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Article ; Online: MRI Assessment of Cerebral White Matter Microvascular Hemodynamics Across the Adult Lifespan.

Damestani, Nikou L / Jacoby, John / Michel, Christa B / Rashid, Barnaly / Salat, David H / Juttukonda, Meher R

Journal of magnetic resonance imaging : JMRI

2024

Abstract: Background: Changes in cerebral hemodynamics with aging are important for understanding age-related variation in neuronal health. While many prior studies have focused on gray matter, less is known regarding white matter due in part to measurement ... ...

Abstract	Background: Changes in cerebral hemodynamics with aging are important for understanding age-related variation in neuronal health. While many prior studies have focused on gray matter, less is known regarding white matter due in part to measurement challenges related to the lower vascular density in white matter. Purpose: To investigate the impact of age and sex on white matter hemodynamics in a Human Connectome Project in Aging (HCP-A) cohort using tract-based spatial statistics (TBSS). Study type: Retrospective cross-sectional. Population: Six hundred seventy-eight typically aging individuals (381 female), aged 36-100 years. Field strength/sequence: Multi-delay pseudo-continuous arterial spin labeling (ASL) and diffusion-weighted pulsed-gradient spin-echo echo planar imaging sequences at 3.0 T. Assessment: A skeleton of mean fractional anisotropy (FA) was produced using TBSS. This skeleton was used to project ASL-derived cerebral blood flow (CBF) and arterial transit time (ATT) measures onto white matter tracts. Statistical tests: General linear models were applied to white matter FA, CBF, and ATT maps, while covarying for age and sex. Threshold-free cluster enhancement multiple comparisons correction was performed for the effects of age and sex, thresholded at P Results: Significantly lower white matter CBF and significantly prolonged white matter ATTs were associated with older age. These effects were widespread across tracts for ATT. Significant (P Data conclusion: This study identified significant sex- and age-associated differences in white matter hemodynamics across tracts. Evidence level: 3 TECHNICAL EFFICACY: Stage 3.
Language	English
Publishing date	2024-01-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.29217
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Zs.A 3648: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 236: Show issues

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Article ; Online: The canonical pattern of Alzheimer's disease atrophy is linked to white matter hyperintensities in normal controls, differently in normal controls compared to in AD.

Riphagen, Joost M / Suresh, Mahanand Belathur / Salat, David H

Neurobiology of aging

2022 Volume 114, Page(s) 105–112

Abstract: White matter signal abnormalities (WMSA), either hypo- or hyperintensities in MRI imaging, are considered a proxy of cerebrovascular pathology and contribute to, and modulate, the clinical presentation of Alzheimer's disease (AD), with cognitive ... ...

Abstract	White matter signal abnormalities (WMSA), either hypo- or hyperintensities in MRI imaging, are considered a proxy of cerebrovascular pathology and contribute to, and modulate, the clinical presentation of Alzheimer's disease (AD), with cognitive dysfunction being apparent at lower levels of amyloid and/or tau pathology when lesions are present. To what extent the topography of cortical thinning associated with AD may be explained by WMSA remains unclear. Cortical thickness group difference maps and subgroup analyses show that the effect of WMSA on cortical thickness in cognitively normal participants has a higher overlap with the canonical pattern of AD, compared to AD participants. (Age and sex-matched group of 119 NC (AV45 PET negative, CDR = 0) versus 119 participants with AD (AV45 PET-positive, CDR > 0.5). The canonical patterns of cortical atrophy thought to be specific to Alzheimer's disease are strongly linked to cerebrovascular pathology supporting a reinterpretation of the classical models of AD suggesting that a part of the typical AD pattern is due to co-localized cortical loss before the onset of AD.
MeSH term(s)	Alzheimer Disease/diagnostic imaging ; Alzheimer Disease/pathology ; Atrophy/pathology ; Cognitive Dysfunction/pathology ; Humans ; Magnetic Resonance Imaging ; White Matter/diagnostic imaging ; White Matter/pathology
Language	English
Publishing date	2022-02-28
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	604505-4
ISSN	1558-1497 ; 0197-4580
ISSN (online)	1558-1497
ISSN	0197-4580
DOI	10.1016/j.neurobiolaging.2022.02.008
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Zs.A 1685: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Brain age gap difference between healthy and mild dementia subjects: Functional network connectivity analysis.

