a systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing

8/18/2019 A Systematic Review and Meta-Analysis of Longitudinal Hippocampal Atrophy in Healthy Human Ageing

1/12

Review

A systematic review and meta-analysis of longitudinal hippocampalatrophy in healthy human ageing☆,☆☆,★,★★

Mark A. Fraser ⁎, Marnie E. Shaw, Nicolas Cherbuin

Centre for Research on Ageing, Health and Wellbeing, Florey, Building 54, Mills Road, Australian National University, Canberra, ACT 2601, Australia

a b s t r a c ta r t i c l e i n f o

Article history:

Received 25 October 2014

Accepted 14 March 2015Available online 20 March 2015

Keywords:

Hippocampus

MRI

Longitudinal

Ageing

Epidemiology

Controls

Introduction: This review aimed to produce hippocampal atrophy rate estimates from healthy ageing studies as

well as control samples from observational studies across the adult lifespan which can be used as benchmarks

to evaluate abnormal changes in pathological conditions.Methods: The review followed PRISMA guidelines. PUBMED (to February 2014) was searched for longitudinal

MRI studies reporting hippocampal atrophy or volume change in cognitively healthy individuals. Titles were

screened and non-English, duplicate or irrelevant entries were excluded. Remaining record abstracts were

reviewedto identify studiesfor fulltext retrieval. Fulltext wasretrieved andscreened againstinclusion/exclusion

criteria. Bibliographies and previous reviews were examined to identify additional studies. Data were

summarised using meta-analysis and age, segmentation technique and study type weretested as potential mod-

erators using meta-regression. It was hypothesised that population studies would produce higher atrophy rates

than clinical observational studies.

Results: The systematic search identied 4410 entries and 119studieswere retrievedwith 58 failing selectionor

quality criteria, 30 were excluded as multiple reports and 3 studies were unsuitable for meta-analysis. The re-

maining 28 studies were included in the meta-analysis, n = 3422, 44.65% male, 11,735 person-years of follow-

up, mean age was 24.50 to 83 years. Mean total hippocampal atrophy for the entire sample was 0.85% per year

(95% CI 0.63, 1.07). Age based atrophy rates were 0.38% per year (CI 0.14, 0.62) for studies with mean age

b55 years (n = 413), 0.98% (CI 0.27, 1.70) for 55 to b70 years (n = 426), and 1.12% (CI 0.86, 1.38) for

≥70 years (n = 2583). Meta-regression indicated age was associated with increased atrophy rates of 0.0263%(CI 0.0146, 0.0379) per year and automated segmentation approaches were associated with a reduced atrophy

rate of −0.466% (CI −0.841, −0.090). Population studies were not associated with a signicant effect on atro-

phy. Analyses of 11 studies separately measuring left and right hippocampal atrophy (n = 1142) provided little

evidence of laterality effects. While no study separately reported atrophy by gender, a number tested for gender

effects and 2 studies reported higher atrophy in males.

Conclusions: Hippocampal atrophy rates increase with age with the largest increases occurring from midlife on-

wards. Manual segmentation approaches result in higher measured atrophy rates.

© 2015 Elsevier Inc. All rights reserved.

Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

Inclusion and exclusion criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

Data extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366

NeuroImage 112 (2015) 364–374

☆ Statistical analysis: Mark Frasera.☆☆ Disclosure: The authors have reported no conicts of interest.★ Disclosures: Mark Fraser reports no disclosures. This study is not industry sponsored.

★★ Contributions: Mr. Fraser contributed to the design of the study, conducted all statistical analyses, and managed all aspects of manuscript preparation and submission. Dr. Shaw

providedmethodological input and theoretical expertise,and contributed to writing and editing of the manuscript. Dr. Cherbuin contributed to the design of the study andthe statistical

analyses, provided methodological input and theoretical expertise, and contributed to writing and editing of the manuscript.

⁎ Corresponding author. Fax: +61 2 6125 1558.

E-mail address: [email protected] (M.A. Fraser).

http://dx.doi.org/10.1016/j.neuroimage.2015.03.035

1053-8119/© 2015 Elsevier Inc. All rights reserved.

