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14 results on '"Exalto, L. G."'

2. Multimodal tract-based MRI metrics outperform whole brain markers in determining cognitive impact of small vessel disease-related brain injury

Author

De Luca, Alberto, Kuijf, H. J., Exalto, L. G., Thiebaut de Schotten, Michel, Biessels, G. J., van den Berg, E., Frijns, C. J.M., Groeneveld, O., Heinen, R., Heringa, S. M., Kappelle, L. J., Reijmer, Y. D., Verwer, J., Vlegels, N., de Bresser, J., De Luca, A., Leemans, A., Koek, H. L., Hamaker, M., Faaij, R., Pleizier, M., Vriens, E., Neurology, Pediatrics, and Erasmus MC other

Subjects
Aged, 80 and over, Male, Histology, General Neuroscience, Brain, Middle Aged, Magnetic Resonance Imaging, Benchmarking, Cognition, Diffusion Tensor Imaging, Brain Injuries, Cerebral Small Vessel Diseases, Humans, Cognitive Dysfunction, Anatomy, Aged
Abstract

In cerebral small vessel disease (cSVD), whole brain MRI markers of cSVD-related brain injury explain limited variance to support individualized prediction. Here, we investigate whether considering abnormalities in brain tracts by integrating multimodal metrics from diffusion MRI (dMRI) and structural MRI (sMRI), can better capture cognitive performance in cSVD patients than established approaches based on whole brain markers. We selected 102 patients (73.7 ± 10.2 years old, 59 males) with MRI-visible SVD lesions and both sMRI and dMRI. Conventional linear models using demographics and established whole brain markers were used as benchmark of predicting individual cognitive scores. Multi-modal metrics of 73 major brain tracts were derived from dMRI and sMRI, and used together with established markers as input of a feed-forward artificial neural network (ANN) to predict individual cognitive scores. A feature selection strategy was implemented to reduce the risk of overfitting. Prediction was performed with leave-one-out cross-validation and evaluated with the R2 of the correlation between measured and predicted cognitive scores. Linear models predicted memory and processing speed with R2 = 0.26 and R2 = 0.38, respectively. With ANN, feature selection resulted in 13 tract-specific metrics and 5 whole brain markers for predicting processing speed, and 28 tract-specific metrics and 4 whole brain markers for predicting memory. Leave-one-out ANN prediction with the selected features achieved R2 = 0.49 and R2 = 0.40 for processing speed and memory, respectively. Our results show proof-of-concept that combining tract-specific multimodal MRI metrics can improve the prediction of cognitive performance in cSVD by leveraging tract-specific multi-modal metrics.

Published
2022

3. Impact of white matter hyperintensity location on depressive symptoms in memory-clinic patients

Author

Leeuwis, Anna E., Weaver, Nick A., Biesbroek, J. Matthijs, Exalto, L. G., Kuijf, Hugo J., Hooghiemstra, Astrid M., Prins, Niels D., Scheltens, Philip, Barkhof, Frederik, van der Flier, Wiesje M., Biessels, Geert Jan, Benedictus, M. R., Bremer, J., Leijenaar, J., Scheltens, P., Tijms, B. M., Wattjes, M. P., Teunissen, C. E., Koene, T., van den Berg, E., van den Brink, H., Boomsma, J. M. F., Ferro, D. A., Frijns, C. J. M., Groeneveld, O., Heinen, R., Heringa, S. M., Kappelle, L. J., Reijmer, Y. D., Verwer, J., de Bresser, J., Koek, H. L., Boss, H. M., Weinstein, H. C., Neurology, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, APH - Personalized Medicine, APH - Methodology, Immunology, and Pediatrics

Subjects
Male, medicine.medical_specialty, Population, Pyramidal Tracts, Neuroimaging, Comorbidity, computer.software_genre, Cohort Studies, White matter, 03 medical and health sciences, 0302 clinical medicine, Voxel, Internal medicine, medicine, Journal Article, Humans, Dementia, Cognitive Dysfunction, Pharmacology (medical), Cognitive decline, education, Geriatric Assessment, Biological Psychiatry, Aged, Psychiatric Status Rating Scales, education.field_of_study, 030214 geriatrics, Depression, business.industry, Middle Aged, medicine.disease, Magnetic Resonance Imaging, White Matter, Cerebrovascular Disorders, Psychiatry and Mental health, medicine.anatomical_structure, Corticospinal tract, Female, Geriatric Depression Scale, Biological psychiatry, business, computer, 030217 neurology & neurosurgery, Research Paper
Abstract

