Timeline of Brain Alterations in Alzheimer’s Disease Across the Entire Lifespan

Coupé, Pierrick; Jv, Manjón; Lanuza, Enrique; Catheline, Gwénaëlle

doi:10.1101/229195

Cited by 6 publications

(6 citation statements)

References 50 publications

(61 reference statements)

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“…2 are remarkably similar to those from a recent meta-analysis with more than 100,000 HR isotropic scans (47): They correctly capture the peak of the white matter at about 30 years, the earlier decline of the gray matter, and the highly nonlinear trajectory of the ventricles. Despite using clinical scans with large spacing, our method also produces trajectories for subcortical ROIs that are highly consistent with previously published studies relying on thousands of 1-mm isotropic T1 scans (48,49), showing, e.g., earlier atrophy of the thalamus compared with hippocampus or amygdala.…”

Section: Image Segmentation and Volumetry With Existing Toolssupporting

confidence: 83%

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

et al. 2023

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Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in hospitals across the world. These have the potential to revolutionize our understanding of many neurological diseases, but their morphometric analysis has not yet been possible due to their anisotropic resolution. We present an artificial intelligence technique, “SynthSR,” that takes clinical brain MRI scans with any MR contrast (T1, T2, etc.), orientation (axial/coronal/sagittal), and resolution and turns them into high-resolution T1 scans that are usable by virtually all existing human neuroimaging tools. We present results on segmentation, registration, and atlasing of >10,000 scans of controls and patients with brain tumors, strokes, and Alzheimer’s disease. SynthSR yields morphometric results that are very highly correlated with what one would have obtained with high-resolution T1 scans. SynthSR allows sample sizes that have the potential to overcome the power limitations of prospective research studies and shed new light on the healthy and diseased human brain.

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Section: Image Segmentation and Volumetry With Existing Toolssupporting

confidence: 83%

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

et al. 2023

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“…Replicating our earlier finding (Chao, 2020), veterans with MCI had smaller hippocampal volume compared to veterans with unimpaired cognition in this study. Previous longitudinal studies have reported morphometric difference in the hippocampi of incident AD cases at least 10 years prior to diagnosis (den Heijer et al, 2010;Bernard et al, 2014;Coupe et al, 2017). In a study that compared two models (normal and pathological) of brain aging, Coupe et al (2019) reported that the hippocampus was the first brain region to diverge from normal aging.…”

Section: Discussionmentioning

confidence: 97%

The prevalence of mild cognitive impairment in Gulf War veterans: a follow-up study

Chao,

Sullivan,

Krengel

et al. 2024

Front. Neurosci.

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IntroductionGulf War Illness (GWI), also called Chronic Multisymptom Illness (CMI), is a multi-faceted condition that plagues an estimated 250,000 Gulf War (GW) veterans. Symptoms of GWI/CMI include fatigue, pain, and cognitive dysfunction. We previously reported that 12% of a convenience sample of middle aged (median age 52 years) GW veterans met criteria for mild cognitive impairment (MCI), a clinical syndrome most prevalent in older adults (e.g., ≥70 years). The current study sought to replicate and extend this finding.MethodsWe used the actuarial neuropsychological criteria and the Montreal Cognitive Assessment (MoCA) to assess the cognitive status of 952 GW veterans. We also examined regional brain volumes in a subset of GW veterans (n = 368) who had three Tesla magnetic resonance images (MRIs).ResultsWe replicated our previous finding of a greater than 10% rate of MCI in four additional cohorts of GW veterans. In the combined sample of 952 GW veterans (median age 51 years at time of cognitive testing), 17% met criteria for MCI. Veterans classified as MCI were more likely to have CMI, history of depression, and prolonged (≥31 days) deployment-related exposures to smoke from oil well fires and chemical nerve agents compared to veterans with unimpaired and intermediate cognitive status. We also replicated our previous finding of hippocampal atrophy in veterans with MCI, and found significant group differences in lateral ventricle volumes.DiscussionBecause MCI increases the risk for late-life dementia and impacts quality of life, it may be prudent to counsel GW veterans with cognitive dysfunction, CMI, history of depression, and high levels of exposures to deployment-related toxicants to adopt lifestyle habits that have been associated with lowering dementia risk. With the Food and Drug Administration’s recent approval of and the VA’s decision to cover the cost for anti-amyloid β (Aβ) therapies, a logical next step for this research is to determine if GW veterans with MCI have elevated Aβ in their brains.

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“…After a highly dynamic early postnatal period, brain growth stabilizes in adulthood, when interindividual differences become well established. These differences result from varying and nonlinear growth patterns in different brain structures throughout the lifespan (Coupé et al, 2017;Danielsen et al, 2020), leading to interindividual differences in brain volume, shape, development, and proportion between brain structures.…”

Section: Correlation Between Brain Volume and Stereotaxic Coordinatesmentioning

confidence: 99%

From imaging to precision: low cost and accurate determination of stereotactic coordinates for brain surgery Sapajus apella using MRI

Pedrosa,

Leal,

Muniz

et al. 2024

Front. Neurosci.

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The capuchin monkey (Sapajus apella), a New World monkey species, exhibits prominent characteristics that make it an ideal model for neuroscience research. These characteristics include its phylogenetic traits, telencephalization coefficient, anatomical structures and pathways, genetic profile, immune responses, cognitive abilities, and complex behavioral repertoires. Traditionally, methodologies for stereotactic neurosurgery in research models have relied on the use of brain atlases. However, this approach can lead to errors due to the considerable variation in brain size and shape among individual monkeys. To address this issue, we developed a protocol for deriving individual coordinates for each monkey using a straightforward and relatively inexpensive method involving MRI imaging. Our protocol utilizes a specially designed, 3D-printed stereotactic head-holder that is safe to use with an MR magnet, non-invasive placement of fiducial markers, and post-processing with open-source software. This approach enhances MRI data visualization, improves anatomical targeting, and refines the design of neurosurgical experiments. Our technique could also prove beneficial in other areas of neuroscience research that require accurate calculation of stereotaxic coordinates. Furthermore, it could be useful for other nonhuman primate species for which brain atlases are typically unavailable.

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Timeline of Brain Alterations in Alzheimer’s Disease Across the Entire Lifespan

Cited by 6 publications

References 50 publications

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

The prevalence of mild cognitive impairment in Gulf War veterans: a follow-up study

From imaging to precision: low cost and accurate determination of stereotactic coordinates for brain surgery Sapajus apella using MRI

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