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Article ; Online: Imaging Markers of Vascular Brain Health: Quantification, Clinical Implications, and Future Directions.

Vemuri, Prashanthi / Decarli, Charles / Duering, Marco

2022 Volume 53, Issue 2, Page(s) 416–426

Abstract: Cerebrovascular disease (CVD) manifests through a broad spectrum of mechanisms that negatively impact brain and cognitive health. Oftentimes, CVD changes (excluding acute stroke) are insufficiently considered in aging and dementia studies which can lead ... ...

Abstract	Cerebrovascular disease (CVD) manifests through a broad spectrum of mechanisms that negatively impact brain and cognitive health. Oftentimes, CVD changes (excluding acute stroke) are insufficiently considered in aging and dementia studies which can lead to an incomplete picture of the etiologies contributing to the burden of cognitive impairment. Our goal with this focused review is 3-fold. First, we provide a research update on the current magnetic resonance imaging methods that can measure CVD lesions as well as early CVD-related brain injury specifically related to small vessel disease. Second, we discuss the clinical implications and relevance of these CVD imaging markers for cognitive decline, incident dementia, and disease progression in Alzheimer disease, and Alzheimer-related dementias. Finally, we present our perspective on the outlook and challenges that remain in the field. With the increased research interest in this area, we believe that reliable CVD imaging biomarkers for aging and dementia studies are on the horizon.
MeSH term(s)	Alzheimer Disease/diagnostic imaging ; Alzheimer Disease/psychology ; Biomarkers ; Brain/diagnostic imaging ; Cerebrovascular Disorders/diagnostic imaging ; Cerebrovascular Disorders/psychology ; Cognitive Dysfunction ; Health Status ; Humans ; Magnetic Resonance Imaging/methods ; Magnetic Resonance Imaging/trends ; Neuroimaging/methods ; Neuroimaging/trends
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-01-10
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	80381-9
ISSN	1524-4628 ; 0039-2499 ; 0749-7954
ISSN (online)	1524-4628
ISSN	0039-2499 ; 0749-7954
DOI	10.1161/STROKEAHA.120.032611
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Article ; Online: Preanalytic variable effects on segmentation and quantification machine learning algorithms for amyloid-β analyses on digitized human brain slides.

Oliveira, Luca Cerny / Lai, Zhengfeng / Harvey, Danielle / Nzenkue, Kevin / Jin, Lee-Way / Decarli, Charles / Chuah, Chen-Nee / Dugger, Brittany N

Journal of neuropathology and experimental neurology

2023 Volume 82, Issue 3, Page(s) 212–220

Abstract: Computational machine learning (ML)-based frameworks could be advantageous for scalable analyses in neuropathology. A recent deep learning (DL) framework has shown promise in automating the processes of visualizing and quantifying different types of ... ...

Abstract	Computational machine learning (ML)-based frameworks could be advantageous for scalable analyses in neuropathology. A recent deep learning (DL) framework has shown promise in automating the processes of visualizing and quantifying different types of amyloid-β deposits as well as segmenting white matter (WM) from gray matter (GM) on digitized immunohistochemically stained slides. However, this framework has only been trained and evaluated on amyloid-β-stained slides with minimal changes in preanalytic variables. In this study, we evaluated select preanalytical variables including magnification, compression rate, and storage format using three digital slides scanners (Zeiss Axioscan Z1, Leica Aperio AT2, and Leica Aperio GT 450), on over 60 whole slide images, in a cohort of 14 cases having a spectrum of amyloid-β deposits. We conducted statistical comparisons of preanalytic variables with repeated measures analysis of variance evaluating the outputs of two DL frameworks for segmentation and object classification tasks. For both WM/GM segmentation and amyloid-β plaque classification tasks, there were statistical differences with respect to scanner types (p < 0.05) and magnifications (p < 0.05). Although small numbers of cases were analyzed, this pilot study highlights the significance of preanalytic variables that may alter the performance of ML algorithms.
MeSH term(s)	Humans ; Algorithms ; Brain ; Image Processing, Computer-Assisted/methods ; Machine Learning ; Pilot Projects
Chemical Substances	APP protein, human
Language	English
Publishing date	2023-01-24
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	3088-0
ISSN	1554-6578 ; 0022-3069
ISSN (online)	1554-6578
ISSN	0022-3069
DOI	10.1093/jnen/nlac132
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Article: Vascular factors in dementia: an overview.