Sendi, Mohammad S E / Salat, David H / Calhoun, Vince D

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2021 Volume 2021, Page(s) 1636–1639

Abstract: Brain age gap, the difference between an individual's brain predicted age and their chronological age, is used as a biomarker of brain disease and aging. To date, although previous studies used structural magnetic resonance imaging (MRI) data to predict ... ...

Abstract	Brain age gap, the difference between an individual's brain predicted age and their chronological age, is used as a biomarker of brain disease and aging. To date, although previous studies used structural magnetic resonance imaging (MRI) data to predict brain age, less work has used functional network connectivity (FNC) estimated from functional MRI to predict brain age and its association with Alzheimer's disease progression. This study used FNC estimated from 951 normal cognitive functions (NCF) individuals aged 42-95 years to train a support vector regression (SVR) to predict brain age. In the next step, we tested the trained model on two unseen datasets, including NCF and mild dementia (MD) subjects with similar age distribution (between 50-80 years old, N=70). The mean brain age gap for the NCF and MD groups was -2.25 and 2.08, respectively. We also found a significant difference between the brain age gap of NCF and MD groups. This piece of evidence introduces the brain age gap estimated from FNC as a biomarker of Alzheimer's disease progression.
MeSH term(s)	Adult ; Aged ; Aged, 80 and over ; Aging ; Alzheimer Disease/diagnosis ; Brain/diagnostic imaging ; Dementia/diagnosis ; Humans ; Magnetic Resonance Imaging ; Middle Aged
Language	English
Publishing date	2021-12-10
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC46164.2021.9630648
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Article ; Online: Mean Arterial Pressure and Cerebral Hemodynamics Across The Lifespan: A Cross-Sectional Study From Human Connectome Project-Aging.

Yetim, Ezgi / Jacoby, John / Damestani, Nikou L / Lovely, Allison E / Salat, David H / Juttukonda, Meher R

Journal of magnetic resonance imaging : JMRI

2023 Volume 58, Issue 6, Page(s) 1892–1900

Abstract: Background: Cerebral perfusion is directly affected by systemic blood pressure, which has been shown to be negatively correlated with cerebral blood flow (CBF). The impact of aging on these effects is not fully understood.: Purpose: To determine ... ...

Abstract	Background: Cerebral perfusion is directly affected by systemic blood pressure, which has been shown to be negatively correlated with cerebral blood flow (CBF). The impact of aging on these effects is not fully understood. Purpose: To determine whether the relationship between mean arterial pressure (MAP) and cerebral hemodynamics persists throughout the lifespan. Study type: Retrospective, cross-sectional study. Population: Six hundred and sixty-nine participants from the Human Connectome Project-Aging ranging between 36 and 100+ years and without a major neurological disorder. Field strength/sequence: Imaging data was acquired at 3.0 Tesla using a 32-channel head coil. CBF and arterial transit time (ATT) were measured by multi-delay pseudo-continuous arterial spin labeling. Assessment: The relationships between cerebral hemodynamic parameters and MAP were evaluated globally in gray and white matter and regionally using surface-based analysis in the whole group, separately within different age groups (young: <60 years; younger-old: 60-79 years; oldest-old: ≥80 years). Statistical tests: Chi-squared, Kruskal-Wallis, ANOVA, Spearman rank correlation and linear regression models. The general linear model setup in FreeSurfer was used for surface-based analyses. P < 0.05 was considered significant. Results: Globally, there was a significant negative correlation between MAP and CBF in both gray (ρ = -0.275) and white matter (ρ = -0.117). This association was most prominent in the younger-old [gray matter CBF (β = -0.271); white matter CBF (β = -0.241)]. In surface-based analyses, CBF exhibited a widespread significant negative association with MAP throughout the brain, whereas a limited number of regions showed significant prolongation in ATT with higher MAP. The associations between regional CBF and MAP in the younger-old showed a different topographic pattern in comparison to young subjects. Data conclusion: These observations further emphasize the importance of cardiovascular health in mid-to-late adulthood for healthy brain aging. The differences in the topographic pattern with aging indicate a spatially heterogeneous relationship between high blood pressure and CBF. Level of evidence: 3 TECHNICAL EFFICACY STAGE: 3.
MeSH term(s)	Humans ; Aged, 80 and over ; Adult ; Middle Aged ; Cross-Sectional Studies ; Longevity ; Arterial Pressure ; Magnetic Resonance Imaging/methods ; Retrospective Studies ; Connectome ; Brain/diagnostic imaging ; Brain/blood supply ; Hemodynamics ; Arteries ; Cerebrovascular Circulation/physiology ; Aging ; Spin Labels
Chemical Substances	Spin Labels
Language	English
Publishing date	2023-04-11
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.28722
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Zs.A 3648: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 236: Show issues