Contents lists available at ScienceDirect

NeuroImage

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / y n i m g

http://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://dx.doi.org/10.1016/j.neuroimage.2015.03.035mailto:[email protected]://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://www.sciencedirect.com/science/journal/10538119http://www.elsevier.com/locate/ynimghttp://www.elsevier.com/locate/ynimghttp://www.sciencedirect.com/science/journal/10538119http://dx.doi.org/10.1016/j.neuroimage.2015.03.035mailto:[email protected]://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://crossmark.crossref.org/dialog/?doi=10.1016/j.neuroimage.2015.03.035&domain=pdf


2/12

Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Missing data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Reporting bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Meta-analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Reporting bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Laterality effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Moderators & heterogeneity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Reporting bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Dropouts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Limitations of the study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Introduction

The hippocampus plays an essential role in memory function, goal

selection, and mood regulation. Hippocampal volume changes have

been associated with neurological conditions including Alzheimer's

disease ( Jack et al., 2000; West et al., 1994), Parkinson's disease

(Camicioli et al., 2003), Huntington's disease (Majid et al., 2011),

epilepsy (Liu et al., 2001), schizophrenia (Wang et al., 2008), and

depression (Arnone et al., 2012; Steffens et al., 2011). Hippocampal

volume changes also occur across the typical adult lifespan (Raz et al.,

2010). However, the magnitude of normal hippocampal age related

change is unclear and this presents a challenge when evaluating

abnormal changes in pathological conditions such as Alzheimer's

disease.

In order to accurately estimate hippocampal change in pathological

conditions it is critical that reliable and precise estimates be available

for generally healthy populations of different ages. This review

has focused on estimates from longitudinal studies in preference tocross-sectional estimates because cross-sectional estimates can be con-

founded by individual subject baseline volumes. Studies where both

longitudinal and cross-sectional analyses were used indicate that

cross-sectional studies are less able to detect hippocampal volume

change effects (Du et al., 2006; Raz et al., 2005; Ridha et al., 2006 ).

There is now a substantial bodyof researchinvestigatinglongitudinal

hippocampal volume change across multiple domains encompassing

the entire adult lifespan. The domain covering younger individuals fo-

cuses on neurodegenerative conditions that become apparent in adoles-

cenceor young adulthood such as schizophrenia, temporal lobe epilepsy

and mood disorders (Geuze et al., 2005). The studies in these younger

age groups tend to have small sample sizes and small effect sizes

(b0.5% annualised atrophy). A second domain of research focuses on

conditions that become apparent later in life including AD, other formsof dementia, Parkinson's disease, Huntington's disease and other age re-

lated pathologies (Geuze et al., 2005). Hippocampal atrophy rates in-

crease prior to the appearance of AD symptoms and continue to

increase as the disease progresses (Fox et al., 2001; Ridha et al., 2006;

Whitwell et al., 2007). Given that theincidence of dementia is increasing

as populations worldwide age (Fratiglioni et al., 1999), a growing body

of research on dementia with many large samples primarily focused

on people over 50 years of age has emerged. In a review of AD studies,

Barnes et al. (2009) estimated annualised atrophy rates of 4.66% per

year (95% CI 3.92, 5.40) for AD subjects and 1.41% per year (95% CI

0.52, 2.30) for healthy elderly controls. A third domain investigates

changes in healthy ageing in normal individuals. Available evidencesug-

gests that hippocampal volumes change throughout adult life in a non-

linear manner (Raz et al., 2010), with hippocampal volume being

relatively stable in young adulthood. There appears to be a critica

point after 50 years of age when the rate of hippocampal atrophy accel

erates to 0.8–0.9% per yearwithhippocampal volumes decliningsteadil

thereafter with age (Fjell et al., 2013; Schuff et al., 2012).

The aim of this review was rstly to provide age-specic dataon th

rates of hippocampal atrophy across the adult lifespan which are as rep

resentative as possible of the normal population. The second aim was t

investigatethe effects of segmentation techniqueson atrophy measure

ments. Thirdly, we sought to investigate the impact of study design on

measured atrophy rates. It was hypothesised that population studie

would produce higher atrophy rates due to less restrictive health

based exclusion criteria than control groups used in clinical investiga

tions. Our nal goal was to summarise other ndings pertinent to nor

mal ageing such as gender and laterality effects.