Decarli, Charles

Journal of the neurological sciences

2004 Volume 226, Issue 1-2, Page(s) 19–23

Abstract: Alzheimer's disease and cerebrovascular disease are two illnesses common to the elderly. Conventional wisdom has sought to separately describe and treat these two diseases. Accumulating evidence, however, shows that cerebrovascular risk factors may cause ...

Abstract	Alzheimer's disease and cerebrovascular disease are two illnesses common to the elderly. Conventional wisdom has sought to separately describe and treat these two diseases. Accumulating evidence, however, shows that cerebrovascular risk factors may cause asymptomatic brain injury, share genetic risk with Alzheimer's disease and possibly accelerate the Alzheimer's process. Such evidence suggests that these two diseases may act additively or synergistically to cause clinical dementia. This review focuses on evolving data that support this hypothesis.
MeSH term(s)	Aged ; Alzheimer Disease/pathology ; Brain/pathology ; Cerebrovascular Circulation/physiology ; Cerebrovascular Disorders/pathology ; Dementia, Vascular/pathology ; Disease Progression ; Humans
Language	English
Publishing date	2004-11-15
Publishing country	Netherlands
Document type	Journal Article ; Review
ZDB-ID	80160-4
ISSN	1878-5883 ; 0022-510X ; 0374-8642
ISSN (online)	1878-5883
ISSN	0022-510X ; 0374-8642
DOI	10.1016/j.jns.2004.09.005
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Article ; Online: Amylin: what might be its role in Alzheimer's disease and how could this affect therapy?

Despa, Florin / Decarli, Charles

Expert review of proteomics

2013 Volume 10, Issue 5, Page(s) 403–405

MeSH term(s)	Alzheimer Disease/metabolism ; Alzheimer Disease/pathology ; Alzheimer Disease/therapy ; Brain/metabolism ; Brain/pathology ; Humans ; Islet Amyloid Polypeptide/metabolism
Chemical Substances	Islet Amyloid Polypeptide
Language	English
Publishing date	2013-10-14
Publishing country	England
Document type	Editorial ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2299100-1
ISSN	1744-8387 ; 1478-9450
ISSN (online)	1744-8387
ISSN	1478-9450
DOI	10.1586/14789450.2013.841549
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Article ; Online: Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology.

Baril, Andrée-Ann / Kojis, Daniel J / Himali, Jayandra J / Decarli, Charles S / Sanchez, Erlan / Johnson, Keith A / El Fakhri, Georges / Thibault, Emma / Yiallourou, Stephanie R / Himali, Dibya / Cavuoto, Marina G / Pase, Matthew P / Beiser, Alexa S / Seshadri, Sudha

Neurology

2023 Volume 102, Issue 1, Page(s) e207807

Abstract: Background and objectives: Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, ( ... ...

Abstract	Background and objectives: Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease. Methods: Two Framingham Heart Study overlapping samples were studied: participants who underwent Results: The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average β [SE] 0.0062 [0.0024], Discussion: Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.
MeSH term(s)	Male ; Humans ; Middle Aged ; Aged ; Female ; Sleep Duration ; Cross-Sectional Studies ; Amyloidogenic Proteins ; Neuroimaging ; Biomarkers
Chemical Substances	Amyloidogenic Proteins ; Biomarkers
Language	English
Publishing date	2023-12-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000207807
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Article: BrainSec: Automated Brain Tissue Segmentation Pipeline for Scalable Neuropathological Analysis.

