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      The effects of intracranial volume adjustment approaches on multiple regional MRI volumes in healthy aging and Alzheimer's disease

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          Abstract

          In neurodegeneration research, normalization of regional volumes by intracranial volume (ICV) is important to estimate the extent of disease-driven atrophy. There is little agreement as to whether raw volumes, volume-to-ICV fractions or regional volumes from which the ICV factor has been regressed out should be used for volumetric brain imaging studies. Using multiple regional cortical and subcortical volumetric measures generated by Freesurfer (51 in total), the main aim of this study was to elucidate the implications of these adjustment approaches. Magnetic resonance imaging (MRI) data were analyzed from two large cohorts, the population-based PIVUS cohort ( N = 406, all subjects age 75) and the Alzheimer disease Neuroimaging Initiative (ADNI) cohort ( N = 724). Further, we studied whether the chosen ICV normalization approach influenced the relationship between hippocampus and cognition in the three diagnostic groups of the ADNI cohort (Alzheimer's disease, mild cognitive impairment, and healthy individuals). The ability of raw vs. adjusted hippocampal volumes to predict diagnostic status was also assessed. In both cohorts raw volumes correlate positively with ICV, but do not scale directly proportionally with it. The correlation direction is reversed for all volume-to-ICV fractions, except the lateral and third ventricles. Most gray matter fractions are larger in females, while lateral ventricle fractions are greater in males. Residual correction effectively eliminated the correlation between the regional volumes and ICV and removed gender differences. The association between hippocampal volumes and cognition was not altered by ICV normalization. Comparing prediction of diagnostic status using the different approaches, small but significant differences were found. The choice of normalization approach should be carefully considered when designing a volumetric brain imaging study.

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          Differential aging of the brain: patterns, cognitive correlates and modifiers.

          Deciphering the secret of successful aging depends on understanding the patterns and biological underpinnings of cognitive and behavioral changes throughout adulthood. That task is inseparable from comprehending the workings of the brain, the physical substrate of behavior. In this review, we summarize the extant literature on age-related differences and changes in brain structure, including postmortem and noninvasive magnetic resonance imaging (MRI) studies. Among the latter, we survey the evidence from volumetry, diffusion-tensor imaging, and evaluations of white matter hyperintensities (WMH). Further, we review the attempts to elucidate the mechanisms of age-related structural changes by measuring metabolic markers of aging through magnetic resonance spectroscopy (MRS). We discuss the putative links between the pattern of brain aging and the pattern of cognitive decline and stability. We then present examples of activities and conditions (hypertension, hormone deficiency, aerobic fitness) that may influence the course of normal aging in a positive or negative fashion. Lastly, we speculate on several proposed mechanisms of differential brain aging, including neurotransmitter systems, stress and corticosteroids, microvascular changes, calcium homeostasis, and demyelination.
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            Sex differences in cortical thickness mapped in 176 healthy individuals between 7 and 87 years of age.

            Findings from previous magnetic resonance imaging studies of sex differences in gray matter have been inconsistent, with some showing proportionally increased gray matter in women and some showing no differences between the sexes. Regional sex differences in gray matter thickness have not yet been mapped over the entire cortical surface in a large sample of subjects spanning the age range from early childhood to old age. We applied algorithms for cortical pattern matching and techniques for measuring cortical thickness to the structural magnetic resonance images of 176 healthy individuals between the ages of 7 and 87 years. We also mapped localized differences in brain size. Maps of sex differences in cortical thickness revealed thicker cortices in women in right inferior parietal and posterior temporal regions even without correcting for total brain volume. In these regions, the cortical mantle is up to 0.45 mm thicker, on average, in women than in men. Analysis of a subset of 18 female and 18 male subjects matched for age and brain volume confirmed the significance of thicker gray matter in temporal and parietal cortices in females, independent of brain size differences. Further analyses were conducted in the adult subjects where gender differences were evaluated using height as a covariate, and similar sex differences were observed even when body size differences between the sexes were controlled. Together, these results suggest that greater cortical thickness in posterior temporal inferior parietal regions in females relative to males are independent of differences in brain or body size. Age-by-sex interactions were not significant in the temporoparietal region, suggesting that sex differences in these regions are present from at least late childhood and then are maintained throughout life. Male brains were larger than female brains in all locations, though male enlargement was most prominent in the frontal and occipital poles, bilaterally. Given the large sample and the large range of ages studied, these results help to address controversies in the study of central nervous system sexual dimorphisms.
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              Changes in brain weights during the span of human life: relation of brain weights to body heights and body weights.

              More than 20,000 autopsy reports from several general hospitals were surveyed for the purpose of selecting brains without a pathological lesion that had been weighed in the fresh condition. From this number, 2,773 males and 1,963 females were chosen for whom body weight, body height, and cause of death had been recorded. The data were segregated into 23 age groups ranging from birth to 86+ years and subjected to statistical evaluation. Overall, the brain weights in males were greater than in females by 9.8%. The largest increases in brain weights in both sexes occurred during the first 3 years of life, when the value quadruples over that at birth, while during the subsequent 15 years the brain weight barely quintuples over that at birth. Progressive decline in brain weight begins at about 45 to 50 years of age and reaches its lowest values after age 86 years, by which time the mean brain weight has decreased by about 11% relative to the maximum brain weight attained in young adults (about 19 years of age). Computed regression lines for brain weights versus body heights and body weights and for ratios for brain weights to body heights and weights versus age groups show clearly differential rates of change in brain weights which are less affected by sex.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                07 October 2014
                2014
                : 6
                : 264
                Affiliations
                [1] 1Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm, Sweden
                [2] 2Department of Neuroimaging, Institute of Psychiatry, King's College London London, UK
                [3] 3NIHR Biomedical Research Centre for Mental Health and NIHR Biomedical Research Unit for Dementia London, UK
                [4] 4Department of Radiology, Uppsala University Uppsala, Sweden
                [5] 5Department of Medical Sciences, Uppsala University Uppsala, Sweden
                Author notes

                Edited by: P. Hemachandra Reddy, Oregon Health and Science University, USA

                Reviewed by: Christopher D. Kroenke, Oregon Health and Science University, USA; Lisa C. Silbert, Oregon Health and Science University, USA

                *Correspondence: Olga Voevodskaya, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Novum, Plan 5, SE-14186, Stockholm, Sweden e-mail: olga.voevodskaya@ 123456ki.se

                This article was submitted to the journal Frontiers in Aging Neuroscience.

                †Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

                Article
                10.3389/fnagi.2014.00264
                4188138
                25339897
                f8685c06-1eb6-4730-9786-13b3ba44fc00
                Copyright © 2014 Voevodskaya, Simmons, Nordenskjöld, Kullberg, Ahlström, Lind, Wahlund, Larsson, Westman and Alzheimer's Disease Neuroimaging Initiative.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 May 2014
                : 12 September 2014
                Page count
                Figures: 3, Tables: 9, Equations: 3, References: 34, Pages: 14, Words: 8646
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                intracranial volume,normalization,alzheimer's disease,neuroimaging,gender dimorphism,healthy aging

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