Background: We investigated the association between white matter hyperintensity location and depressive symptoms in a memoryclinic population using lesion–symptom mapping.Methods: We included 680 patients with vascular brain injury from the TRACE-VCI cohort (mean age ± standard deviation: 67 ± 8 years; 52% female): 168 patients with subjective cognitive decline, 164 with mild cognitive impairment and 348 with dementia. We assessed depressive symptoms using the Geriatric Depression Scale. We applied assumptionfree voxel-based lesion–symptom mapping, adjusted for age, sex, total white matter hyperintensity volume and multiple testing. Next, we applied exploratory region-of-interest linear regression analyses of major white matter tracts, with additional adjustment for diagnosis.Results: Voxel-based lesion–symptom mapping identified voxel clusters related to the Geriatric Depression Scale in the left corticospinal tract. Region-of-interest analyses showed no relation between white matter hyperintensity volume and the Geriatric Depression Scale, but revealed an interaction with diagnosis in the forceps minor, where larger regional white matter hyperintensity volume was associated with more depressive symptoms in subjective cognitive decline (β = 0.26, p < 0.05), but not in mild cognitive impairment or dementia.Limitations: We observed a lack of convergence of findings between voxel-based lesion–symptom mapping and region-of-interest analyses, which may have been due to small effect sizes and limited lesion coverage despite the large sample size. This warrants replication of our findings and further investigation in other cohorts.Conclusion: This lesion–symptom mapping study in depressive symptoms indicates the corticospinal tract and forceps minor as strategic tracts in which white matter hyperintensity is associated with depressive symptoms in memory-clinic patients with vascular brain injury. The impact of white matter hyperintensity on depressive symptoms is modest, but it appears to depend on the location of white matter hyperintensity and disease severity.

Published
2019

4. Prediction of poor clinical outcome in vascular cognitive impairment:TRACE-VCI study

Author

Boomsma, Jooske M.F., Exalto, L. G., Barkhof, Frederik, Chen, Christopher L.H., Hilal, S., Leeuwis, Anna E., Prins, Niels D., Saridin, F. N., Scheltens, Philip, Teunissen, Charlotte E., Verwer, Jurre H., Weinstein, Henry C., van der Flier, W. M., Biessels, G. J., Boomsma, Jooske M.F., Exalto, L. G., Barkhof, Frederik, Chen, Christopher L.H., Hilal, S., Leeuwis, Anna E., Prins, Niels D., Saridin, F. N., Scheltens, Philip, Teunissen, Charlotte E., Verwer, Jurre H., Weinstein, Henry C., van der Flier, W. M., and Biessels, G. J.

Abstract

Introduction: Prognostication in memory clinic patients with vascular brain injury (eg possible vascular cognitive impairment [VCI]) is often uncertain. We created a risk score to predict poor clinical outcome. Methods: Using data from two longitudinal cohorts of memory clinic patients with vascular brain injury without advanced dementia, we created (n = 707) and validated (n = 235) the risk score. Poor clinical outcome was defined as substantial cognitive decline (change of Clinical Dementia Rating ≥1 or institutionalization) or major vascular events or death. Twenty-four candidate predictors were evaluated using Cox proportional hazard models. Results: Age, clinical syndrome diagnosis, Disability Assessment for Dementia, Neuropsychiatric Inventory, and medial temporal lobe atrophy most strongly predicted poor outcome and constituted the risk score (C-statistic 0.71; validation cohort 0.78). Of note, none of the vascular predictors were retained in this model. The 2-year risk of poor outcome was 6.5% for the lowest (0-5) and 55.4% for the highest sum scores (10-13). Discussion: This is the first, validated, prediction score for 2-year clinical outcome of patients with possible VCI.

Published
2020

5. Cerebral amyloid burden is associated with white matter hyperintensity location in specific posterior white matter regions

Author

Weaver, Nick A., Doeven, Thomas, Barkhof, Frederik, Biesbroek, J. Matthijs, Groeneveld, Onno N., Kuijf, H. J., Prins, N. D., Scheltens, Philip, Teunissen, Charlotte E., van der Flier, W. M., Biessels, G. J., Benedictus, M. R., Bremer, J., Leijenaar, J., Scheltens, P., Tijms, B. M., Barkhof, F., Wattjes, M. P., Teunissen, C. E., Koene, T., van den Berg, E., van den Brink, H., Exalto, L. G., Ferro, D. A., Groeneveld, O., Heinen, R., Heringa, S. M., Kappelle, L. J., Reijmer, Y. D., Verwer, J., de Bresser, J., Koek, H. L., Hamaker, M., Faaij, R., Pleizier, M., Vriens, E., Boomsma, J. M. F., Boss, H. M., Weinstein, H. C., Radiology and nuclear medicine, Amsterdam Neuroscience - Neurodegeneration, Neurology, Laboratory Medicine, APH - Personalized Medicine, APH - Methodology, Epidemiology and Data Science, Immunology, Pediatrics, and Erasmus MC other

Subjects
0301 basic medicine, Aging, Pathology, medicine.medical_specialty, Lesion mapping, Amyloid, Amyloid beta, Neuroscience(all), Clinical Neurology, Splenium, tau Proteins, Corpus callosum, White matter, 03 medical and health sciences, 0302 clinical medicine, Cerebrospinal fluid, Magnetic resonance imaging, Alzheimer Disease, mental disorders, medicine, White matter hyperintensities, Journal Article, Humans, Amyloid beta-Peptides, medicine.diagnostic_test, biology, business.industry, General Neuroscience, Alzheimer's disease, White Matter, Peptide Fragments, Hyperintensity, Ageing, 030104 developmental biology, medicine.anatomical_structure, biology.protein, Neurology (clinical), Amyloid-beta, Tau, Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Developmental Biology
Abstract

