Cognitive Decline Assessment: A Review From Medical Imaging Perspective

Dartora, Caroline Machado; Borelli, Wyllians Vendramini; Silva, Ana Maria Marques da

doi:10.3389/fnagi.2021.704661

Cited by 7 publications

(4 citation statements)

References 77 publications

(195 reference statements)

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“…Third, it is noteworthy that amyloid‐PET data were unavailable for all individuals with AD and MCI included in our study. Consequently, the diagnostic process relied primarily on clinical data and imaging markers (Dartora et al, 2021; Sheng et al, 2020). Future research should incorporate ample gold‐standard evidence, including amyloid‐PET imaging, to strengthen diagnostic validity.…”

Section: Discussionmentioning

confidence: 99%

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Zhang,

Chen,

Huang

et al. 2024

Human Brain Mapping

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Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0‐T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including β‐amyloid (Aβ), phosphorylated tau181 (p‐tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 × 10−24; quadratic trend: t = 7.708, p = 2.25 × 10−13; adjusted R2 = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 × 10−10; quadratic trend: t = 3.896, p = 1.22 × 10−4; adjusted R2 = 0.330), p‐tau181 (linear trend: t = 8.452, p = 1.61 × 10−15; quadratic trend: t = 6.316, p = 1.05 × 10−9; adjusted R2 = 0.346) and Aβ42/Aβ40 (linear trend: t = −3.257, p = 1.27 × 10−3; quadratic trend: t = −1.662, p = 9.76 × 10−2; adjusted R2 = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = −0.61, p = 6.3 × 10−7), NfL (R = −0.57, p = 6.4 × 10−6), and p‐tau181 (R = −0.48, p = 2.0 × 10−4). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = −0.224, 95% confidence interval [CI] = [−0.417 to −0.029], p = .0196 for MMSE; ab = −0.198, 95% CI = [−0.42 to −0.003], p = .0438 for MOCA) or NfL (ab = −0.224, 95% CI = [−0.417 to −0.029], p = .0196 for MMSE; ab = −0.198, 95% CI = [−0.42 to −0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network‐plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.

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Section: Discussionmentioning

confidence: 99%

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Zhang,

Chen,

Huang

et al. 2024

Human Brain Mapping

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“…Changes in lipid levels in the central nervous system also affect the glucose metabolism of hippocampal neurons in brain areas responsible for learning and memory. 13 − 16 Lipids also play an important role in hippocampal neuron plasticity, learning, and memory. 17 In this study, we found that the levels of ketogenic and glycogenic amino acids (tryptophan, phenylalanine, and tyrosine), lipid intake, and glucose utilization in the internal environment of 14 DIV neurons decreased.…”

Section: Discussionmentioning

confidence: 99%

Deciphering the Heterogeneity of the Internal Environment of Hippocampal Neurons during Maturation by Raman Spectroscopy

et al. 2022

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Hippocampal neurons are sensitive to changes in the internal environment and play a significant role in controlling learning, memory, and emotions. A remarkable characteristic of the aging brain is its ability to shift from a state of normal inflammation to excessive inflammation. Various cognitive abilities of the elderly may suffer from serious harm due to the change in the neural environment. Hippocampal neurons may have various subsets involved in controlling their internal environment at different stages of development. Developmental differences may eventually result from complex changes in the dynamic neuronal system brought on by metabolic changes. In this study, we used an in vitro hippocampal neuron model cultured in C57BL/6J mice in conjugation with Raman spectroscopy to examine the relative alterations in potential biomarkers, such as levels of metabolites in the internal environment of hippocampal neurons at various developmental stages. The various differentially expressed genes (DEGs) of hippocampal neurons at various developmental stages were simultaneously screened using bioinformatics, and the biological functions as well as the various regulatory pathways of DEGs were preliminarily analyzed, providing an essential reference for investigating novel therapeutic approaches for diseases that cause cognitive impairment, such as Alzheimer’s disease. A stable hippocampal neuron model was established using the GIBCO C57BL/6J hippocampal neuron cell line as a donor and in vitro hippocampal neuron culture technology. The Raman peak intensities of culture supernatants from the experimental groups incubated for 0, 7, and 14 days in vitro(DIV) were examined. The GEO database was used to screen for different DEGs associated with various developmental stages. The data was then analyzed using a statistical method called orthogonal partial least squares discriminant analysis (OPLS-DA). The levels of ketogenic and glycogenic amino acids (such as tryptophan, phenylalanine, and tyrosine), lipid intake rate, glucose utilization rate, and nucleic acid expression in the internal environment of hippocampal neurons were significantly different in the 14 DIV group compared to the 0 DIV and 7 DIV groups ( P < 0.01). The top 10 DEGs with neuronal maturation were screened, and the results were compared to the OPLS-DA model’s analysis of the differential peaks. It was found that different genes involved in maturation can directly relate to changes in the body’s levels of ketogenic and glycogenic amino acids ( P < 0.01). The altered expression of the maturation-related genes epidermal growth factor receptor, protein tyrosine kinase 2-beta, discs large MAGUK scaffold protein 2, and Ras protein-specific guanine nucleotide releasing factor 1 may be connected to the altered uptake of ketogenic and glycogenic amino acids and nucleic acids in the internal environment of neurons at different developmental stages. The levels of ketogenic, glycogenic amino acids, and lipid intake ...

