scholarly journals Free water elimination improves test–retest reproducibility of diffusion tensor imaging indices in the brain: A longitudinal multisite study of healthy elderly subjects

2016 ◽  
Vol 38 (1) ◽  
pp. 12-26 ◽  
Author(s):  
Angela Albi ◽  
Ofer Pasternak ◽  
Ludovico Minati ◽  
Moira Marizzoni ◽  
David Bartrés‐Faz ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Free Water ◽  
Elderly Subjects ◽  
Healthy Elderly ◽  
Water Elimination ◽  
The Brain ◽  
Healthy Elderly Subjects

Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects

NeuroImage ◽  
2014 ◽  
Vol 101 ◽  
pp. 390-403 ◽  
Author(s):  
Jorge Jovicich ◽  
Moira Marizzoni ◽  
Beatriz Bosch ◽  
David Bartrés-Faz ◽  
Jennifer Arnold ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Elderly Subjects ◽  
Healthy Elderly ◽  
Tract Based Spatial Statistics ◽  
Healthy Elderly Subjects

scholarly journals Intrinsic Functional Connectivity Networks in Healthy Elderly Subjects: A Multiparametric Approach with Structural Connectivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Martin Gorges ◽  
Hans-Peter Müller ◽  
Albert C. Ludolph ◽  
Volker Rasche ◽  
Jan Kassubek
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Elderly Subjects ◽  
Single Subject ◽  
Group Level ◽  
Intrinsic Functional Connectivity ◽  
Healthy Elderly ◽  
Healthy Elderly Subjects

Intrinsic functional connectivity magnetic resonance imaging (iFCMRI) provides an encouraging approach for mapping large-scale intrinsic connectivity networks (ICNs) in the “resting” brain. Structural connections as measured by diffusion tensor imaging (DTI) are a major constraint on the identified ICNs. This study aimed at the combined investigation of ten well-defined ICNs in healthy elderly subjects at single subject level as well as at the group level, together with the underlying structural connectivity. IFCMRI and DTI data were acquired in twelve subjects (68 ± 7 years) at a 3T scanner and were studied using thetensor imaging and fiber trackingsoftware package. The seed-based iFCMRI analysis approach was comprehensively performed with DTI analysis, following standardized procedures including an 8-step processing of iFCMRI data. Our findings demonstrated robust ICNs at the single subject level and conclusive brain maps at the group level in the healthy elderly sample, supported by the complementary fiber tractography. The findings demonstrated here provide a methodological framework for future comparisons of pathological (e.g., neurodegenerative) conditions with healthy controls on the basis of multiparametric functional connectivity mapping.

scholarly journals [Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging

2017 ◽  
Author(s):  
Rafael Neto Henriques ◽  
Ariel Rokem ◽  
Eleftherios Garyfallidis ◽  
Samuel St-Jean ◽  
Eric Thomas Peterson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Free Water ◽  
Compartment Model ◽  
B Values ◽  
Brain White Matter ◽  
Diffusion Weighted ◽  
Two Compartment Model ◽  
Water Elimination

Typical diffusion-weighted imaging (DWI) is susceptible to partial volume effects: different types of tissue that reside in the same voxel are inextricably mixed. For instance, in regions near the cerebral ventricles or parenchyma, fractional anisotropy (FA) from diffusion tensor imaging (DTI) may be underestimated, due to partial volumes of cerebral spinal fluid (CSF). Free-water can be suppressed by adding parameters to diffusion MRI models. For example, the DTI model can be extended to separately take into account the contributions of tissue and CSF, by representing the tissue compartment with an anisotropic diffusion tensor and the CSF compartment as an isotropic free water diffusion coefficient. Recently, two procedures were proposed to fit this two-compartment model to diffusion-weighted data acquired for at least two different non-zero diffusion MRI b-values. In this work, the first open-source reference implementation of these procedures is provided. In addition to presenting some methodological improvements that increase model fitting robustness, the free water DTI procedures are re-evaluated using Monte-Carlo multicompartmental simulations. Analogous to previous studies, our results show that the free water elimination DTI model is able to remove confounding effects of fast diffusion for typical FA values of brain white matter. In addition, this study confirms that for a fixed scanning time the fwDTI fitting procedures have better performance when data is acquired for diffusion gradient direction evenly distributed along two b-values of 500 and 1500 s/mm2.