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Article ; Online: Current themes and issues in neuroimaging of aging processes: Editorial overview to the special issue on imaging the nonpathological aging brain.

Salat, David H / Kennedy, Kristen M

NeuroImage

2019 Volume 201, Page(s) 116046

MeSH term(s)	Aging/physiology ; Brain/diagnostic imaging ; Brain/physiology ; Humans ; Neuroimaging
Language	English
Publishing date	2019-07-31
Publishing country	United States
Document type	Editorial
ZDB-ID	1147767-2
ISSN	1095-9572 ; 1053-8119
ISSN (online)	1095-9572
ISSN	1053-8119
DOI	10.1016/j.neuroimage.2019.116046
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Zs.A 3664: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Brain structural indicators of β-amyloid neuropathology.

Jang, Ikbeom / Li, Binyin / Rashid, Barnaly / Jacoby, John / Huang, Susie Y / Dickerson, Bradford C / Salat, David H

Neurobiology of aging

2024 Volume 136, Page(s) 157–170

Abstract: Recent efforts demonstrated the efficacy of identifying early-stage neuropathology of Alzheimer's disease (AD) through lumbar puncture cerebrospinal fluid assessment and positron emission tomography (PET) radiotracer imaging. These methods are effective ... ...

Abstract	Recent efforts demonstrated the efficacy of identifying early-stage neuropathology of Alzheimer's disease (AD) through lumbar puncture cerebrospinal fluid assessment and positron emission tomography (PET) radiotracer imaging. These methods are effective yet are invasive, expensive, and not widely accessible. We extend and improve the multiscale structural mapping (MSSM) procedure to develop structural indicators of β-amyloid neuropathology in preclinical AD, by capturing both macrostructural and microstructural properties throughout the cerebral cortex using a structural MRI. We find that the MSSM signal is regionally altered in clear positive and negative cases of preclinical amyloid pathology (N = 220) when cortical thickness alone or hippocampal volume is not. It exhibits widespread effects of amyloid positivity across the posterior temporal, parietal, and medial prefrontal cortex, surprisingly consistent with the typical pattern of amyloid deposition. The MSSM signal is significantly correlated with amyloid PET in almost half of the cortex, much of which overlaps with regions where beta-amyloid accumulates, suggesting it could provide a regional brain 'map' that is not available from systemic markers such as plasma markers.
MeSH term(s)	Humans ; Amyloid beta-Peptides/metabolism ; Brain/metabolism ; Alzheimer Disease/pathology ; Positron-Emission Tomography/methods ; Magnetic Resonance Imaging/methods ; Amyloid/metabolism
Chemical Substances	Amyloid beta-Peptides ; Amyloid
Language	English
Publishing date	2024-01-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	604505-4
ISSN	1558-1497 ; 0197-4580
ISSN (online)	1558-1497
ISSN	0197-4580
DOI	10.1016/j.neurobiolaging.2024.01.005
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Zs.A 1685: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: A two-step clustering-based pipeline for big dynamic functional network connectivity data.

Sendi, Mohammad S E / Miller, Robyn L / Salat, David H / Calhoun, Vince D

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2022 Volume 2022, Page(s) 3741–3744

Abstract: Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporal properties of FNC among brain networks by putting them into distinct states using the clustering method. The ... ...