Methods

This systematic review and meta-analysis followed the PreferredReporting Items for Systematic Reviews and Meta-Analyses (PRISMA

2009 guidelines without prior publication of the review protoco

(Moher et al., 2009). The literature search was based on pre

determined search terms, inclusion, exclusion and quality criteria tha

included the assessment of bias at the study level. The approach used

for data collection, conrmation and data simplications are fully de

scribed. The risk of bias across studies was assessed and the post ho

analyses are clearly identied.

Search strategy

PUBMED (1950 to February 2014) was searched using the terms

“(hippocampus or hippocamp*) and (longitudinal or atrophy or chang

or volume or volumetry or volumetric) and humans and (magnetic resonance imaging or MRI or neuroimaging)”. All returned titles wer

screened and any non-English, duplicate or clearly irrelevant entrie

were excluded. Next, the remaining record abstracts were reviewed to

identify studies for full text review. Full text and supplementary materi

al of potential studies were retrieved for screening against inclusion an

exclusion criteria. Bibliographies of retrieved reports and previous re

views covering hippocampal atrophy were examined to identify addi

tional studies for inclusion.

Inclusion and exclusion criteria

Published studies were included if they met the following criteria

(1) were an empirical study; (2) measured adult human hippocampa

volume from in-vivo structural MRI images at more than one time

36M.A. Fraser et al. / NeuroImage 112 (2015) 364– 374


3/12

point; and(3) included at least one group of healthy participants, cogni-

tively normal or derived from a population sample. Studies were ex-

cluded if they (a) reported exclusively on clinical treatment groups

(including placebo treatments); (b) were case studies or samples with

less than twenty participants; (c) had an MRI follow-up period of less

than twelve months; (d) the age or gender of the sample could not be

ascertained; or (e) did not provide information to allow calculation of

hippocampal atrophy. Studies meeting the inclusion and exclusion

criteria were assessed for quality using a checklist adapted from previ-ous reviews and the Cochrane collaboration handbook (Anstey et al.,

2011; Harlein et al., 2009; JPT and Green, 2011; Stroup et al., 2000).

Mandatory quality criteria were a prospective design, a dened study

period, specication of population characteristics, standardised data

collection and the absence of signicant bias in the sample selection.

For example, samples that had been constructed to increase the propor-

tion of participants with a family history of AD were excluded.

Data extraction

Data wereextracted bytwo of theauthors(MF and MS) and discrep-

ancies were resolved by consensus. Where a particular sample was re-

ported in multiple studies, the study that best t the selection criteria

and provided information in the format most suitable for meta-

analysis was included and other studies were excluded. Studies that

measured hippocampal volume using manual techniques were

classied as using ‘Manual segmentation’ and studies that used

automated or semi-automated segmentation techniques were classied

as using ‘Automated segmentation’. Follow-up periods were converted

to years and atrophy measures were converted to % per year with

positive atrophy representing a loss of hippocampal tissue. Variance

information was converted to standard deviations (SD). Where

atrophy was not provided, it was calculated using the formula:

Atrophy = ((volume_time1 − volume_time2) / volume_time1) /

(time1 − time2). Total atrophy was calculated by averaging left and

right atrophy weighted by left and right hippocampal volumes. Authors

of the selected studies were contacted via email to gain additional infor-

mation or seek clarication where required. The authors contacted pro-vided additional volume, atrophy or correlation information to enable

studies to be included in the meta-analyses.

Where studies provided separate atrophy rates for age based sub-

sets, the age based rates were included separately. For studies where a

normal sample had been split into sub-samples by category such as

APOE variant and the atrophy information was only available at the

sub-sample level, a single weighted atrophy rate was calculated from

the sub-sample information. Where studies provided separate atrophy

rates for consecutive time points, a single mean atrophy rate was

calculated.

Statistical analysis

R version 3.1.1 (R Core Team, 2014) was used for statistical analysis.

