Literature DB >> 27989773

In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging.

Yue Zhao1, Marcus E Raichle2, Jie Wen3, Tammie L Benzinger3, Anne M Fagan4, Jason Hassenstab4, Andrei G Vlassenko3, Jie Luo3, Nigel J Cairns4, Jon J Christensen3, John C Morris4, Dmitriy A Yablonskiy5.   

Abstract

BACKGROUND: Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals.
METHODS: Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR=0; n=23) or with mild AD dementia (CDR=0.5 or 1; n=11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ42. A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n=13) and preclinical (Aβ positive; n=10) groups.
RESULTS: GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging - a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low.
CONCLUSION: We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer's disease; Beta-amyloid; GEPCI; MRI; PET; Pathology

Mesh:

Substances:

Year:  2016        PMID: 27989773      PMCID: PMC5344724          DOI: 10.1016/j.neuroimage.2016.12.026

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  67 in total

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Journal:  Neuroimage       Date:  2002-10       Impact factor: 6.556

2.  Gradient echo plural contrast imaging--signal model and derived contrasts: T2*, T1, phase, SWI, T1f, FST2*and T2*-SWI.

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3.  Regional differences in MRI detection of amyloid plaques in AD transgenic mouse brain.

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5.  Alzheimer's disease. In the beginning...

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Journal:  Nature       Date:  1991-12-12       Impact factor: 49.962

6.  Detection of neuritic plaques in Alzheimer's disease by magnetic resonance microscopy.

Authors:  H Benveniste; G Einstein; K R Kim; C Hulette; G A Johnson
Journal:  Proc Natl Acad Sci U S A       Date:  1999-11-23       Impact factor: 11.205

7.  Major decrease in the volume of the entorhinal cortex in patients with Alzheimer's disease carrying the apolipoprotein E epsilon4 allele.

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8.  Alzheimer's disease neurodegenerative biomarkers are associated with decreased cognitive function but not β-amyloid in cognitively normal older individuals.

Authors:  Miranka Wirth; Cindee M Madison; Gil D Rabinovici; Hwamee Oh; Susan M Landau; William J Jagust
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Review 9.  FSL.

Authors:  Mark Jenkinson; Christian F Beckmann; Timothy E J Behrens; Mark W Woolrich; Stephen M Smith
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10.  Cognition, reserve, and amyloid deposition in normal aging.

Authors:  Dorene M Rentz; Joseph J Locascio; John A Becker; Erin K Moran; Elisha Eng; Randy L Buckner; Reisa A Sperling; Keith A Johnson
Journal:  Ann Neurol       Date:  2010-03       Impact factor: 10.422

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  22 in total

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2.  Single scan quantitative gradient recalled echo MRI for evaluation of tissue damage in lesions and normal appearing gray and white matter in multiple sclerosis.

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3.  Automated Detection of Alzheimer's Disease Using Brain MRI Images- A Study with Various Feature Extraction Techniques.

Authors:  U Rajendra Acharya; Steven Lawrence Fernandes; Joel En WeiKoh; Edward J Ciaccio; Mohd Kamil Mohd Fabell; U John Tanik; V Rajinikanth; Chai Hong Yeong
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4.  A Novel Gradient Echo Plural Contrast Imaging Method Detects Brain Tissue Abnormalities in Patients With TBI Without Evident Anatomical Changes on Clinical MRI: A Pilot Study.

Authors:  Serguei V Astafiev; Jie Wen; David L Brody; Anne H Cross; Andrey P Anokhin; Kristina L Zinn; Maurizio Corbetta; Dmitriy A Yablonskiy
Journal:  Mil Med       Date:  2019-03-01       Impact factor: 1.437

5.  Integrating Convolutional Neural Networks and Multi-Task Dictionary Learning for Cognitive Decline Prediction with Longitudinal Images.

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Review 6.  Immune-pineal axis - acute inflammatory responses coordinate melatonin synthesis by pinealocytes and phagocytes.

Authors:  Regina P Markus; Pedro A Fernandes; Gabriela S Kinker; Sanseray da Silveira Cruz-Machado; Marina Marçola
Journal:  Br J Pharmacol       Date:  2017-12-15       Impact factor: 8.739

7.  Communicating 5-Year Risk of Alzheimer's Disease Dementia: Development and Evaluation of Materials that Incorporate Multiple Genetic and Biomarker Research Results.

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8.  Quantitative signal properties from standardized MRIs correlate with multiple sclerosis disability.

Authors:  Tammie L S Benzinger; Robert T Naismith; Matthew R Brier; Abraham Z Snyder; Aaron Tanenbaum; Richard A Rudick; Elizabeth Fisher; Stephen Jones; Joshua S Shimony; Anne H Cross
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9.  Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease.

Authors:  J O'Callaghan; H Holmes; N Powell; J A Wells; O Ismail; I F Harrison; B Siow; R Johnson; Z Ahmed; A Fisher; S Meftah; M J O'Neill; T K Murray; E C Collins; K Shmueli; M F Lythgoe
Journal:  Neuroimage       Date:  2017-08-04       Impact factor: 6.556

10.  Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer's disease: a preliminary study.

Authors:  Haifeng Chen; Weikai Li; Xiaoning Sheng; Qing Ye; Hui Zhao; Yun Xu; Feng Bai
Journal:  Eur Radiol       Date:  2021-06-10       Impact factor: 5.315

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