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      Intracranial internal carotid artery calcification is not predictive of future cognitive decline

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          Abstract

          Background

          Intracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICAC (ICAC) for future risk of cognitive decline and compared the results with conventional imaging biomarkers of dementia.

          Methods

          In a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICAC was quantified on baseline CT scans using the Agatson calcium score, and the association between baseline ICA calcium scores and the risk of conversion from a CDR of zero in baseline to a persistent CDR > 0 at any follow-up visit, as well as longitudinal changes in cognitive scores, were evaluated through linear and mixed regression models. We also evaluated the association of conventional imaging biomarkers of dementia with longitudinal changes in cognitive scores and a potential indirect effect of ICAC on cognition through these biomarkers.

          Results

          Baseline ICA calcium score could not distinguish participants who converted to CDR > 0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICAC increased with age and in men. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICAC was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume.

          Conclusions

          In elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICAC is not directly associated with a future risk of cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.

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          Most cited references43

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

            We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that only label a small number of tissue classes, the current method assigns one of 37 labels to each voxel, including left and right caudate, putamen, pallidum, thalamus, lateral ventricles, hippocampus, and amygdala. The classification technique employs a registration procedure that is robust to anatomical variability, including the ventricular enlargement typically associated with neurological diseases and aging. The technique is shown to be comparable in accuracy to manual labeling, and of sufficient sensitivity to robustly detect changes in the volume of noncortical structures that presage the onset of probable Alzheimer's disease.
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              mediation:RPackage for Causal Mediation Analysis

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                Author and article information

                Contributors
                benzingert@wustl.edu
                Journal
                Alzheimers Res Ther
                Alzheimers Res Ther
                Alzheimer's Research & Therapy
                BioMed Central (London )
                1758-9193
                11 February 2022
                11 February 2022
                2022
                : 14
                : 32
                Affiliations
                [1 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Mallinckrodt Institute of Radiology, Washington University School of Medicine, ; St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO 63110 USA
                [2 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), , Washington University, ; St. Louis, MO USA
                [3 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Neurology, , Washington University in Saint Louis, ; St. Louis, MO USA
                [4 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Division of Public Health Sciences, Department of Surgery, , Washington University School of Medicine (WUSM), ; St. Louis, MO USA
                Article
                972
                10.1186/s13195-022-00972-2
                8832765
                35148796
                8fbacad2-71a2-46ad-8887-c679e01b7b1a
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 15 September 2021
                : 31 January 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: P50AG005681
                Award ID: P01AG026276
                Award ID: P01AG003991
                Award ID: T32AG05851804
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000065, National Institute of Neurological Disorders and Stroke;
                Award ID: 1P30NS098577
                Funded by: FundRef http://dx.doi.org/10.13039/100000070, National Institute of Biomedical Imaging and Bioengineering;
                Award ID: R01 EB009352
                Funded by: FundRef http://dx.doi.org/10.13039/100007338, Foundation for Barnes-Jewish Hospital;
                Funded by: McDonnell Center for Systems Neuroscience
                Funded by: FundRef http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR000448
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Neurology
                internal carotid artery,calcification,clinical dementia rating,white matter hyperintensities,mini-mental state exam,11c-pittsburgh compound b,pib,centiloid

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