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease. WMHs are also frequently observed in patients with familial and sporadic Alzheimer's disease, often with a particular posterior predominance. Whether amyloid and tau pathologies are linked to WMH occurrence is still debated. We examined whether cerebral amyloid and tau burden, reflected in cerebrospinal fluid amyloid-beta 1-42 (A beta-42) and phosphorylated tau (p-tau), are related to WMH location in a cohort of 517 memory clinic patients. Two lesion mapping techniques were performed: voxel-based analyses and region of interest-based linear regression. Voxelwise associations were found between lower (A beta-42) and parieto-occipital periventricular WMHs. Regression analyses demonstrated that lower A beta-42 correlated with larger WMH volumes in the splenium of the corpus callosum and posterior thalamic radiation, also after controlling for markers of vascular disease. P-tau was not consistently related to WMH occurrence. Our findings indicate that cerebral amyloid burden is associated with WMHs located in specific posterior white matter regions, possibly reflecting region-specific effects of amyloid pathology on the white matter. (C) 2019 The Authors. Published by Elsevier Inc.

Published
2019

7. Performance of five automated white matter hyperintensity segmentation methods in a multicenter dataset

Author

Heinen, Rutger, Steenwijk, Martijn D., Barkhof, Frederik, Biesbroek, J. Matthijs, van der Flier, Wiesje M., Kuijf, H. J., Prins, N. D., Vrenken, Hugo, Biessels, Geert Jan, de Bresser, Jeroen, van den Berg, E., Boomsma, J. M. F., Exalto, L. G., Ferro, D. A., Frijns, C. J. M., Groeneveld, O. N., van Kalsbeek, N. M., Verwer, J. H., de Bresser, J., Emmelot-Vonk, M. E., Koek, H. L., Benedictus, M. R., Bremer, J., Leeuwis, A. E., Leijenaar, J., Scheltens, P., Tijms, B. M., Wattjes, M. P., Teunissen, C. E., Koene, T., Weinstein, H. C., Hamaker, M., Faaij, R., Pleizier, M., Prins, M., Vriens, E., Anatomy and neurosciences, Radiology and nuclear medicine, Amsterdam Neuroscience - Neurodegeneration, Neurology, APH - Personalized Medicine, APH - Methodology, Other Research, Clinical chemistry, CCA - Imaging and biomarkers, Immunology, Erasmus MC other, and Public Health

Subjects
Male, Computer science, lcsh:Medicine, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Image Interpretation, Computer-Assisted, medicine, Journal Article, Humans, Multicenter Studies as Topic, Segmentation, lcsh:Science, General, Aged, Automation, Laboratory, Multidisciplinary, medicine.diagnostic_test, business.industry, lcsh:R, Magnetic resonance imaging, Pattern recognition, Middle Aged, Magnetic Resonance Imaging, White Matter, Hyperintensity, Stroke, White matter hyperintensity, Female, lcsh:Q, Artificial intelligence, Small vessel, business, Algorithms, 030217 neurology & neurosurgery
Abstract

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease, that is increasingly studied with large, pooled multicenter datasets. This data pooling increases statistical power, but poses challenges for automated WMH segmentation. Although there is extensive literature on the evaluation of automated WMH segmentation methods, such evaluations in a multicenter setting are lacking. We performed WMH segmentations in sixty patients scanned on six different magnetic resonance imaging (MRI) scanners (10 patients per scanner) using five freely available and fully-automated WMH segmentation methods (Cascade, kNN-TTP, Lesion-TOADS, LST-LGA and LST-LPA). Different MRI scanner vendors and field strengths were included. We compared these automated WMH segmentations with manual WMH segmentations as a reference. Performance of each method both within and across scanners was assessed using spatial and volumetric correspondence with the reference segmentations by Dice’s similarity coefficient (DSC) and intra-class correlation coefficient (ICC) respectively. We found the best performance, both within and across scanners, for kNN-TTP, followed by LST-LPA and LST-LGA, with worse performance for Lesion-TOADS and Cascade. Our findings can serve as a guide for choosing a method and also highlight the importance to further improve and evaluate consistency of methods in a multicenter setting.

Published
2019

8. Cortical Microinfarcts and White Matter Connectivity in Memory Clinic Patients

Author

Ferro, Doeschka, Heinen, Rutger, Robalo, Bruno de Brito, Kuijf, Hugo, Biessels, Geert Jan, Reijmer, Yael, van den Berg, E., Brundel, M., Bouvy, W. H., Exalto, L. G., Frijns, C. J. M., Groeneveld, O., Heringa, S. M., Kalsbeek, N., Kappelle, L. J., Reijmer, Y. D., Verwer, J., de Bresser, J., Leemans, A., Luijten, P. R., Viergever, M. A., Vincken, K. L., Zwanenburg, J. J. M., Koek, H. L., Hamaker, M., Faaij, R., Pleizier, M., Vriens, E., Neurology, Pediatrics, and Erasmus MC other

Subjects
medicine.medical_specialty, Neurology, Clinical Neurology, 030204 cardiovascular system & hematology, computer.software_genre, white matter connectivity, lcsh:RC346-429, White matter, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Voxel, Cortex (anatomy), medicine, Effects of sleep deprivation on cognitive performance, vascular cognitive impairment, lcsh:Neurology. Diseases of the nervous system, Original Research, cerebral small vessel disease, business.industry, diffusion tensor imaging, microinfarcts, medicine.anatomical_structure, Neurology (clinical), business, Neuroscience, computer, 030217 neurology & neurosurgery, Diffusion MRI, Tractography
Abstract