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“…A tomografia por emissão de pósitrons ou PET (do inglês, Positron Emission Tomography) e as imagens por ressonância magnética ou MR (do inglês, Magnetic Resonance) são modalidades essenciais no estudo das doenças neurológicas, oncológicas e cardíacas. Ambas as modalidades de imagem são relevantes no estudo do envelhecimento cerebral, que provoca modificações desde os níveis moleculares até os morfológicos, alterando o tamanho do cérebro, a vasculatura e cognição (1). As imagens por PET têm proporcionado abordagens quantitativas para apoiar o diagnóstico diferencial em doenças neurodegenerativas, como a doença de Alzheimer (DA) (1,2).As imagens por PET e MR têm proporcionado abordagens quantitativas para apoiar o diagnóstico diferencial em doenças neurodegenerativas, como a doença de Alzheimer (DA) (1,2).…”

Section: Introductionunclassified

Implementação da Escala Centiloide para o radiotraçador Neuraceq [18F]Florbetaben

Silva

Souza²,

Silva³

2023

Rev Bras Fis Med

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A tomografia por emissão de pósitrons (PET) e a ressonância magnética (MR) são modalidades relevantes no estudo do envelhecimento cerebral. A deposição de placa beta-amiloide (bA) pode ser avaliada por PET utilizando radiotraçadores específicos, como [11C]PiB ou [18F]Florbetaben. A escala Centiloide (CL) foi desenvolvida para reduzir a variabilidade do protocolo de processamento e produzir uma quantificação harmonizada das imagens PET de bA. O objetivo deste estudo é apresentar o processo de implementação da escala CL para o radiotraçador [18F]Florbetaben em nossa instituição. Para tanto, é preciso validar o pipeline de processamento e análise das imagens com os dados disponibilizados pela Rede Interativa da Associação Global de Alzheimer (GAAIN) para o radiotraçador [18F]Florbetaben e [11C]PiB. O GAAIN possui imagens de PET e MR de 10 controles (bA negativos) e 25 indivíduos bA positivos, incluindo idosos cognitivamente saudáveis, com comprometimento cognitivo leve, doença de Alzheimer e demência frontotemporal. Na escala CL são utilizados os valores de captação entre região cortical global (CTX), que considera as regiões córtex frontal, temporal, parietal, precuneus, estriato anterior e córtex insular, e o cerebelo inteiro (WC), como região de referência. O processamento das imagens foi realizado utilizando o software PMOD, com a ferramenta PNEURO. Como resultado, obtivemos uma forte correlação entre os valores de [18F]Florbetaben e [11C]PiB para os mesmos indivíduos. A equação final que transforma os valores SUVR do [18F]Florbetaben para escala CL em nossa instituição é: CLFBB= 156,47 * SUVR*PIBind - 157,47. A equação foi validada e atingiu os valores mínimos requeridos pelo Klunk et al (2015) de coeficiente de determinação R²=0,997, coeficiente angular igual a 1,00 e coeficiente linear igual a 1,34.Conclui-se que a implementação da escala CL em nossa instituição é viável,constituindo um passo importante para a utilização clínica dessa escala para investigação longitudinal de indivíduos em processo de envelhecimento usando radiotraçadores bA.

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Cognitive Decline Assessment: A Review From Medical Imaging Perspective

Cited by 7 publications

References 77 publications

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum

Deciphering the Heterogeneity of the Internal Environment of Hippocampal Neurons during Maturation by Raman Spectroscopy

Implementação da Escala Centiloide para o radiotraçador Neuraceq [18F]Florbetaben

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