The Amelia II R package version 1.7.2 was used for multiple imputations

(Honaker et al., 2011) and meta-analyses were performed using the

Metafor version 1.9-4 R package (Viechtbauer, 2010).

Missing data

In a few instances (n = 3) where atrophy SDs were missing, it was

possible to impute them from other published information ( JPT and

Green, 2011). In other cases (total hippocampus n = 6, left/right hippo-

campi n = 3),missing SDswere estimatedby multiple imputation using

an expectation-maximisation (EM) bootstrappingmethod with 5 impu-

tations using Amelia II (Thiessen Philbrook et al., 2007).

Meta-analysis

A random-effects model using a restricted maximum likelihood esti-

mator (REML) was used for all meta-analyses. A random effects model

was chosen based on the assumption that included studies are hetero-

geneous because they sample populations with different characteristics

using a range of methodologies and therefore one cannot assume that

there is a single effect size (Borenstein et al., 2011). A random effects

meta-analysis estimates the mean of a distribution of effects ratherthan estimating a unique effect (Borenstein et al., 2011). We assessed

heterogeneity across studies with theQ statistic (with p b .10being sug-

gestive of signicant heterogeneity) and the I2 statistic (values of 25%,

50% and 75% were indicative of low, medium, and high heterogeneity).

Separate meta-analyses were performed for total, left and right hippo-

campal atrophy. Sensitivity analysis was performedto assessthe impact

of including SDs imputed with the multiple imputation procedure.

The impact of age on the observed atrophy rate was explored

through a meta-analysis stratied by age groups. The stratication pro-

cedureconsisted of groupingstudies such that it maximisedthe number

of age groups, containing at least 3 samples, where most of the partici-

pants from those samples would t within the age range of the group.

The distribution of samples in terms of mean age and SD was examined

to identify the number of age based groups that could be practically im-

plemented for total, left and right hippocampal atrophy. For each age

group, the mean and SD of the included samples were used to estimate

the proportion of participants that would be fall below, within and

above the group age range. Sensitivity analysis was used to determine

group boundaries that would optimise the proportion of the sample

participants included within the groups.

Meta-regression was used to investigate the inuence of the moder-

ators of sample type (population vs clinical), segmentation approach

(manual vs automated) and age using linear mixed-effects models

(Borenstein et al., 2011; Viechtbauer, 2010). A number of additional

non-linear meta-regression models using quadratic and cubic terms

were tested post hoc but they provided a poorer t than the linear

models.

Reporting bias

Studies that report signicant results are more likely to be published

than studies resulting in non-signicant outcomes (Song et al., 2010)

and this is known to bias theresults of meta-analytic reviews. It is there-

fore important to formally assess publication bias and interpret results

accordingly. Reporting bias was assessed by visual inspection of funnel

plots which are scatterplots where the effect size is plotted against the

standard error of the effect size. Asymmetry of the funnel plots may

be an indication of reporting bias. The trim and ll method (Duval and

Tweedie, 2000a,b) was used to estimate the number of studies that

may be missing from the meta-analysis and to estimate adjusted effect

sizes.

Results

The search identied 4410 titles, bibliography searches identied

another 11 titles and a previous review (Barnes et al., 2009) yielded

onetitle (Kaye et al., 2005). Of 119 retrieved studies, 58did not meet in-

clusion, exclusion or quality criteria; 14 were not longitudinal, 21 did

not measure hippocampal volume change, 10 had biased samples, 6

had b 20 participants, 3 had no age or gender, 3 had b 12 month follow

up, and 1 was an autopsy study. A further 30 studies were excluded

due to multiple reporting of the same data, 16 of which used samples

from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset.

Of 31 studies that met the inclusion and exclusion criteria, 16 related

to mild cognitive impairment (MCI) or dementia, 8 were ageing or

population studies, 3 related to schizophrenia, 2 to depression, 1 to

Huntington's disease and 1 to total life experience. Fig. 1 shows the

366 M.A. Fraser et al. / NeuroImage 112 (2015) 364– 374


4/12

process used for inclusion in the review. The reviewed studies are

summarised in Table 1. Additional information including imaging pa-

rameters and segmentation protocols are described in Supplementary

tables S1–S4.