Lai, Zhengfeng / Oliveira, Luca Cerny / Guo, Runlin / Xu, Wenda / Hu, Zin / Mifflin, Kelsey / Decarli, Charles / Cheung, Sen-Ching / Chuah, Chen-Nee / Dugger, Brittany N

IEEE access : practical innovations, open solutions

2022 Volume 10, Page(s) 49064–49079

Abstract: As neurodegenerative disease pathological hallmarks have been reported in both grey matter (GM) and white matter (WM) with different density distributions, automating the segmentation process of GM/WM would be extremely advantageous for aiding in ... ...

Abstract	As neurodegenerative disease pathological hallmarks have been reported in both grey matter (GM) and white matter (WM) with different density distributions, automating the segmentation process of GM/WM would be extremely advantageous for aiding in neuropathologic deep phenotyping. Standard segmentation methods typically involve manual annotations, where a trained researcher traces the delineation of GM/WM in ultra-high-resolution Whole Slide Images (WSIs). This method can be time-consuming and subjective, preventing a scalable analysis on pathology images. This paper proposes an automated segmentation pipeline (BrainSec) combining a Convolutional Neural Network (CNN) module for segmenting GM/WM regions and a post-processing module to remove artifacts/residues of tissues. The final output generates XML annotations that can be visualized via Aperio ImageScope. First, we investigate two baseline models for medical image segmentation: FCN, and U-Net. Then we propose a patch-based approach, BrainSec, to classify the GM/WM/background regions. We demonstrate BrainSec is robust and has reliable performance by testing it on over 180 WSIs that incorporate numerous unique cases as well as distinct neuroanatomic brain regions. We also apply gradient-weighted class activation mapping (Grad-CAM) to interpret the segmentation masks and provide relevant explanations and insights. In addition, we have integrated BrainSec with an existing Amyloid-
Language	English
Publishing date	2022-05-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2687964-5
ISSN	2169-3536
ISSN	2169-3536
DOI	10.1109/access.2022.3171927
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Article ; Online: Association of Plasma YKL-40 With MRI, CSF, and Cognitive Markers of Brain Health and Dementia.

Pase, Matthew P / Himali, Jayandra J / Puerta, Raquel / Beiser, Alexa S / Gonzales, Mitzi M / Satizabal, Claudia L / Yang, Qiong / Aparicio, Hugo J / Kojis, Daniel J / Decarli, Charles S / Lopez, Oscar L / Longstreth, Will / Gudnason, Vilmundur / Mosley, Thomas H / Bis, Joshua C / Fohner, Alison / Psaty, Bruce M / Boada, Mercè / García-González, Pablo /

Valero, Sergi / Marquié, Marta / Tracy, Russell / Launer, Lenore J / Ruiz, Agustín / Fornage, Myriam / Seshadri, Sudha

Neurology

2024 Volume 102, Issue 4, Page(s) e208075

Abstract: Background and objectives: Higher YKL-40 levels in the CSF are a known biomarker of brain inflammation. We explored the utility of plasma YKL-40 as a biomarker for accelerated brain aging and dementia risk.: Methods: We performed cross-sectional and ... ...