scholarly journals Microstructural white matter alterations in preclinical Alzheimer’s disease detected using free water elimination diffusion tensor imaging

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173982 ◽  
Author(s):  
Andrew R. Hoy ◽  
Martina Ly ◽  
Cynthia M. Carlsson ◽  
Ozioma C. Okonkwo ◽  
Henrik Zetterberg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Free Water ◽  
Preclinical Alzheimer’S Disease ◽  
Water Elimination

scholarly journals Whole-blood metabolomics of dementia patients reveal classes of disease-linked metabolites

2021 ◽  
Vol 118 (37) ◽  
pp. e2022857118
Author(s):  
Takayuki Teruya ◽  
Yung-Ju Chen ◽  
Hiroshi Kondoh ◽  
Yasuhide Fukuji ◽  
Mitsuhiro Yanagida
Keyword(s):  
Whole Blood ◽  
Brain Function ◽  
Elderly Subjects ◽  
Healthy Elderly ◽  
Dementia Patients ◽  
Adenosyl Methionine ◽  
The Central Nervous System ◽  
The Brain ◽  
Related Compounds ◽  
Healthy Elderly Subjects

Dementia is caused by factors that damage neurons. We quantified small molecular markers in whole blood of dementia patients, using nontargeted liquid chromatography–mass spectroscopy (LC-MS). Thirty-three metabolites, classified into five groups (A to E), differed significantly in dementia patients, compared with healthy elderly subjects. Seven A metabolites present in plasma, including quinolinic acid, kynurenine, and indoxyl-sulfate, increased. Possibly they act as neurotoxins in the central nervous system (CNS). The remaining 26 compounds (B to E) decreased, possibly causing a loss of support or protection of the brain in dementia. Six B metabolites, normally enriched in red blood cells (RBCs), all contain trimethylated ammonium moieties. These metabolites include ergothioneine and structurally related compounds that have scarcely been investigated as dementia markers, validating the examination of RBC metabolites. Ergothioneine, a potent antioxidant, is significantly decreased in various cognition-related disorders, such as mild cognitive impairment and frailty. C compounds also include some oxidoreductants and are normally abundant in RBCs (NADP+, glutathione, adenosine triphosphate, pantothenate, S-adenosyl-methionine, and gluconate). Their decreased levels in dementia patients may also contribute to depressed brain function. Twelve D metabolites contains plasma compounds, such as amino acids, glycerophosphocholine, dodecanoyl-carnitine, and 2-hydroxybutyrate, which normally protect the brain, but their diminution in dementia may reduce that protection. Seven D compounds have been identified previously as dementia markers. B to E compounds may be critical to maintain the CNS by acting directly or indirectly. How RBC metabolites act in the CNS and why they diminish significantly in dementia remain to be determined.

scholarly journals Optimization of a free water elimination two-compartment model for diffusion tensor imaging

NeuroImage ◽  
2014 ◽  
Vol 103 ◽  
pp. 323-333 ◽  
Author(s):  
Andrew R. Hoy ◽  
Cheng Guan Koay ◽  
Steven R. Kecskemeti ◽  
Andrew L. Alexander
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Free Water ◽  
Compartment Model ◽  
Two Compartment Model ◽  
Water Elimination

Quantitative aspects of glucose production and metabolism in healthy elderly subjects

Diabetes ◽  
1982 ◽  
Vol 31 (3) ◽  
pp. 203-211 ◽  
Author(s):  
J. J. Robert ◽  
J. C. Cummins ◽  
R. R. Wolfe ◽  
M. Durkot ◽  
D. E. Matthews ◽  
...  
Keyword(s):  
Glucose Production ◽  
Elderly Subjects ◽  
Healthy Elderly ◽  
Healthy Elderly Subjects
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