ArticleNeuroImage2017
In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging.
Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02414347 (F 18 T807 Tau PET Imaging of Alzheimer's Disease [IND# 123119] Protocol A), which is not on this map. Cited by 37 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
F 18 T807 Tau PET Imaging of Alzheimer's Disease [IND# 123119] Protocol A
Who cites it
37 citing papers in PubMed, 70 citations in OpenAlex.
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- AI-powered Gradient Echo Plural Contrast Imaging (AI-GEPCI) - a Comprehensive Multiparametric Neurological Protocol from a Single MRI Scan.medRxiv : the preprint server for health sciences · 2026Article
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- A Graph Convolutional Network Based on Univariate Neurodegeneration Biomarker for Alzheimer's Disease Diagnosis.IEEE journal of translational engineering in health and medicine · 2023Article
- Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling.Magnetic resonance in medicine · 2023Article
- HTLML: Hybrid AI Based Model for Detection of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2022Article
- Machine learning based on the multimodal connectome can predict the preclinical stage of Alzheimer's disease: a preliminary study.European radiology · 2022Article
- Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
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Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAlzheimer 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.
methodsOur 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 Aβ
resultsGEPCI 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.
conclusionWe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.