Quality ratings of included studies met the following criteria: deni-

tion of exposure variable and outcome, prospective design, specication

of population characteristics, description of study period, description of

the sampling procedure, standardised and described data collection,

multivariate statistics described, and reproducibility. Ten studies hadmore than 100 participants across all groups. Dropout rates varied

with 16 studies reporting a dropout rate of less than 20%, 9 studies

reporting greater than 20%, 1 study did not include dropout informa-

tion, 4 studies selected participants that had two MRI scans from larger

prospective datasets and 1 study invited participants from existing

studies to have a follow-up scan.

Manual segmentation was used in 19 studies. The anatomical deni-

tions used in manually segmented studies were generally consistent in

including the dentate gyrus, hippocampus proper (CA1 through CA4),

subiculum, mbria and the alveus. All manually segmented studies in-

cluded thehead, thebody and the tail up to the crus of thefornix except

for Kaye et al. (2005) who only measured the hippocampus body and

Whitworth et al. (2005)who included some amygdala tissue in the seg-

mentation. Twelve studies used a range of different automated or semi-

automated segmentation approaches.The delineation of the hippocam

pus in most of the automated studies differed from the manually seg

mented studies by including the tail past the crus of the fornix and

excluding the mbria and alveus. A number of studies tested for gende

effects and two found increased atrophy in males; Cherbuin et a

(2012) found greater hippocampal atrophy and Driscoll et al. (2009

found greater age related temporal lobe atrophy.

Meta-analysis

Of the 31 studies reviewed, 28 were included in the meta-analysis

Two all-male studies (MacLullich et al., 2012; Whitworth et al., 2005

were excluded to avoid gender bias and Callisaya et al. (2013), with

an annualised atrophy rate of 9.98%, was identied as an outlier durin

meta-analysis and excluded. The remaining 28 studies covered 3422

participants of whom 1469 (44.65%) were male.

The 28 studies provided 35 samples with estimates for total hippo

campal atrophy. Visual inspection of the distribution of the samples

mean ages suggested that three age groups; young, young–old and

old–old, could be implemented. Sensitivity analysis was used to choos

the optimum break points (50 versus 55 years and 70 versus 75 years

between the age groups. The analysis yielded the following three ag

groups; 1) less than 55 years represented 92% of 413 participants in

12 samples; 55 years to less than 70 years represented 87% of 426 par

ticipants in 7 samples; and 70 years and over represented 78% of 2583

participants in 16 samples. With fewer studies measuring left and

right hippocampal atrophy, the distribution of sample mean ages sug

gested only two age groups. Sensitivity analysis was used to choos

the optimum break point (50 versus 55 years) between the groups

The analyses yielded two age groups;1) less than 55 years representin

88.0% of 225 participants in 4 samples and 2) 55 years and ove

representing 100% of 917 participants in 7 samples. Excluding the mul

tiple imputed samples did not signicantly alter the atrophy estimates

The results of the meta-analyses are shown in Table 2. Forest plots wit

age based subsets for total, left and right hippocampal atrophy are

shown in Figs. 2–4.

Signicant heterogeneity was found in all meta-analyses performe

with p b 0.0001for tests of homogeneity in effects. Theproportion of observed variance between studies (I2) that is real (i.e. not related to ran

dom error) was high in all but one of the age groups with I 2 rangin

from 68.75% to 99.99% and the proportion of heterogeneity tended to

be higher in older age groups. A mixed effects model using moderator

of age, segmentation technique and sample type indicated that age an

segmentation type were signicant moderators of annualised atroph

and sample type was not a signicant moderator. A second model lim

ited to the signicant moderators estimated that age and segmentatio

typeaccounted for 42.78% of the heterogeneity in total hippocampal at

rophy (Table 3). The test for residual heterogeneity was signican

Q(32) = 1976.57, p b 0.0001, indicating that other moderators ar

inuencing the atrophy rate. The impact of segmentation approach

was investigated post hoc using separate meta-regression models fo

manualand automatedstudies (Table 3, Models 3–4). Thedifferent predicted atrophyrates for manual and automated segmentation techniqu

by age are plotted in Fig. 5.

