Structural MRI Biomarkers of Mild Cognitive Impairment from Young Elders to Centenarians

Yang, Zixuan; Wang, Wen; Jiang, Jiyang; Crawford, John D.; Reppermund, Simone; Levitan, Charlene; Slavin, Melissa J.; Kochan, Nicole A.; Richmond, Robyn; Brodaty, Henry; Trollor, Julian N.; Sachdev, Perminder S.

doi:10.2174/1567205013666151218150534

Cited by 13 publications

(13 citation statements)

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“…18 Yang and colleagues found reduced regional temporal and frontal volume reductions among others when comparing patients with aMCI to healthy controls, whereas no significant volumetric differences could be detected between non-aMCI patients and controls. 29 In line with our results and existing PET data, this suggests that brain structure changes in patients with aMCI are less localized than it could be assumed given the characteristic memory impairment.…”

Section: Discussionsupporting

confidence: 91%

Precuneus Structure Changes in Amnestic Mild Cognitive Impairment

Haußmann

Werner

Gruschwitz

et al. 2016

Am J Alzheimers Dis Other Demen

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Patients with amnestic mild cognitive impairment (aMCI) are at risk for developing Alzheimer's disease. Due to their prominent memory impairment, structural magnetic resonance imaging (MRI) often focuses on the hippocampal region. However, recent positron-emission tomography data suggest that within a network of frontal and temporal changes, patients with aMCI show metabolic alterations in the precuneus, a key region for higher cognitive functions. Using high-resolution MRI and whole-brain cortical thickness analyses in 28 patients with aMCI and 25 healthy individuals, we wanted to investigate whether structural changes in the precuneus would be associated with cortical thickness reductions in frontal and temporal brain regions in patients with aMCI. In contrast to healthy people, patients with aMCI showed an association of cortical thinning in the precuneus with predominantly left-hemispheric thickness reductions in medial temporal and frontal cortices. Our data highlight structural neuronal network characteristics among patients with aMCI.

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Section: Discussionsupporting

confidence: 91%

Precuneus Structure Changes in Amnestic Mild Cognitive Impairment

Haußmann

Werner

Gruschwitz

et al. 2016

Am J Alzheimers Dis Other Demen

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“…Cerebrospinal fluid and plasma biomarkers, as well as amyloid imaging markers, can offer information about neuropathological symptoms of AD, when no evidence markers for hippocampal volume loss can be accurately exported from MRI scanning [ 49 ]. Especially structrural MRI biomarkers conclude to major variations among young and elderly populations, associating different neuropathological underpinnings of cognitive impairment in the very old populations [ 50 ].…”

Section: Discussionmentioning

confidence: 99%

Biomarkers for Alzheimer's Disease Diagnosis

Mantzavinos¹,

Alexiou²

2017

CAR

218

138

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Objective:The dramatic increase in the population with dementia expected in the next decades is accompanied by the establishment of novel and innovated methods that will offer accurate and efficient detection of the disease in its early stages. While Alzheimer’s disease is the most common cause of dementia, by the time it is typically diagnosed, substantial neuronal loss and neuropathological lesions can damage many brain regions. The aim of this study is to investigate the main risk factors that affect and increase Alzheimer’s disease progression over time even in cases with no significant memory impairment present. Several potential markers are discussed such as oxidative stress, metal ions, vascular disorders, protein dysfunctions and alterations in the mitochondrial populations.Conclusion:A multiparametric model of Alzheimer’s biomarkers is presented according to the latest classification of the disease.

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“…According to BN theory, if we assume a directed graph G with N nodes, each node n ∈ N has a number of paternal nodes pa(n) that may be linked with “child” nodes and the joint distribution for such a network given as follows:

\begin{matrix} left \\ P false(N false) = \prod_{n \in N} p false(n | p a false(n false) false) . \end{matrix}

By taking into consideration the latest calculations for the relative probabilities of AD progression due to certain brain lesions (Table 2) (Christen, 2000; de la Torre, 2002; Praticò et al, 2002; Modrego and Ferrández, 2004; Hooper et al, 2007; Cheung et al, 2008; Stone, 2008; Schuff et al, 2009; Snider et al, 2009; Wang et al, 2009; Israeli-Korn et al, 2010; Barnes and Yaffe, 2011; Nazem and Mansoori, 2011; Serrano-Pozo et al, 2011; Bird, 2012; Alzheimer's Association, 2015; Chakrabarty et al, 2015) and the majority of the published AD biomarkers (Albert et al, 2010, 2011; Besson et al, 2015; Cabezas-Opazo et al, 2015; Dong et al, 2015; Duce et al, 2015; Eskildsen et al, 2015; Jansen et al, 2015; Madeira et al, 2015; Michel, 2015; Nakanishi et al, 2015; Ossenkoppele et al, 2015; Østergaard et al, 2015; Quiroz et al, 2015; Ringman et al, 2015; Risacher et al, 2015; Sastre et al, 2015; Schindler and Fagan, 2015; Sutphen et al, 2015; Thordardottir et al, 2015; Cauwenberghe et al, 2016; Counts et al, 2016; Gaël et al, 2016; Yang et al, 2016) or calculating indirectly the relative probabilities, we designed a Bayesian model for the prediction of AD based on the abnormal testing of one or more biomarkers. The described probabilities were exported through major clinical trials globally and are continuously subject to updating and redefinition.…”

Section: Methodsmentioning

confidence: 99%

A Bayesian Model for the Prediction and Early Diagnosis of Alzheimer's Disease

Alexiou¹,

Mantzavinos

Greig

et al. 2017

Front. Aging Neurosci.

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Alzheimer's disease treatment is still an open problem. The diversity of symptoms, the alterations in common pathophysiology, the existence of asymptomatic cases, the different types of sporadic and familial Alzheimer's and their relevance with other types of dementia and comorbidities, have already created a myth-fear against the leading disease of the twenty first century. Many failed latest clinical trials and novel medications have revealed the early diagnosis as the most critical treatment solution, even though scientists tested the amyloid hypothesis and few related drugs. Unfortunately, latest studies have indicated that the disease begins at the very young ages thus making it difficult to determine the right time of proper treatment. By taking into consideration all these multivariate aspects and unreliable factors against an appropriate treatment, we focused our research on a non-classic statistical evaluation of the most known and accepted Alzheimer's biomarkers. Therefore, in this paper, the code and few experimental results of a computational Bayesian tool have being reported, dedicated to the correlation and assessment of several Alzheimer's biomarkers to export a probabilistic medical prognostic process. This new statistical software is executable in the Bayesian software Winbugs, based on the latest Alzheimer's classification and the formulation of the known relative probabilities of the various biomarkers, correlated with Alzheimer's progression, through a set of discrete distributions. A user-friendly web page has been implemented for the supporting of medical doctors and researchers, to upload Alzheimer's tests and receive statistics on the occurrence of Alzheimer's disease development or presence, due to abnormal testing in one or more biomarkers.

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Structural MRI Biomarkers of Mild Cognitive Impairment from Young Elders to Centenarians

Abstract: Structural MRI distinguishes aMCI, but not naMCI, from CN in elderly individuals. The structures that best distinguish aMCI from CN differ in those <85 from those ≥85, suggesting different neuropathological underpinnings of cognitive impairment in the very old.

Cited by 13 publications

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Precuneus Structure Changes in Amnestic Mild Cognitive Impairment

Precuneus Structure Changes in Amnestic Mild Cognitive Impairment

Biomarkers for Alzheimer's Disease Diagnosis

A Bayesian Model for the Prediction and Early Diagnosis of Alzheimer's Disease

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