Background and purpose: Cerebral microinfarcts (CMIs) are associated with cognitive impairment and dementia. CMIs might affect cognitive performance through disruption of cerebral networks. We investigated in memory clinic patients whether cortical CMIs are clustered in specific brain regions and if presence of cortical CMIs is associated with reduced white matter (WM) connectivity in tracts projecting to these regions.Methods: 164 memory clinic patients with vascular brain injury with a mean age of 72 +/- 11 years (54% male) were included. All underwent 3 tesla MRI, including a diffusion MRI and cognitive testing. Cortical CMIs were rated according to established criteria and their spatial location was marked. Diffusion imaging-based tractography was used to reconstruct WM connections and voxel based analysis (VBA) to assess integrity of WM directly below the cortex. WM connectivity and integrity were compared between patients with and without cortical CMIs for the whole brain and regions with a high CMI burden.Results: 30 patients (18%) had at least 1 cortical CMI [range 1-46]. More than 70% of the cortical CMIs were located in the superior frontal, middle frontal, and pre- and postcentral brain regions (covering 16% of the cortical surface). In these high CMI burden regions, presence of cortical CMIs was not associated with WM connectivity after correction for conventional neuroimaging markers of vascular injury. WM connectivity in the whole brain and WM voxels directly underneath the cortical surface did not differ between patients with and without cortical CMIs.Conclusion: Cortical CMIs displayed a strong local clustering in highly interconnected frontal, pre- and postcentral brain regions. Nevertheless, WM connections projecting to these regions were not disproportionally impaired in patients with compared to patients without cortical CMIs. Alternative mechanisms, such as focal disturbances in cortical structure and functioning, may better explain CMI associated cognitive impairment.

Published
2019
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9. Progress toward standardized diagnosis of vascular cognitive impairment: Guidelines from the Vascular Impairment of Cognition Classification Consensus Study

Author

Skrobot, Olivia A., Black, Sandra E., Chen, Christopher, DeCarli, Charles, Erkinjuntti, Timo, Ford, Gary A., Kalaria, Rajesh N., O'Brien, John, Pantoni, Leonardo, Pasquier, Florence, Roman, Gustavo C., Wallin, Anders, Sachdev, Perminder, Skoog, Ingmar, VICCCS Group, Taragano, F. E., Kril, J., Cavalieri, M., Jellinger, K. A., Kovacs, G. G., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., De Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J., Lenoir, H., Tsatali, M., Tsolaki, M., Sundar, U., Coen, R. F., Korczyn, A. D., Altieri, M., Baldereschi, M., Caltagirone, C., Caravaglios, G., Di Carlo, A., Di Piero, V., Gainotti, G., Galluzzi, S., Logroscino, G., Mecocci, P., Moretti, D. V., Padovani, A., Fukui, T., Ihara, M., Mizuno, T., Kim, S. Y., Akinyemi, R., Baiyewu, O., Ogunniyi, A., Szczudlik, A., Bastos-Leite, A. J., Firmino, H., Massano, J., Verdelho, A., Kruglov, L. S., Ikram, M. K., Kandiah, N., Arana, E., Barroso-Ribal, J., Calatayud, T., Cruz-Jentoft, A. J., López-Pousa, S., Martinez-Lage, P., Mataro, M., Börjesson-Hanson, A., Englund, E., Laukka, E. J., Qiu, C., Viitanen, M., Biessels, G. J., De Leeuw, F.-E., Den Heijer, T., Exalto, L. G., Kappelle, L. J., Prins, N. D., Richard, E., Schmand, B., Van Den Berg, E., Van Der Flier, W. M., Bilgic, B., Allan, L. M., Archer, J., Attems, J., Bayer, A., Blackburn, D., Brayne, C., Bullock, R., Connelly, P. J., Farrant, A., Fish, M., Harkness, K., Ince, P. G., Langhorne, P., Mann, J., Matthews, F. E., Mayer, P., Pendlebury, S. T., Perneczky, R., Peters, R., Smithard, D., Stephan, B. C., Swartz, J. E., Todd, S., Werring, D. J., Wijayasiri, S. N., Wilcock, G., Zamboni, G., Au, R., Borson, S., Bozoki, A., Browndyke, J. N., Corrada, M. M., Crane, P. K., Diniz, B. S., Etcher, L., Fillit, H., Greenberg, S. M., Grinberg, L. T., Hurt, S. W., Lamar, M., Mielke, M., Ott, B. R., Perry, G., Powers, W. J., Ramos-Estebanez, C., Reed, B., Roberts, R. O., Romero, J. R., Saykin, A. J., Seshadri, S., Silbert, L., Stern, Yaakov, Zarow, C., Ben-Shlomo, Yoav, Passmore, Anthony P., Love, Seth, and Kehoe, Patrick G.

