predominantly in memory functioning, these differences were related to some sex differences in HF-characteristics and vascular brain injury, but not to all., Competing Interests: Declaration of competing interest None declared., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Orthostatic hypotension (OH) is associated with an increased risk of dementia, potentially attributable to cerebral hypoperfusion. We investigated which patterns and characteristics of OH are related to cognition or to potentially underlying structural brain injury in hemodynamically impaired patients and healthy reference participants., Methods: Participants with carotid occlusive disease or heart failure, and reference participants from the Heart-Brain Connection Study underwent OH measurements, neuropsychological assessment and brain MRI. We analyzed the association between OH, global cognitive functioning, white matter hyperintensity (WMH) volume and brain parenchymal fraction with linear regression. We stratified by participant group, severity and duration of OH, chronotropic incompetence and presence of orthostatic symptoms., Results: Of 337 participants (mean age 67.3 ± 8.8 years, 118 (35.0%) women), 113 (33.5%) had OH. Overall, presence of OH was not associated with cognitive functioning (β: -0.12 [-0.24-0.00]), but we did observe worse cognitive functioning in those with severe OH (≥ 30/15 mmHg; β: -0.18 [-0.34 to -0.02]) and clinically manifest OH (β: -0.30 [-0.52 to -0.08]). These associations did not differ significantly by OH duration or chronotropic incompetence, and were similar between patient groups and reference participants. Similarly, both severe OH and clinically manifest OH were associated with a lower brain parenchymal fraction, and severe OH also with a somewhat higher WMH volume., Conclusions: Severe OH and clinically manifest OH are associated with worse cognitive functioning. This supports the notion that specific patterns and characteristics of OH determine its impact on brain health., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Carole H Sudre reports financial support was provided by Alzheimer’s Society. Marleen de Bruijne reports financial support was provided by Netherlands Organisation for Scientific Research. Kimberlin van Wijnen reports financial support was provided by Netherlands Organisation for Scientific Research. Shuai Chen reports financial support was provided by Netherlands Organisation for Scientific Research. Silvia Ingala, Luigi Lorenzini, Frederik Barkhof reports financial support was provided by EU Framework Horizon 2020 Research and Innovation. Florian Kofler, Bjoern Menze, Benedikt Wiestler reports financial support was provided by Deutsche Forschung Gemeinschaft. Hugo J Kuijf reports financial support was provided by Galen and Hilary Weston Foundation. Juan Domingo Gispert reports financial support was provided by Spanish Ministry of Science and Innovation. Bjoern Menze reports financial support was provided by Helmut Horten Foundation. Florian Dubost reports financial support was provided by Netherlands Organisation for Health Research and Development. Ivan Ezhov reports financial support was provided by DComEx. Marius de Groot reports a relationship with GlaxoSmithKline that includes: employment and equity or stocks. Jose Luis Molinuevo reports a relationship with Lundbeck that includes: employment. Jose Luis Molinuevo reports a relationship with Roche Diagnostics that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Genentech Inc that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Novartis that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Oryzon Genomics, S.A. that includes: board membership, consulting or advisory, and speaking and lecture fees. Juan Domingo Gispert reports a relationship with GE Healthcare that includes: funding grants. Juan Domingo Gispert reports a relationship with Roche Diagnostics that includes: funding grants. Juan Domingo Gispert reports a relationship with Hoffmann-La Roche Limited that includes: funding grants. Juan Domingo Gispert reports a relationship with Biogen that includes: speaking and lecture fees. Juan Domingo Gispert reports a relationship with Philips that includes: speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Lilly that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Green Valley that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Janssen that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with MSD that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Alector that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with BioCross that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with Eisai that includes: board membership, consulting or advisory, and speaking and lecture fees. Jose Luis Molinuevo reports a relationship with ProMIS Neurosciences Inc that includes: board membership, consulting or advisory, and speaking and lecture fees. NVIDIA and Icometrix provided the challenge prizes., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: As disease progression remains poorly understood in multiple sclerosis (MS), we aim to investigate the sequence in which different disease milestones occur using a novel data-driven approach., Methods: We analysed a cohort of 295 relapse-onset MS patients and 96 healthy controls, and considered 28 features, capturing information on T2-lesion load, regional brain and spinal cord volumes, resting-state functional centrality ("hubness"), microstructural tissue integrity of major white matter (WM) tracts and performance on multiple cognitive tests. We used a discriminative event-based model to estimate the sequence of biomarker abnormality in MS progression in general, as well as specific models for worsening physical disability and cognitive impairment., Results: We demonstrated that grey matter (GM) atrophy of the cerebellum, thalamus, and changes in corticospinal tracts are early events in MS pathology, whereas other WM tracts as well as the cognitive domains of working memory, attention, and executive function are consistently late events. The models for disability and cognition show early functional changes of the default-mode network and earlier changes in spinal cord volume compared to the general MS population. Overall, GM atrophy seems crucial due to its early involvement in the disease course, whereas WM tract integrity appears to be affected relatively late despite the early onset of WM lesions., Conclusion: Data-driven modelling revealed the relative occurrence of both imaging and non-imaging events as MS progresses, providing insights into disease propagation mechanisms, and allowing fine-grained staging of patients for monitoring purposes., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI). We used a conventional support vector machine (SVM) and a deep convolutional neural network (CNN) approach based on structural MRI scans that underwent either minimal