Neuroimage. 2016 Aug 15;137:9-20. doi: 10.1016/j.neuroimage.2016.05.016.

Normative data for subcortical regional volumes over the lifetime of the adult human brain.

Potvin O1, Mouiha A1, Dieumegarde L1, Duchesne S2; Alzheimer’s Disease Neuroimaging Initiative.
  • 1Centre de recherche de l’Institut universitaire en santé mentale de Québec, 2601, de la Canardière, Québec G1J 2G3, Canada.
  • 2Centre de recherche de l’Institut universitaire en santé mentale de Québec, 2601, de la Canardière, Québec G1J 2G3, Canada; Département de radiologie, Université Laval, 1050, avenue de la Médecine, Québec G1V 0A6, Canada. Electronic address: Simon.Duchesne@fmed.ulaval.ca.

Abstract

Normative data for volumetric estimates of brain structures are necessary to adequately assess brain volume alterations in individuals with suspected neurological or psychiatric conditions. Although many studies have described age and sex effects in healthy individuals for brain morphometry assessed via magnetic resonance imaging, proper normative values allowing to quantify potential brain abnormalities are needed. We developed norms for volumetric estimates of subcortical brain regions based on cross-sectional magnetic resonance scans from 2790 healthy individuals aged 18 to 94years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting subcortical regional volumes of each hemisphere were produced including age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The mean explained variance by the models was 48%. For most regions, age, sex and eTIV predicted most of the explained variance while manufacturer, magnetic field strength and interactions predicted a limited amount. Estimates of the expected volumes of an individual based on its characteristics and the scanner characteristics can be obtained using derived formulas. For a new individual, significance test for volume abnormality, effect size and estimated percentage of the normative population with a smaller volume can be obtained. Normative values were validated in independent samples of healthy adults and in adults with Alzheimer’s disease and schizophrenia.

Copyright © 2016 Elsevier Inc. All rights reserved.

KEYWORDS: Aging; Atrophy; Magnetic resonance imaging; Morphometry; Normality; Sex

PMID: 27165761

 

Supplement:

Magnetic resonance imaging (MRI) is widely used to evaluate regional brain volume abnormalities. However, proper quantification of the volumes’ deviation from the normality according to an individual’s age and sex is problematic since there are no proper reference standards of the normality. This lack of normative values is due to many factors. Automated segmentation techniques, anatomical definitions, and scanner magnetic field strength and manufacturer all have an influence on the generated regional brain volumes.

In order to build normative data for subcortical regional volumes, we assembled a large sample of individual with a wide age range and segmented the MRI images using FreeSurfer, a widely used and freely available automated segmentation software. We produced models predicting expected volumes according to age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, and magnetic field strength. Using these models, the quantification of volume abnormality for any individuals compared to the normative sample can be assessed. Along with this article, we also published in Data in Brief a Microsoft Excel spreadsheet to easily calculate volume abnormality, Z score effect sizes and estimates of the normative population with a smaller volume. With these normative values and spreadsheet, we hope to enable researchers by providing the necessary tools to correctly assess and interpret novel structural MRI data in their respective studies.

 

 

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Figure 1. Illustration of how the normative values can be used with a new individual. To compute the expected left hippocampal volume of a new subject, the individual and scanner characteristics, a 61 years old female with an MRI image from a Philips 3T scanner and an estimated intracranial volume of 1521907 mm3, are entered in the given formula in the Excel spreadsheet which yields 4209 mm3. Her actual volume is 3400 mm3, which is represented by an orange X on the graphic in the middle and appears below the mean of the normative sample according to his age and sex (green curve for female). A Z score is calculated by subtracting the actual volume from the expected volume divided by the root mean square error of the model predicting the expected left hippocampal volume. This new subject has a Z score of -2.1, which means that her left hippocampal volume is more than two standard deviations below what is expected for her age, sex, and estimated intracranial volume.

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