Subjects
Cognition disorders, Cognition disorders--Diagnosis, FOS: Clinical medicine, Neurosciences
Abstract

Introduction: Progress in understanding and management of vascular cognitive impairment (VCI) has been hampered by lack of consensus on diagnosis, reflecting the use of multiple different assessment protocols. A large multinational group of clinicians and researchers participated in a two-phase Vascular Impairment of Cognition Classification Consensus Study (VICCCS) to agree on principles (VICCCS-1) and protocols (VICCCS-2) for diagnosis of VCI. We present VICCCS-2. Methods: We used VICCCS-1 principles and published diagnostic guidelines as points of reference for an online Delphi survey aimed at achieving consensus on clinical diagnosis of VCI. Results: Six survey rounds comprising 65–79 participants agreed guidelines for diagnosis of VICCCS-revised mild and major forms of VCI and endorsed the National Institute of Neurological Disorders–Canadian Stroke Network neuropsychological assessment protocols and recommendations for imaging. Discussion: The VICCCS-2 suggests standardized use of the National Institute of Neurological Disorders–Canadian Stroke Network recommendations on neuropsychological and imaging assessment for diagnosis of VCI so as to promote research collaboration.

Published
2018
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10. Progress toward standardized diagnosis of vascular cognitive impairment: Guidelines from the Vascular Impairment of Cognition Classification Consensus Study

Author

Skrobot, O. A., Black, S. E., Chen, C., Decarli, C., Erkinjuntti, T., Ford, G. A., Kalaria, R. N., O'Brien, J., Pantoni, L., Pasquier, F., Roman, G. C., Wallin, A., Sachdev, P., Skoog, I., Taragano, F. E., Kril, J., Cavalieri, M., Jellinger, K. A., Kovacs, G. G., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J., Lenoir, H., Tsatali, M., Tsolaki, M., Sundar, U., Coen, R. F., Korczyn, A. D., Altieri, M., Baldereschi, M., Caltagirone, C., Caravaglios, G., Di Carlo, A., Di Piero, V., Gainotti, Guido, Galluzzi, S., Logroscino, G., Mecocci, P., Moretti, D. V., Padovani, A., Fukui, T., Ihara, M., Mizuno, T., Kim, S. Y., Akinyemi, R., Baiyewu, O., Ogunniyi, A., Szczudlik, A., Bastos-Leite, A. J., Firmino, H., Massano, J., Verdelho, A., Kruglov, L. S., Ikram, M. K., Kandiah, N., Arana, E., Barroso-Ribal, J., Calatayud, T., Cruz-Jentoft, A. J., Lopez-Pousa, S., Martinez-Lage, P., Mataro, M., Borjesson-Hanson, A., Englund, E., Laukka, E. J., Qiu, C., Viitanen, M., Biessels, G. J., de Leeuw, F. -E., den Heijer, T., Exalto, L. G., Kappelle, L. J., Prins, N. D., Richard, E., Schmand, B., van den Berg, E., van der Flier, W. M., Bilgic, B., Allan, L. M., Archer, J., Attems, J., Bayer, A., Blackburn, D., Brayne, C., Bullock, R., Connelly, P. J., Farrant, A., Fish, M., Harkness, K., Ince, P. G., Langhorne, P., Mann, J., Matthews, F. E., Mayer, P., Pendlebury, S. T., Perneczky, R., Peters, R., Smithard, D., Stephan, B. C., Swartz, J. E., Todd, S., Werring, D. J., Wijayasiri, S. N., Wilcock, G., Zamboni, G., Au, R., Borson, S., Bozoki, A., Browndyke, J. N., Corrada, M. M., Crane, P. K., Diniz, B. S., Etcher, L., Fillit, H., Greenberg, S. M., Grinberg, L. T., Hurt, S. W., Lamar, M., Mielke, M., Ott, B. R., Perry, G., Powers, W. J., Ramos-Estebanez, C., Reed, B., Roberts, R. O., Romero, J. R., Saykin, A. J., Seshadri, S., Silbert, L., Stern, Y., Zarow, C., Ben-Shlomo, Y., Passmore, A. P., Love, S., Kehoe, P. G., Gainotti G., Skrobot, O. A., Black, S. E., Chen, C., Decarli, C., Erkinjuntti, T., Ford, G. A., Kalaria, R. N., O'Brien, J., Pantoni, L., Pasquier, F., Roman, G. C., Wallin, A., Sachdev, P., Skoog, I., Taragano, F. E., Kril, J., Cavalieri, M., Jellinger, K. A., Kovacs, G. G., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J., Lenoir, H., Tsatali, M., Tsolaki, M., Sundar, U., Coen, R. F., Korczyn, A. D., Altieri, M., Baldereschi, M., Caltagirone, C., Caravaglios, G., Di Carlo, A., Di Piero, V., Gainotti, Guido, Galluzzi, S., Logroscino, G., Mecocci, P., Moretti, D. V., Padovani, A., Fukui, T., Ihara, M., Mizuno, T., Kim, S. Y., Akinyemi, R., Baiyewu, O., Ogunniyi, A., Szczudlik, A., Bastos-Leite, A. J., Firmino, H., Massano, J., Verdelho, A., Kruglov, L. S., Ikram, M. K., Kandiah, N., Arana, E., Barroso-Ribal, J., Calatayud, T., Cruz-Jentoft, A. J., Lopez-Pousa, S., Martinez-Lage, P., Mataro, M., Borjesson-Hanson, A., Englund, E., Laukka, E. J., Qiu, C., Viitanen, M., Biessels, G. J., de Leeuw, F. -E., den Heijer, T., Exalto, L. G., Kappelle, L. J., Prins, N. D., Richard, E., Schmand, B., van den Berg, E., van der Flier, W. M., Bilgic, B., Allan, L. M., Archer, J., Attems, J., Bayer, A., Blackburn, D., Brayne, C., Bullock, R., Connelly, P. J., Farrant, A., Fish, M., Harkness, K., Ince, P. G., Langhorne, P., Mann, J., Matthews, F. E., Mayer, P., Pendlebury, S. T., Perneczky, R., Peters, R., Smithard, D., Stephan, B. C., Swartz, J. E., Todd, S., Werring, D. J., Wijayasiri, S. N., Wilcock, G., Zamboni, G., Au, R., Borson, S., Bozoki, A., Browndyke, J. N., Corrada, M. M., Crane, P. K., Diniz, B. S., Etcher, L., Fillit, H., Greenberg, S. M., Grinberg, L. T., Hurt, S. W., Lamar, M., Mielke, M., Ott, B. R., Perry, G., Powers, W. J., Ramos-Estebanez, C., Reed, B., Roberts, R. O., Romero, J. R., Saykin, A. J., Seshadri, S., Silbert, L., Stern, Y., Zarow, C., Ben-Shlomo, Y., Passmore, A. P., Love, S., Kehoe, P. G., and Gainotti G.