Abstract	Background and objectives: Higher YKL-40 levels in the CSF are a known biomarker of brain inflammation. We explored the utility of plasma YKL-40 as a biomarker for accelerated brain aging and dementia risk. Methods: We performed cross-sectional and prospective analyses of 4 community-based cohorts in the United States or Europe: the Age, Gene/Environment Susceptibility-Reykjavik Study, Atherosclerosis Risk in the Communities study, Coronary Artery Risk Development in Young Adults study, and Framingham Heart Study (FHS). YKL-40 was measured from stored plasma by a single laboratory using Mesoscale Discovery with levels log transformed and standardized within each cohort. Outcomes included MRI total brain volume, hippocampal volume, and white matter hyperintensity volume (WMHV) as a percentage of intracranial volume, a general cognitive composite derived from neuropsychological testing (SD units [SDU]), and the risk of incident dementia. We sought to replicate associations with dementia in the clinic-based ACE csf cohort, which also had YKL-40 measured from the CSF. Results: Meta-analyses of MRI outcomes included 6,558 dementia-free participants, and for analysis of cognition, 6,670. The blood draw preceded MRI/cognitive assessment by up to 10.6 years across cohorts. The mean ages ranged from 50 to 76 years, with 39%-48% male individuals. In random-effects meta-analysis of study estimates, each SDU increase in log-transformed YKL-40 levels was associated with smaller total brain volume (β = -0.33; 95% CI -0.45 to -0.22; Discussion: Higher plasma YKL-40 levels were associated with lower brain volume, poorer cognition, and incident dementia. Plasma YKL-40 may be useful for studying the association of inflammation and its treatment on dementia risk.
MeSH term(s)	Aged ; Female ; Humans ; Male ; Middle Aged ; Alzheimer Disease ; Biomarkers ; Brain/diagnostic imaging ; Chitinase-3-Like Protein 1 ; Cognition ; Cognitive Dysfunction ; Cross-Sectional Studies ; Dementia/diagnostic imaging ; Magnetic Resonance Imaging ; Prospective Studies
Chemical Substances	Biomarkers ; Chitinase-3-Like Protein 1 ; CHI3L1 protein, human
Language	English
Publishing date	2024-01-30
Publishing country	United States
Document type	Meta-Analysis ; Journal Article
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000208075
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Article ; Online: Validation of T1w-based segmentations of white matter hyperintensity volumes in large-scale datasets of aging.

Dadar, Mahsa / Maranzano, Josefina / Ducharme, Simon / Carmichael, Owen T / Decarli, Charles / Collins, D Louis

Human brain mapping

2017 Volume 39, Issue 3, Page(s) 1093–1107

Abstract: Introduction: Fluid-attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter hyperintensities (WMHs) in aging and Alzheimer's ... ...

Abstract	Introduction: Fluid-attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter hyperintensities (WMHs) in aging and Alzheimer's disease populations. However, many existing large multisite studies forgo their acquisition in favor of other MRI sequences due to economic and time constraints. Methods: In this article, we have investigated whether FLAIR and T2w/PD sequences are necessary to detect WMHs in Alzheimer's and aging studies, compared to using only T1w images. Using a previously validated automated tool based on a Random Forests classifier, WMHs were segmented for the baseline visits of subjects from ADC, ADNI1, and ADNI2/GO studies with and without T2w/PD and FLAIR information. The obtained WMH loads (WMHLs) in different lobes were then correlated with manually segmented WMHLs, each other, age, cognitive, and clinical measures to assess the strength of the correlations with and without using T2w/PD and FLAIR information. Results: The WMHLs obtained from T1w-Only segmentations correlated with the manual WMHLs (ADNI1: r = .743, p < .001, ADNI2/GO: r = .904, p < .001), segmentations obtained from T1w + T2w + PD for ADNI1 (r = .888, p < .001) and T1w + FLAIR for ADNI2/GO (r = .969, p < .001), age (ADNI1: r = .391, p < .001, ADNI2/GO: r = .466, p < .001), and ADAS13 (ADNI1: r = .227, p < .001, ADNI2/GO: r = .190, p < 0.001), and NPI (ADNI1: r = .290, p < .001, ADNI2/GO: r = 0.144, p < .001), controlling for age. Conclusion: Our results suggest that while T2w/PD and FLAIR provide more accurate estimates of the true WMHLs, T1w-Only segmentations can still provide estimates that hold strong correlations with the actual WMHLs, age, and performance on various cognitive/clinical scales, giving added value to datasets where T2w/PD or FLAIR are not available.
MeSH term(s)	Aged ; Aging/pathology ; Alzheimer Disease/diagnostic imaging ; Alzheimer Disease/pathology ; Brain/diagnostic imaging ; Brain/pathology ; Datasets as Topic ; Female ; Humans ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods ; Male ; Organ Size ; Pattern Recognition, Automated ; White Matter/diagnostic imaging ; White Matter/pathology
Language	English
Publishing date	2017-11-27
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Validation Study
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.23894
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Article: Vascular dementia: emerging trends.