Abstract	Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporal properties of FNC among brain networks by putting them into distinct states using the clustering method. The computational cost of clustering dFNCs has become a significant practical barrier given the availability of enormous neuroimaging datasets. To this end, we developed a new dFNC pipeline to analyze large dFNC data without accessing hug processing capacity. We validated our proposed pipeline and compared it with the standard one using a publicly available dataset. We found that both standard and iSparse kmeans generate similar dFNC states while our approach is 27 times faster than the traditional method in finding the optimum number of clusters and creating better clustering quality.
MeSH term(s)	Big Data ; Brain/diagnostic imaging ; Cluster Analysis ; Neuroimaging
Language	English
Publishing date	2022-09-10
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC48229.2022.9871997
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Article ; Online: Multiscale structural mapping of Alzheimer's disease neurodegeneration.

Jang, Ikbeom / Li, Binyin / Riphagen, Joost M / Dickerson, Bradford C / Salat, David H

NeuroImage. Clinical

2022 Volume 33, Page(s) 102948

Abstract: The recently described biological framework of Alzheimer's disease (AD) emphasizes three types of pathology to characterize this disorder, referred to as the 'amyloid/tau/neurodegeneration' (A-T-N) status. The 'neurodegenerative' component is typically ... ...

Abstract	The recently described biological framework of Alzheimer's disease (AD) emphasizes three types of pathology to characterize this disorder, referred to as the 'amyloid/tau/neurodegeneration' (A-T-N) status. The 'neurodegenerative' component is typically defined by atrophy measures derived from structural magnetic resonance imaging (MRI) such as hippocampal volume. Neurodegeneration measures from imaging are associated with disease symptoms and prognosis. Thus, sensitive image-based quantification of neurodegeneration in AD has an important role in a range of clinical and research operations. Although hippocampal volume is a sensitive metric of neurodegeneration, this measure is impacted by several clinical conditions other than AD and therefore lacks specificity. In contrast, selective regional cortical atrophy, known as the 'cortical signature of AD' provides greater specificity to AD pathology. Although atrophy is apparent even in the preclinical stages of the disease, it is possible that increased sensitivity to degeneration could be achieved by including tissue microstructural properties in the neurodegeneration measure. However, to facilitate clinical feasibility, such information should be obtainable from a single, short, noninvasive imaging protocol. We propose a multiscale MRI procedure that advances prior work through the quantification of features at both macrostructural (morphometry) and microstructural (tissue properties obtained from multiple layers of cortex and subcortical white matter) scales from a single structural brain image (referred to as 'multi-scale structural mapping'; MSSM). Vertex-wise partial least squares (PLS) regression was used to compress these multi-scale structural features. When contrasting patients with AD to cognitively intact matched older adults, the MSSM procedure showed substantially broader regional group differences including areas that were not statistically significant when using cortical thickness alone. Further, with multiple machine learning algorithms and ensemble procedures, we found that MSSM provides accurate detection of individuals with AD dementia (AUROC = 0.962, AUPRC = 0.976) and individuals with mild cognitive impairment (MCI) that subsequently progressed to AD dementia (AUROC = 0.908, AUPRC = 0.910). The findings demonstrate the critical advancement of neurodegeneration quantification provided through multiscale mapping. Future work will determine the sensitivity of this technique for accurately detecting individuals with earlier impairment and biomarker positivity in the absence of impairment.
MeSH term(s)	Aged ; Alzheimer Disease/pathology ; Atrophy/pathology ; Cognitive Dysfunction/pathology ; Hippocampus/pathology ; Humans ; Magnetic Resonance Imaging/methods
Language	English
Publishing date	2022-01-22
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2701571-3
ISSN	2213-1582 ; 2213-1582
ISSN (online)	2213-1582
ISSN	2213-1582
DOI	10.1016/j.nicl.2022.102948
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Article: Two-step clustering-based pipeline for big dynamic functional network connectivity data.

Sendi, Mohammad S E / Salat, David H / Miller, Robyn L / Calhoun, Vince D

Frontiers in neuroscience

2022 Volume 16, Page(s) 895637

Abstract: Background: Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporally varying functional integration between brain networks. In a conventional dFNC pipeline, a clustering ... ...

