ArticleHuman brain mapping2022
A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age.
Article in Human brain mapping, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Cerebral cortical alterations in adolescent early-onset psychosis: a surface-based morphometry mega-analysis.Molecular psychiatry · 2026Article
- Inclusion of intracranial volume as a covariate feature improves MRI-based Alzheimer's disease classification.Magma (New York, N.Y.) · 2026Article
- Brain Age Estimation on T2-FLAIR Scans for Application to Multiple Sclerosis.Human brain mapping · 2026Article
- Comparison of Three Automated Measurements of Ventricular Volumes of the Brain.Journal of imaging informatics in medicine · 2026Article
- Pneumocephalus after deep brain stimulation in Parkinson's disease: The role of brain volume in brain shift.Surgical neurology international · 2026Article
- Longitudinal MRI-based changes in intracranial volume and skull thickness observed in both metachromatic leukodystrophy and multiple sclerosis.NeuroImage. Clinical · 2026Article
- Longitudinal development of sex differences in the limbic system is associated with age, puberty and mental health.Communications biology · 2025Article
- Estimation of the Intracranial Volume Is Crucial in Multi-Site Studies: Reliability for Longitudinal Investigations and Traveling Subjects.Human brain mapping · 2025Article
- Regional gray matter volume is associated with motor imagery performance in children with and without developmental coordination disorder.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Hypothalamus and intracranial volume segmentation at the group level by use of a Gradio-CNN framework.International journal of computer assisted radiology and surgery · 2025Article
- Reversal of cerebral pseudoatrophy in normal pressure hydrocephalus after ventriculoatrial shunt placement.Scientific reports · 2025Article
- A lifespan-generalizable skull-stripping model for magnetic resonance images that leverages prior knowledge from brain atlases.Nature biomedical engineering · 2025Article
- Brain and intracranial volumes are both enlarged and serve as potential risk factors in normal pressure hydrocephalus.Scientific reports · 2025Article
- Article
- Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Distinct Volume Alterations of Thalamic Nuclei Across the Schizophrenia Spectrum.Schizophrenia bulletin · 2024Article
- Article
- Altered Sex Differences in Hippocampal Subfield Volumes in Schizophrenia.Schizophrenia bulletin · 2024Article
- Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR.Journal of neurology · 2023Article
- Elevated dementia risk, cognitive decline, and hippocampal atrophy in multisite chronic pain.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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11 authors.
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Abstract
Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.
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