Abstract

Introduction: Progress in understanding and management of vascular cognitive impairment (VCI) has been hampered by lack of consensus on diagnosis, reflecting the use of multiple different assessment protocols. A large multinational group of clinicians and researchers participated in a two-phase Vascular Impairment of Cognition Classification Consensus Study (VICCCS) to agree on principles (VICCCS-1) and protocols (VICCCS-2) for diagnosis of VCI. We present VICCCS-2. Methods: We used VICCCS-1 principles and published diagnostic guidelines as points of reference for an online Delphi survey aimed at achieving consensus on clinical diagnosis of VCI. Results: Six survey rounds comprising 65–79 participants agreed guidelines for diagnosis of VICCCS-revised mild and major forms of VCI and endorsed the National Institute of Neurological Disorders–Canadian Stroke Network neuropsychological assessment protocols and recommendations for imaging. Discussion: The VICCCS-2 suggests standardized use of the National Institute of Neurological Disorders–Canadian Stroke Network recommendations on neuropsychological and imaging assessment for diagnosis of VCI so as to promote research collaboration.

Published
2018

11. The Vascular Impairment of Cognition Classification Consensus Study

Author

Skrobot, Olivia A., Love, Seth, Kehoe, Patrick G., O'Brien, John, Black, Sandra E., Chen, Christopher, DeCarli, Charles, Erkinjuntti, Timo, Ford, Gary A., Kalaria, Rajesh N., Pantoni, Leonardo, Pasquier, Florence, Roman, Gustavo C., Wallin, Anders, Sachdev, Perminder S., Skoog, Ingmar, Ben-Shlomo, Yoav, Passmore, Anthony P., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J-J., Lenoir, H., Tsatali, M., Tsolaki, Magda, Sundar, U., Ikram, M. K., Biessels, G. J., Exalto, L. G., Kappelle, L. J., van den Berg, E., Swartz, J. E., and VICCCS group

Subjects
Consensus, Epidemiology, Health Policy, Clinical Neurology, Guidelines, Criteria, Delphi, Vascular dementia, Cellular and Molecular Neuroscience, Psychiatry and Mental health, Developmental Neuroscience, Journal Article, Vascular cognitive impairment, Geriatrics and Gerontology
Abstract

Introduction Numerous diagnostic criteria have tried to tackle the variability in clinical manifestations and problematic diagnosis of vascular cognitive impairment (VCI) but none have been universally accepted. These criteria have not been readily comparable, impacting on clinical diagnosis rates and in turn prevalence estimates, research, and treatment. Methods The Vascular Impairment of Cognition Classification Consensus Study (VICCCS) involved participants (81% academic researchers) from 27 countries in an online Delphi consensus study. Participants reviewed previously proposed concepts to develop new guidelines. Results VICCCS had a mean of 122 (98–153) respondents across the study and a 67% threshold to represent consensus. VICCCS redefined VCI including classification of mild and major forms of VCI and subtypes. It proposes new standardized VCI-associated terminology and future research priorities to address gaps in current knowledge. Discussion VICCCS proposes a consensus-based updated conceptualization of VCI intended to facilitate standardization in research.