Aggarwal, Neelum T / Decarli, Charles

Seminars in neurology

2007 Volume 27, Issue 1, Page(s) 66–77

Abstract: Vascular dementia is a term used to describe a constellation of cognitive and functional impairment that can be viewed as a subset of the larger syndrome of vascular cognitive impairment associated with cerebrovascular brain injury. Vascular dementia is ... ...

Abstract	Vascular dementia is a term used to describe a constellation of cognitive and functional impairment that can be viewed as a subset of the larger syndrome of vascular cognitive impairment associated with cerebrovascular brain injury. Vascular dementia is a common disorder among the elderly, although it can also occur in younger persons. Comprising 20% of all cases of dementia in the United States, vascular dementia is the second most common form of dementia after Alzheimer's disease. Patients with vascular dementia often exhibit mood and behavioral changes and may have focal neurological signs on neurological examination. Primary treatment is through primary or secondary modification of cerebrovascular risk factors such as hypertension, although symptomatic treatments with cholinesterase inhibitors have shown modest symptomatic benefit.
MeSH term(s)	Brain/blood supply ; Brain/pathology ; Brain/physiopathology ; Causality ; Cerebral Arteries/physiopathology ; Cholinesterase Inhibitors/therapeutic use ; Dementia, Vascular/diagnosis ; Dementia, Vascular/physiopathology ; Dementia, Vascular/therapy ; Diagnosis, Differential ; Humans ; Hypertension/complications ; Hypertension/prevention & control ; Hypertension/therapy
Chemical Substances	Cholinesterase Inhibitors
Language	English
Publishing date	2007-02
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	603165-1
ISSN	1098-9021 ; 0271-8235
ISSN (online)	1098-9021
ISSN	0271-8235
DOI	10.1055/s-2006-956757
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Article: Effects of T2-Weighted MRI Based Cranial Volume Measurements on Studies of the Aging Brain.

Vuong, Phong / Drucker, David / Schwarz, Chris / Fletcher, Evan / Decarli, Charles / Carmichael, Owen

Proceedings of SPIE--the International Society for Optical Engineering

2013 Volume 8669

Abstract: Many brain aging studies use total intracranial volume (TIV) as a proxy measure of premorbid brain size that is unaffected by neurodegeneration. T1-weighted Magnetic Resonance Imaging (MRI) sequences are commonly used to measure TIV, but T2-weighted MRI ... ...

Abstract	Many brain aging studies use total intracranial volume (TIV) as a proxy measure of premorbid brain size that is unaffected by neurodegeneration. T1-weighted Magnetic Resonance Imaging (MRI) sequences are commonly used to measure TIV, but T2-weighted MRI sequences provide superior contrast between the cerebrospinal fluid (CSF) bounding the premorbid brain space and surrounding dura mater. In this study, we compared T1-based and T2-based TIV measurements to assess the practical impact of this superior contrast on studies of brain aging. 810 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, including healthy elders and those with mild cognitive impairment (MCI) and Alzheimer's Disease (AD), received T1-weighted and T2-weighted MRI at their baseline evaluation. TIV was automatically estimated from T1-weighted images using FreeSurfer version 4.3 (T1TIV), and an automated active contour method was used to estimate TIV from T2-weighted images (T2TIV). The correlation between T1TIV and T2TIV was high (.93), and disagreement was greater on larger heads. However, correcting a FreeSurfer-based measure of total parenchymal volume by dividing it by T2TIV led to stronger expected associations with a standardized measure of cognitive dysfunction (MMSE) in Poisson regression models among individuals with AD (
Language	English
Publishing date	2013-11-21
Publishing country	United States
Document type	Journal Article
ISSN	0277-786X
ISSN	0277-786X
DOI	10.1117/12.2006727
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