Alzheimer’s Disease Neuroimaging Initiative
Ludwig Maximilian University of Munich
PathologyMagnetic resonance imagingOncologyNeuroscienceCognitionNeurodegenerationAlzheimer's Disease Neuroimaging InitiativeDiseaseDementiaCerebrospinal fluidHippocampusAtrophyCognitive declineComputer scienceAlzheimer's diseaseNeuroimagingMedicineBiomarker (medicine)BiologyAmyloid
538Publications
29H-index
3,939Citations
Publications 534
Newest
#1Michael Ouk (Sunnybrook Research Institute)H-Index: 1
#2Che-Yuan Wu (Sunnybrook Research Institute)H-Index: 1
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Abstract Some studies suggest that angiotensin II type-1 Receptor Blockers (ARBs) may protect against memory decline more than Angiotensin-Converting Enzyme Inhibitors (ACE-Is), but few have examined possible mechanisms. We assessed longitudinal differences between ARB vs. ACE-I users in global and sub-regional amyloid-β accumulation by 18F-florbetapir among Alzheimer’s Disease Neuroimaging Initiative participants. In cognitively normal older adults (n=142), propensity-weighted linear mixed-effe...
1 CitationsSource
#1Farshid Sepehrband (SC: University of Southern California)H-Index: 13
#2Giuseppe Barisano (SC: University of Southern California)H-Index: 6
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Vascular contributions to early cognitive decline are increasingly recognized, prompting further investigation into the nature of related changes in perivascular spaces (PVS). Using magnetic resonance imaging, we show that, compared to a cognitively normal sample, individuals with early cognitive dysfunction have altered PVS presence and distribution, irrespective of Amyloid-β. Surprisingly, we noted lower PVS presence in the anterosuperior medial temporal lobe (asMTL) (1.29 times lower PVS volu...
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#1Jinhyeong Bae (NU: Northwestern University)H-Index: 1
#2Jane Stocks (NU: Northwestern University)H-Index: 1
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Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learning model to predict conversion from MCI to DAT. Structural magnetic resonance imaging scans were used as input to a 3-dimensional convolutional neural network. The 3-dimensional convolutional neural network was trained using transfer learning; in the...
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#1Ahmed A. Moustafa (UJ: University of Johannesburg)H-Index: 40
#2Richard Tindle (CSU: Charles Sturt University)H-Index: 4
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Abstract Background This study explores how mild cognitive impairment (MCI) and Alzheimer’s disease (AD) develop over time. New method this study involves a new application of latent curve models (LCM) to examine the development trajectory of a healthy, MCI, and AD groups on a series of clinical and neural measures. Multiple-group latent curve models were used to compare the parameters of the trajectories across groups. Results LCM results showed that a linear functional form of growth was adequ...
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#1Xiaoxi Ji (HIT: Harbin Institute of Technology)H-Index: 1
#2Hui WangH-Index: 1
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Postmortem studies on patients with Alzheimer's disease (AD) have confirmed that the dorsal raphe nucleus (DRN) in the brainstem is the first brain structure affected in the earliest stage of AD. The present study examined the brainstem in the early stage of AD using magnetic resonance (MR) imaging. T1-weighted MR images of the brains of 81 subjects were obtained from the publicly available Open Access Series of Imaging Studies (OASIS) database, including 27 normal control (NC) subjects, 27 pati...
5 CitationsSource
#1Zuo-Teng Wang (Ocean University of China)H-Index: 3
#2Xue-Ning Shen (Fudan University)H-Index: 4
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Abstract Background: Depression is considered a psychological risk factor for Alzheimer's disease (AD). We sought to examine the differential associations of depression severity with cognitive decline, clinical progression to mild cognitive impairment (MCI) or AD, and neuroimaging markers of AD in cognitively normal older adults. Methods: A total of 522 cognitively normal (CN) participants who underwent assessments for depression (longitudinal geriatric depression scale [GDS] ) and cognitive ass...
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#1Gabriel Gonzalez-Escamilla (University of Mainz)H-Index: 8
#2Isabelle Miederer (University of Mainz)H-Index: 5
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Alzheimer's disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 c...
1 CitationsSource
#1Avinash Chandra ('KCL': King's College London)H-Index: 5
#2Chloe Farrell ('KCL': King's College London)
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Abstract Clearance of amyloid-β (Aβ) from the brain is hypothesised to be mediated by the glymphatic system through aquaporin-4 (AQP4) water channels. Genetic variation of AQP4 may impact water channel function, Aβ clearance and clinical outcomes. We examined whether single nucleotide polymorphisms (SNPs) of the AQP4 gene were related to Aβ neuropathology on [18F]Florbetapir PET in 100 Aβ positive late mild cognitive impairment (LMCI) or Alzheimer’s disease (AD) patients, and were predictive of ...
3 CitationsSource
BACKGROUND Noninvasive identification of amyloid-β (Aβ) is important for better clinical management of mild cognitive impairment (MCI) patients. OBJECTIVE To investigate whether radiomics features in the hippocampus in MCI improve the prediction of cerebrospinal fluid (CSF) Aβ42 status when integrated with clinical profiles. METHODS A total of 407 MCI subjects from the Alzheimer's Disease Neuroimaging Initiative were allocated to training (n = 324) and test (n = 83) sets. Radiomics features (n =...
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#1Kilian Hett (Vandy: Vanderbilt University)H-Index: 1
#2Vinh-Thong Ta (L'Abri)H-Index: 15
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Abstract The prediction of subjects with mild cognitive impairment (MCI) who will progress to Alzheimer’s disease (AD) is clinically relevant, and may above all have a significant impact on accelerating the development of new treatments. In this paper, we present a new MRI-based biomarker that enables us to accurately predict conversion of MCI subjects to AD. In order to better capture the AD signature, we introduce two main contributions. First, we present a new graph-based grading framework to...
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