Published
2017

12. The Vascular Impairment of Cognition Classification Consensus Study

Author

ZL Cerebrovasculaire Ziekten Medisch, ZL Algemene Neurologie Medisch, Circulatory Health, Brain, Opleiding Neurologie, Projectafdeling VCI, MS KNO, Skrobot, Olivia A., Love, Seth, Kehoe, Patrick G., O'Brien, John, Black, Sandra E., Chen, Christopher, DeCarli, Charles, Erkinjuntti, Timo, Ford, Gary A., Kalaria, Rajesh N., Pantoni, Leonardo, Pasquier, Florence, Roman, Gustavo C., Wallin, Anders, Sachdev, Perminder S., Skoog, Ingmar, Ben-Shlomo, Yoav, Passmore, Anthony P., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J-J., Lenoir, H., Tsatali, M., Tsolaki, Magda, Sundar, U., Ikram, M. K., Biessels, G. J., Exalto, L. G., Kappelle, L. J., van den Berg, E., Swartz, J. E., VICCCS group, ZL Cerebrovasculaire Ziekten Medisch, ZL Algemene Neurologie Medisch, Circulatory Health, Brain, Opleiding Neurologie, Projectafdeling VCI, MS KNO, Skrobot, Olivia A., Love, Seth, Kehoe, Patrick G., O'Brien, John, Black, Sandra E., Chen, Christopher, DeCarli, Charles, Erkinjuntti, Timo, Ford, Gary A., Kalaria, Rajesh N., Pantoni, Leonardo, Pasquier, Florence, Roman, Gustavo C., Wallin, Anders, Sachdev, Perminder S., Skoog, Ingmar, Ben-Shlomo, Yoav, Passmore, Anthony P., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J-J., Lenoir, H., Tsatali, M., Tsolaki, Magda, Sundar, U., Ikram, M. K., Biessels, G. J., Exalto, L. G., Kappelle, L. J., van den Berg, E., Swartz, J. E., and VICCCS group

Published
2017

13. The Vascular Impairment of Cognition Classification Consensus Study

Author

Skrobot, O. A., Love, S., Kehoe, P. G., O'Brien, J., Black, S., Chen, C., DeCarli, C., Erkinjuntti, T., Ford, G. A., Kalaria, R. N., Pantoni, L., Pasquier, F., Roman, G. C., Wallin, A., Sachdev, P., Kril, J., Skoog, I., Ben-Shlomo, Y., Passmore, A. P., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J., Lenoir, H., Tsatali, M., Tsolaki, M., Sundar, U., Coen, R. F., Korczyn, A. D., Altieri, M., Baldereschi, M., Caltagirone, C., Caravaglios, G., Di Carlo, A., DI Piero, V., Gainotti, G., Galluzzi, S., Logroscino, G., Mecocci, P., Moretti, D. V., Padovani, A., Fukui, T., Ihara, M., Mizuno, T., Kim, S. Y., Akinyemi, R., Baiyewu, O., Ogunniyi, A., Szczudlik, A., Bastos-Leite, A. J., Firmino, H., Massano, J., Verdelho, A., Kruglov, L. S., Ikram, M. K., Kandiah, N., Arana, E., Barroso-Ribal, J., Calatayud, T., Cruz-Jentoft, A. J., Lopez-Pousa, S., Martinez-Lage, P., Mataro, M., Borjesson-Hanson, A., Englund, E., Laukka, E. J., Qiu, C., Viitanen, M., Biessels, G. J., de Leeuw, F. -E., den Heijer, T., Exalto, L. G., Kappelle, L. J., Prins, N. D., Richard, E., Schmand, B., van den Berg, E., van der Flier, W. M., Bilgic, B., Allan, L. M., Archer, J., Attems, J., Bayer, A., Blackburn, D., Brayne, C., Bullock, R., Connelly, P. J., Farrant, A., Fish, M., Harkness, K., Ince, P. G., Langhorne, P., Mann, J., Matthews, F. E., Mayer, P., Pendlebury, S. T., Perneczky, R., Peters, R., Smithard, D., Stephan, B. C., Swartz, J. E., Todd, S., Werring, D. J., Wijayasiri, S. N., Wilcock, G., Zamboni, G., Au, R., Borson, S., Bozoki, A., Browndyke, J. N., Corrada, M. M., Crane, P. K., Diniz, B. S., Etcher, L., Fillit, H., Greenberg, S. M., Grinberg, L. T., Hurt, S. W., Lamar, M., Mielke, M., Ott, B. R., Perry, G., Powers, W. J., Ramos-Estebanez, C., Reed, B., Roberts, R. O., Romero, J. R., Saykin, A. J., Seshadri, S., Silbert, L., Stern, Y., Zarow, C., Gainotti G., Logroscino G. (ORCID:0000-0003-1301-5343), Skrobot, O. A., Love, S., Kehoe, P. G., O'Brien, J., Black, S., Chen, C., DeCarli, C., Erkinjuntti, T., Ford, G. A., Kalaria, R. N., Pantoni, L., Pasquier, F., Roman, G. C., Wallin, A., Sachdev, P., Kril, J., Skoog, I., Ben-Shlomo, Y., Passmore, A. P., Engelborghs, S., Lafosse, C., Bertolucci, P. H., Brucki, S., Caramelli, P., de Toledo Ferraz Alves, T. C., Bocti, C., Fulop, T., Hogan, D. B., Hsiung, G. R., Kirk, A., Leach, L., Robillard, A., Sahlas, D. J., Guo, Q., Tian, J., Hokkanen, L., Jokinen, H., Benisty, S., Deramecourt, V., Hauw, J., Lenoir, H., Tsatali, M., Tsolaki, M., Sundar, U., Coen, R. F., Korczyn, A. D., Altieri, M., Baldereschi, M., Caltagirone, C., Caravaglios, G., Di Carlo, A., DI Piero, V., Gainotti, G., Galluzzi, S., Logroscino, G., Mecocci, P., Moretti, D. V., Padovani, A., Fukui, T., Ihara, M., Mizuno, T., Kim, S. Y., Akinyemi, R., Baiyewu, O., Ogunniyi, A., Szczudlik, A., Bastos-Leite, A. J., Firmino, H., Massano, J., Verdelho, A., Kruglov, L. S., Ikram, M. K., Kandiah, N., Arana, E., Barroso-Ribal, J., Calatayud, T., Cruz-Jentoft, A. J., Lopez-Pousa, S., Martinez-Lage, P., Mataro, M., Borjesson-Hanson, A., Englund, E., Laukka, E. J., Qiu, C., Viitanen, M., Biessels, G. J., de Leeuw, F. -E., den Heijer, T., Exalto, L. G., Kappelle, L. J., Prins, N. D., Richard, E., Schmand, B., van den Berg, E., van der Flier, W. M., Bilgic, B., Allan, L. M., Archer, J., Attems, J., Bayer, A., Blackburn, D., Brayne, C., Bullock, R., Connelly, P. J., Farrant, A., Fish, M., Harkness, K., Ince, P. G., Langhorne, P., Mann, J., Matthews, F. E., Mayer, P., Pendlebury, S. T., Perneczky, R., Peters, R., Smithard, D., Stephan, B. C., Swartz, J. E., Todd, S., Werring, D. J., Wijayasiri, S. N., Wilcock, G., Zamboni, G., Au, R., Borson, S., Bozoki, A., Browndyke, J. N., Corrada, M. M., Crane, P. K., Diniz, B. S., Etcher, L., Fillit, H., Greenberg, S. M., Grinberg, L. T., Hurt, S. W., Lamar, M., Mielke, M., Ott, B. R., Perry, G., Powers, W. J., Ramos-Estebanez, C., Reed, B., Roberts, R. O., Romero, J. R., Saykin, A. J., Seshadri, S., Silbert, L., Stern, Y., Zarow, C., Gainotti G., and Logroscino G. (ORCID:0000-0003-1301-5343)