pre-processing or more extensive pre-processing into modulated gray matter (GM) maps. Classifiers were optimized and evaluated using cross-validation in the Alzheimer's Disease Neuroimaging Initiative (ADNI; 334 AD, 520 CN). Trained classifiers were subsequently applied to predict conversion to AD in ADNI MCI patients (231 converters, 628 non-converters) and in the independent Health-RI Parelsnoer Neurodegenerative Diseases Biobank data set. From this multi-center study representing a tertiary memory clinic population, we included 199 AD patients, 139 participants with subjective cognitive decline, 48 MCI patients converting to dementia, and 91 MCI patients who did not convert to dementia. AD-CN classification based on modulated GM maps resulted in a similar area-under-the-curve (AUC) for SVM (0.940; 95%CI: 0.924-0.955) and CNN (0.933; 95%CI: 0.918-0.948). Application to conversion prediction in MCI yielded significantly higher performance for SVM (AUC = 0.756; 95%CI: 0.720-0.788) than for CNN (AUC = 0.742; 95%CI: 0.709-0.776) (p<0.01 for McNemar's test). In external validation, performance was slightly decreased. For AD-CN, it again gave similar AUCs for SVM (0.896; 95%CI: 0.855-0.932) and CNN (0.876; 95%CI: 0.836-0.913). For prediction in MCI, performances decreased for both SVM (AUC = 0.665; 95%CI: 0.576-0.760) and CNN (AUC = 0.702; 95%CI: 0.624-0.786). Both with SVM and CNN, classification based on modulated GM maps significantly outperformed classification based on minimally processed images (p=0.01). Deep and conventional classifiers performed equally well for AD classification and their performance decreased only slightly when applied to the external cohort. We expect that this work on external validation contributes towards translation of machine learning to clinical practice., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: To investigate the relationship between Alzheimer's disease biomarkers and neuropsychiatric symptoms., Methods: Data from two large cohort studies, the Dutch Parelsnoer Institute - Neurodegenerative Diseases and the Alzheimer's Disease Neuroimaging Initiative was used, including subjects with subjective cognitive decline (N = 650), mild cognitive impairment (N = 887), and Alzheimer's disease dementia (N = 626). Cerebrospinal fluid (CSF) levels of Aβ 42 , t-tau, p-tau, and hippocampal volume were associated with neuropsychiatric symptoms (measured with the Neuropsychiatric Inventory) using multiple logistic regression analyses. The effect of the Mini-Mental State Examination (as proxy for cognitive functioning) on these relationships was assessed with mediation analyses., Results: Alzheimer's disease biomarkers were not associated with depression, agitation, irritability, and sleep disturbances. Lower levels of CSF Aβ 42 , higher levels of t- and p-tau were associated with presence of anxiety. Lower levels of CSF Aβ 42 and smaller hippocampal volumes were associated with presence of apathy. All associations were mediated by cognitive functioning., Conclusion: The association between Alzheimer's disease pathology and anxiety and apathy is partly due to impairment in cognitive functioning., (Copyright © 2020 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)

Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols. Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used. Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R 2 EBM  = 0.866; R 2 DEBM  = 0.906). In discriminant analyses, significant differences (p-value ≤ 0.05) between the staging of subjects from training and test sets were observed in both models. No significant difference between the staging of subjects from the training and test was observed (p-value > 0.05) when considering a subset composed by 562 subjects for which all biomarker families (cognitive, imaging and CSF) are available. Event sequence obtained with DEBM recapitulates the heuristic models in a data-driven fashion and is clinically plausible. We demonstrated inter-cohort transferability of two disease progression models and their robustness in detecting AD phases. This is an important step towards the adoption of data-driven statistical models into clinical domain., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

This study investigates regional coherence between white matter (WM) microstructure and gray matter (GM) volume and perfusion measures in Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) using a correlational approach. WM-GM coherence, compared with controls, was stronger between cingulum WM and frontotemporal GM in AD, and temporoparietal GM in bvFTD. In addition, in AD compared with controls, coherence was stronger between inferior fronto-occipital fasciculus WM microstructure and occipital GM perfusion. In this first study assessing regional WM-GM coherence in AD and bvFTD, we show that WM microstructure and GM volume and perfusion measures are coherent, particularly in regions implicated in AD and bvFTD pathology. This indicates concurrent degeneration in disease-specific networks. Our methodology allows for the detection of incipient abnormalities that go undetected in conventional between-group analyses., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: 'Phenocopy' frontotemporal dementia (phFTD) patients may clinically mimic the behavioral variant of FTD (bvFTD), but do not show functional decline or abnormalities upon visual inspection of routine neuroimaging. We aimed to identify abnormalities in gray matter (GM) volume and perfusion in phFTD and to assess whether phFTD belongs to the FTD spectrum. We compared phFTD patients with both healthy controls and bvFTD patients., Materials & Methods: Seven phFTD and 11 bvFTD patients, and 20 age-matched controls underwent structural T1-weighted magnetic resonance imaging (MRI) and 3D pseudo-continuous arterial spin labeling (pCASL) at 3T. Normalized GM (nGM) volumes and perfusion, corrected for partial volume effects, were quantified regionally as well as in the entire supratentorial cortex, and compared between groups taking into account potential confounding effects of gender and scanner., Results: PhFTD patients showed cortical atrophy, most prominently in the right temporal lobe. Apart from this regional atrophy, GM volume was generally not different from either controls or from bvFTD. BvFTD however showed extensive frontotemporal atrophy. Perfusion was increased in the left prefrontal cortex compared to bvFTD and to a lesser extent to controls., Conclusion: PhFTD and bvFTD show overlapping cortical structural abnormalities indicating a continuum of changes especially in the frontotemporal regions. Together with functional changes suggestive of a compensatory response to incipient pathology in the left prefrontal regions, these findings are the first to support a possible neuropathological etiology of phFTD and suggest that phFTD may be a neurodegenerative disease on the FTD spectrum.