Abstract	Background: Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporally varying functional integration between brain networks. In a conventional dFNC pipeline, a clustering stage to summarize the connectivity patterns that are transiently but reliably realized over the course of a scanning session. However, identifying the right number of clusters (or states) through a conventional clustering criterion computed by running the algorithm repeatedly over a large range of cluster numbers is time-consuming and requires substantial computational power even for typical dFNC datasets, and the computational demands become prohibitive as datasets become larger and scans longer. Here we developed a new dFNC pipeline based on a two-step clustering approach to analyze large dFNC data without having access to huge computational power. Methods: In the proposed dFNC pipeline, we implement two-step clustering. In the first step, we randomly use a sub-sample dFNC data and identify several sets of states at different model orders. In the second step, we aggregate all dFNC states estimated from all iterations in the first step and use this to identify the optimum number of clusters using the elbow criteria. Additionally, we use this new reduced dataset and estimate a final set of states by performing a second kmeans clustering on the aggregated dFNC states from the first k-means clustering. To validate the reproducibility of results in the new pipeline, we analyzed four dFNC datasets from the human connectome project (HCP). Results: We found that both conventional and proposed dFNC pipelines generate similar brain dFNC states across all four sessions with more than 99% similarity. We found that the conventional dFNC pipeline evaluates the clustering order and finds the final dFNC state in 275 min, while this process takes only 11 min for the proposed dFNC pipeline. In other words, the new pipeline is 25 times faster than the traditional method in finding the optimum number of clusters and finding the final dFNC states. We also found that the new method results in better clustering quality than the conventional approach ( Conclusion: We developed a new analytic pipeline that facilitates the analysis of large dFNC datasets without having access to a huge computational power source. We validated the reproducibility of the result across multiple datasets.
Language	English
Publishing date	2022-07-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2411902-7
ISSN	1662-453X ; 1662-4548
ISSN (online)	1662-453X
ISSN	1662-4548
DOI	10.3389/fnins.2022.895637
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Article ; Online: Accelerated longitudinal cortical atrophy in OEF/OIF/OND veterans with severe PTSD and the impact of comorbid TBI.

Brown, Emma M / Salat, David H / Milberg, William P / Fortier, Catherine B / McGlinchey, Regina E

Human brain mapping

2022 Volume 43, Issue 12, Page(s) 3694–3705

Abstract: Veterans who deployed in support of Operation Enduring Freedom (OEF), Iraqi Freedom (OIF), and New Dawn (OND) commonly experience severe psychological trauma, often accompanied by physical brain trauma resulting in mild traumatic brain injury (mTBI). ... ...

Abstract	Veterans who deployed in support of Operation Enduring Freedom (OEF), Iraqi Freedom (OIF), and New Dawn (OND) commonly experience severe psychological trauma, often accompanied by physical brain trauma resulting in mild traumatic brain injury (mTBI). Prior studies of individuals with posttraumatic stress disorder (PTSD) have revealed alterations in brain structure, accelerated cellular aging, and impacts on cognition following exposure to severe psychological trauma and potential interactive effects of military-related mTBI. To date, however, little is known how such deployment-related trauma changes with time and age of injury of the affected veteran. In this study, we explored changes in cortical thickness, volume, and surface area after an average interval of approximately 2 years in a cohort of 254 OEF/OIF/OND Veterans ranging in age from 19 to 67 years. Whole-brain vertex-wise analyses revealed that veterans who met criteria for severe PTSD (Clinician-Administered PTSD Scale ≥60) at baseline showed greater negative longitudinal changes in cortical thickness, volume, and area over time. Analyses also revealed a significant severe-PTSD by age interaction on cortical measures with severe-PTSD individuals exhibiting accelerated cortical degeneration with increasing age. Interaction effects of comorbid military-related mTBI within the severe-PTSD group were also observed in several cortical regions. These results suggest that those exhibiting severe PTSD symptomatology have accelerated atrophy that is exacerbated with increasing age and history of mTBI.
MeSH term(s)	Adult ; Afghan Campaign 2001- ; Aged ; Atrophy ; Brain Concussion/complications ; Brain Concussion/diagnostic imaging ; Brain Concussion/epidemiology ; Humans ; Iraq War, 2003-2011 ; Middle Aged ; Neurodegenerative Diseases ; Stress Disorders, Post-Traumatic/complications ; Stress Disorders, Post-Traumatic/diagnostic imaging ; Stress Disorders, Post-Traumatic/epidemiology ; Veterans/psychology ; Young Adult
Language	English
Publishing date	2022-04-15
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1197207-5
ISSN	1097-0193 ; 1065-9471
ISSN (online)	1097-0193
ISSN	1065-9471
DOI	10.1002/hbm.25877
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