Abstract

Introduction Numerous diagnostic criteria have tried to tackle the variability in clinical manifestations and problematic diagnosis of vascular cognitive impairment (VCI) but none have been universally accepted. These criteria have not been readily comparable, impacting on clinical diagnosis rates and in turn prevalence estimates, research, and treatment. Methods The Vascular Impairment of Cognition Classification Consensus Study (VICCCS) involved participants (81% academic researchers) from 27 countries in an online Delphi consensus study. Participants reviewed previously proposed concepts to develop new guidelines. Results VICCCS had a mean of 122 (98–153) respondents across the study and a 67% threshold to represent consensus. VICCCS redefined VCI including classification of mild and major forms of VCI and subtypes. It proposes new standardized VCI-associated terminology and future research priorities to address gaps in current knowledge. Discussion VICCCS proposes a consensus-based updated conceptualization of VCI intended to facilitate standardization in research.

Published
2017

14. Neuropsychiatric symptoms in patients with possible vascular cognitive impairment, does sex matter?

Author

Exalto LG, Boomsma JM, Sep Y, Leeuwis AE, Scheltens P, Biessels GJ, and van der Flier WM

Abstract

Background: Neuropsychiatric symptoms (NPS) are common in patients with vascular cognitive impairment (VCI). We aimed to establish sex differences in the manifestation of NPS in memory clinic patients with possible VCI and identify which NPS are determinants of clinical progression in women and men separately., Methods: We included 718 memory clinic patients (age 68 ± 8; 45% women) with cognitive complaints and vascular brain lesions on MRI (i.e. possible VCI). NPS were measured using the 12-item Neuropsychiatric Inventory. Clinical progression after two years (women 18%, men 14%) was defined as increase in CDR ≥1 or institutionalization (available n  = 589 without advanced dementia at baseline). The association between NPS and clinical progression was assessed with Cox proportional hazard models stratified by sex, adjusted for age and clinical diagnosis and in a second model additionally for manifestations of vascular brain lesions., Results: Men more often presented with agitation (29% versus 17%, p <.05) and irritability (58% versus 45%, p <.05), the other 10 NPS (delusions, hallucinations, depression, anxiety, euphoria, apathy, disinhibition, aberrant motor behavior, nighttime disturbances and appetite & eating abnormalities) did not differ between sexes. In women the presence of apathy (HR 2.1[1.1;4.3]) was associated with higher risk of clinical progression. In men the presence of depression (HR 2.7[1.4;5.1]) and aberrant motor behavior (HR 2.1[1.1;3.8]) were associated with increased risk of clinical progression., Conclusion: Manifestations of NPS in patients with possible VCI differ by sex. Different NPS are associated with future clinical progression in men and women. Management strategies of NPS could benefit from sex-specific approaches., (© 2022 The Authors. Published by Elsevier B.V.)

Published
2022
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