Reporting bias

The funnel plot for studies reporting on total hippocampal atroph

(Fig. 6) is reasonably symmetrical and no missing studies were identi

ed using the trim and ll method, suggesting the absence of publica

tion bias (Duval and Tweedie, 2000a,b). The large number of th

points falling outside the funnel in Fig. 6 islikely to be due to the signif

icant heterogeneity between studies. In the absence of heterogeneity

95% of the studies would be expected to fall within the funnel area

The funnel plots for studies reporting left and right hippocampal atro

phy (Figs. 7–

8) were less symmetrical and the trim and ll method

Fig. 1. Screening and selection process for studies included in the meta-analysis.



5/12

Table 1

Studies included in the review.

Study Group n Male % Age mean

(SD)

Time

(SD)

Segmentation Atrophy % per year

Total Left Right

Barnes et al. (2008) NC 20 50 69 (7) 1 (01) Manual 0.28 (0.93) 0.02 (1.25) 0.52 (1.37)

Callisaya et al. (2013) Population 225 56.4 71.4 (6.8) 2.55 (0.41) Manual 9.86 (4.17)a

Cherbuin et al. (2012) Population 249 57 62.6 (1.4) 4 (0.21) Manual 2.03 (0.033) 2.56 (0.034)a 1.46 (0.036)a

Crivello et al. (2010) Population 1186 36.7 72.3 (3.9) 4 (−) Automated 1.204 (2.5402)b

den Heijer et al. (2010) Population 244 49 73.5 (7.9) 3.4 (0.3) Automated 0.51 (0.43) 0.52 (0.60) 0.51 (0.88)

Driscoll et al. (2009) Population 120 60.8 70.6 (6.1) 6.02 (2.91) Automated 0.32 (0.049)a

Du et al. (2004) CN 25 4 4 76 (7.8) 2 (0.7) Automated 0.8 (1.7) 1 (2.6) 0.6 (2.5)

Frodl et al. (2008) NC 30 36.7 43.6 (13.1) 3 (0) Manual −0.20c (1.65) −0.31 (2.15) −0.09 (2.36)

Jack et al. (1998) NC 24 33.3 81.0 (3.8) 1.96 (0.75) Manual 1.55 (1.38)

Jack et al. (2004)d CN-stable 40 42.5 79 (−) 4.3 (−) (2.5–5.2)e Manual 1.4 (0.7)f

Kaye et al. (2005) CN 88 47.7 83.0 (7.0) 2.04 (1.42) Manual 2.2 (6.0)

Koolschijn et al. (2010) NC 113 67.3 35.4 (12.3) 4.94 (0.32) Manual 0.8043 (.0267)a 0.8028 (.0285)a 0.8054 (.0285)a

Liu et al. (2003) 14–34 44 59.1 24.5 (6.6) 3.57 (0.13) Manual 0.11 ( 3. 34)

35 to 54 37 45.9 44.5 (5.7) 3.53 (0.08) 0 ( 2. 31)

Over 54 9 66.7 67.9 (6.4) 3.53 (0.09) 0.64 ( 2.78)

MacLullich et al. (2012) Healthy 41 100 67.3 (1.3) 6 (−) Manual −0.16 (−) −0.27 (1.94)g −0.04 (1.90)g

Majid et al. (2011) NC 22 31.8 40.1 (12.2) 1 (0.1) Automated 0.02 (0.72)

Mungas et al. (2005) Normal 58 46.6 74.1 (6.7) 3.4 (1.4) Automated 1.1 (1.4)

Raz et al. (2005) Young b50 32 – 39.4 (8.3) 5.27 (0.3) Manual 0.48 (0.83)a

Old 50+ 40 – 63.1(7.0) 1.04 (0.797)a

Raz et al. 2010 Healthy 30 46.7 63.1 (7.0) 2.61 Manual 2.18 ( 2.46 )

Ridha et al. (2006) Controls 25 36 46.5 (10.2) 1.5 (0.8) Manual 0.31 (1.25)

