Variance in brain volume with advancing age

implications for defining the limits of normality

David Alexander Dickie, Dominic E Job, David Rodriguez Gonzalez, Susan D Shenkin, Trevor S Ahearn, Alison D Murray, Joanna M Wardlaw

Research output: Contribution to journalArticle

15 Citations (Scopus)
5 Downloads (Pure)

Abstract

Background

Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.

Materials and Methods

We acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.

Results

In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.

Conclusions

While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.
Original languageEnglish
Article numbere84093
Number of pages12
JournalPloS ONE
Volume8
Issue number12
DOIs
Publication statusPublished - 19 Dec 2013

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Brain
brain
Tissue
Alzheimer disease
Alzheimer Disease
Aging of materials
Neurodegenerative diseases
neurodegenerative diseases
Neurodegenerative Diseases
sampling
tissues
early diagnosis
Normal Distribution
Magnetic resonance
Early Diagnosis
Magnetic Resonance Spectroscopy
Databases

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Variance in brain volume with advancing age : implications for defining the limits of normality. / Dickie, David Alexander; Job, Dominic E; Gonzalez, David Rodriguez; Shenkin, Susan D; Ahearn, Trevor S; Murray, Alison D; Wardlaw, Joanna M.

In: PloS ONE, Vol. 8, No. 12, e84093, 19.12.2013.

Research output: Contribution to journalArticle

Dickie, David Alexander ; Job, Dominic E ; Gonzalez, David Rodriguez ; Shenkin, Susan D ; Ahearn, Trevor S ; Murray, Alison D ; Wardlaw, Joanna M. / Variance in brain volume with advancing age : implications for defining the limits of normality. In: PloS ONE. 2013 ; Vol. 8, No. 12.
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abstract = "BackgroundStatistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.Materials and MethodsWe acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.ResultsIn both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74{\%} to 75{\%}). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5th percentile rank of normal subjects were ~39{\%} greater than mean differences in the AD subjects.ConclusionsWhile more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.",
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N2 - BackgroundStatistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.Materials and MethodsWe acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.ResultsIn both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.ConclusionsWhile more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.

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