Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis

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Abstract

There is no consensus in literature about lifespan brain maturation and senescence, mainly because previous lifespan studies have been performed on restricted age periods and/or with a limited number of scans, making results instable and their comparison very difficult. Moreover, the use of nonharmonized tools and different volumetric measurements lead to a great discrepancy in reported results. Thanks to the new paradigm of BigData sharing in neuroimaging and the last advances in image processing enabling to process baby as well as elderly scans with the same tool, new insights on brain maturation and aging can be obtained. This study presents brain volume trajectory over the entire lifespan using the largest age range to date (from few months of life to elderly) and one of the largest number of subjects ( N = 2,944). First, we found that white matter trajectory based on absolute and normalized volumes follows an inverted U‐shape with a maturation peak around middle life. Second, we found that from 1 to 8–10 y there is an absolute gray matter (GM) increase related to body growth followed by a GM decrease. However, when normalized volumes were considered, GM continuously decreases all along the life. Finally, we found that this observation holds for almost all the considered subcortical structures except for amygdala which is rather stable and hippocampus which exhibits an inverted U‐shape with a longer maturation period. By revealing the entire brain trajectory picture, a consensus can be drawn since most of the previously discussed discrepancies can be explained. Hum Brain Mapp 38:5501–5518, 2017 . © 2017 Wiley Periodicals, Inc.

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Most cited references 32

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Sexual dimorphism of brain developmental trajectories during childhood and adolescence.

Rhoshel K. Lenroot, Nitin Gogtay, Deanna Greenstein … (2007)

Human total brain size is consistently reported to be approximately 8-10% larger in males, although consensus on regionally specific differences is weak. Here, in the largest longitudinal pediatric neuroimaging study reported to date (829 scans from 387 subjects, ages 3 to 27 years), we demonstrate the importance of examining size-by-age trajectories of brain development rather than group averages across broad age ranges when assessing sexual dimorphism. Using magnetic resonance imaging (MRI) we found robust male/female differences in the shapes of trajectories with total cerebral volume peaking at age 10.5 in females and 14.5 in males. White matter increases throughout this 24-year period with males having a steeper rate of increase during adolescence. Both cortical and subcortical gray matter trajectories follow an inverted U shaped path with peak sizes 1 to 2 years earlier in females. These sexually dimorphic trajectories confirm the importance of longitudinal data in studies of brain development and underline the need to consider sex matching in studies of brain development.

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Adaptive non-local means denoising of MR images with spatially varying noise levels.

José Manjón, Pierrick Coupé, Luis Martí-Bonmatí … (2010)

To adapt the so-called nonlocal means filter to deal with magnetic resonance (MR) images with spatially varying noise levels (for both Gaussian and Rician distributed noise). Most filtering techniques assume an equal noise distribution across the image. When this assumption is not met, the resulting filtering becomes suboptimal. This is the case of MR images with spatially varying noise levels, such as those obtained by parallel imaging (sensitivity-encoded), intensity inhomogeneity-corrected images, or surface coil-based acquisitions. We propose a new method where information regarding the local image noise level is used to adjust the amount of denoising strength of the filter. Such information is automatically obtained from the images using a new local noise estimation method. The proposed method was validated and compared with the standard nonlocal means filter on simulated and real MRI data showing an improved performance in all cases. The new noise-adaptive method was demonstrated to outperform the standard filter when spatially varying noise is present in the images. (c) 2009 Wiley-Liss, Inc.

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Structural brain development between childhood and adulthood: Convergence across four longitudinal samples

Kathryn L Mills, Anne-Lise Goddings, Megan Herting … (2016)

Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8–30 years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies.

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Author and article information

Journal

Title: Human Brain Mapping

Abbreviated Title: Hum. Brain Mapp.

Publisher: Wiley

ISSN: 10659471

Publication date Created: November 2017

Publication date (Print): November 2017

Publication date (Electronic): July 24 2017

Volume: 38

Issue: 11

Pages: 5501-5518

Affiliations

[1 ]University of Bordeaux, LaBRI, UMR 5800, PICTURA; Talence F-33400 France

[2 ]CNRS, LaBRI, UMR 5800, PICTURA; Talence F-33400 France

[3 ]University of Bordeaux, CNRS, EPHE PSL Research University of, INCIA, UMR 5283; Bordeaux F-33000, France

[4 ]Department of Cell Biology; University of Valencia; Burjassot Valencia 46100 Spain

[5 ]Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), Universitat Politècnica de València, Camino de Vera s/n; Valencia 46022 Spain