Benjamin Segun Aribisala1, Natalie A Royle2, Maria C Valdés Hernández2, Catherine Murray3, Lars Penke3, Alan Gow4, Susana Muñoz Maniega2, John M Starr5, Mark Bastin2, Ian Deary3, Joanna Wardlaw2. 1. Brain Research Imaging Centre, Brain Research Imaging Centre Neuroimaging Sciences University of Edinburgh, Western General Hospital, University of Edinburgh, Edinburgh, Scotland EH4 2XU, UK Computer Science Department, Faculty of Science PMB 001 LASU Post Office, Lagos State University, Ojo Lagos, Lagos, Lagos PMB 001 LASU, Nigeria. 2. Brain Research Imaging Centre, University of Edinburgh, Edinburgh, Scotland, UK. 3. Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK. 4. School of Life Sciences, Heriot-Watt University, Edinburgh, Scotland, UK Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK. 5. Geriatric Medicine, University of Edinburgh, Royal Victoria Hospital Craigleith Road, Edinburgh EH4 2DN, UK.
Abstract
BACKGROUND: intracranial volume (ICV) is commonly used as a marker of premorbid brain size in neuroimaging studies as it is thought to remain fixed throughout adulthood. However, inner skull table thickening would encroach on ICV and could mask actual brain atrophy. OBJECTIVE: we investigated the effect that thickening might have on the associations between brain atrophy and cognition. METHODS: the sample comprised 57 non-demented older adults who underwent structural brain MRI at mean age 72.7 ± 0.7 years and were assessed on cognitive ability at mean age 11 and 73 years. Principal component analysis was used to derive factors of general cognitive ability (g), information processing speed and memory from the recorded cognitive ability data. The total brain tissue volume and ICV with (estimated original ICV) and without (current ICV) adjusting for the effects of inner table skull thickening were measured. General linear modelling was used to test for associations. RESULTS: all cognitive ability variables were significantly (P < 0.01) associated with percentage total brain volume in ICV measured without adjusting for skull thickening (g: η(2) = 0.177, speed: η(2) = 0.264 and memory: η(2) = 0.132). After accounting for skull thickening, only speed was significantly associated with percentage total brain volume in ICV (η(2) = 0.085, P = 0.034), not g or memory. CONCLUSIONS: not accounting for skull thickening when computing ICV can distort the association between brain atrophy and cognitive ability in old age. Larger samples are required to determine the true effect.
BACKGROUND: intracranial volume (ICV) is commonly used as a marker of premorbid brain size in neuroimaging studies as it is thought to remain fixed throughout adulthood. However, inner skull table thickening would encroach on ICV and could mask actual brain atrophy. OBJECTIVE: we investigated the effect that thickening might have on the associations between brain atrophy and cognition. METHODS: the sample comprised 57 non-demented older adults who underwent structural brain MRI at mean age 72.7 ± 0.7 years and were assessed on cognitive ability at mean age 11 and 73 years. Principal component analysis was used to derive factors of general cognitive ability (g), information processing speed and memory from the recorded cognitive ability data. The total brain tissue volume and ICV with (estimated original ICV) and without (current ICV) adjusting for the effects of inner table skull thickening were measured. General linear modelling was used to test for associations. RESULTS: all cognitive ability variables were significantly (P < 0.01) associated with percentage total brain volume in ICV measured without adjusting for skull thickening (g: η(2) = 0.177, speed: η(2) = 0.264 and memory: η(2) = 0.132). After accounting for skull thickening, only speed was significantly associated with percentage total brain volume in ICV (η(2) = 0.085, P = 0.034), not g or memory. CONCLUSIONS: not accounting for skull thickening when computing ICV can distort the association between brain atrophy and cognitive ability in old age. Larger samples are required to determine the true effect.
Authors: Stuart J Ritchie; David Alexander Dickie; Simon R Cox; Maria Del C Valdés Hernández; Ruth Sibbett; Alison Pattie; Devasuda Anblagan; Paul Redmond; Natalie A Royle; Janie Corley; Susana Muñoz Maniega; Adele M Taylor; Sherif Karama; Tom Booth; Alan J Gow; John M Starr; Mark E Bastin; Joanna M Wardlaw; Ian J Deary Journal: Neurobiol Aging Date: 2017-10-16 Impact factor: 4.673