Samieri et al. (2012) Population 281 42.3 72.3 (3.8) 4 (−) Automated 0.9455 (0.6841)a 1.0 (0.8) 0.9 (0.8)Scahill et al. (2003) 30–39 years 8 50 36.1 (2.5) 1.58 (1.19) Manual 0.75 (1.25)

40–49 years 10 50 45.6 (2.9) 1.83 (0.87) 0.5 (0.375)

50–59 years 10 50 53.9 (3.5) 1.91 (1.11) 1.05 (0.475)

60–69 years 6 50 62.7 (2.3) 2.07 (1.21) 0.875 (0.5875)

70–84 years 5 25 76.8 (5.5) 0.98 (0.42) 1.9375 (1.7375)

Schott et al. (2003) Controls 20 50 45.8 (6.8) 1.41 (0.8) Manual −0.12c (1.83) −0 .45 ( 1.63 ) 0 .2 1 ( 3.00 )

Schott et al. (2010) Controls 199 53.3 76 (5.1) 1 (−) Automated 1.01 (1.72)

Steffens et al. (2011) Healthy 72 19.4 69.4 (6.2) 2 (−) Automated −0.84 (5.9)h,a −1.07 (7.19)h −0.63 (6.28)h

Stoub et al. (2010) NCI-S 26 19.2 78 (6) 5 Manual 1.4188 (0.2444)a

Valenzuela et al. (2008) Healthy 37 43.2 70.3 (5.8) 3 (−) Manual 1.98 (3.92)b

Wang et al. (2003) CN 26 46.2 73 (7) 2.2 (−) 1.0–2.6e Automated 2.34 (1.853) 1.82 ( 2.04) 2.50 ( 2.03)

Wang et al. (2008) NC 62 54.8 36.2 (14.5) 2.24 (5.8) Automated 0.105c (1.84) 0.26 ( 2.15) −0.03 ( 2.50)

Wang et al. (2009) NC 20 55 75.1 (3.7) 1.88 (−) 0.89–2.9e Manual 1.0 (0.07)

Whitwell et al. (2012)i Po pulation 204 54.4 78.4 (5.0)a 1.25 (−) Automated 0.50 (2.22)a

Whitworth et al. (2005) NC 20 100 31.5 (4.9) j 3.7 (1.63) Manual 1.25 (−) 1.95 (3.12) 0.53 (3.21)

NC = normal controls; CN = cognitively normal; CN-stable = CN that does not progress to MCI or AD; NCI-S = no cognitive impairment at baseline, stable.

Multiply imputed SDs are shown in italics.a Personal communication with author.b Values pooled from subsets.c Calculated from left and right atrophy.d CN split into subsets of stable & converters — only stable subset included in analysis.e Median plus range.f Source Barnes et al. (2009).g SD imputed using p-value.h Atrophy calculated from volume change.i Included MCSA sample only. j Age at follow-up.

Table 2

Meta-analysis estimates of total, left and right hippocampal atrophy rates with age based subsets.

Description k n Age Atrophy %/yr s.e. 95% CI Qp T2 T I2

Total hippocampus 35 3422 68.59 0.85 0.11 0.63 1.07 b .0001 0.36 0.6 99.96

Young: b55 years 12 413 39.53 0.38 0.12 0.14 0.62 b .0001 0.12 0.34 85.45

Old: 55+ years 23 3009 72.58 1.12 0.13 0.86 1.38 b .0001 0.31 0.56 99.92

55 to b70 years 7 426 64.24 0.98 0.37 0.27 1.70 b .0001 0.76 0.87 96.60

70+ years 16 2583 73.95 1.12 0.13 0.86 1.38 b .0001 0.22 0.47 98.75

Left hippocampus 11 1142 64.34 0.64 0.30 0.04 1.23 b.0001 0.89 0.94 99.99

b55 years 4 225 40.06 0.16 0.31 −0.45 0.76 b.0001 0.30 0.55 84.45

N55 years 7 917 70.29 0.94 0.41 0.14 1.75 b.0001 1.05 1.02 99.75

Right hippocampus 11 1142 64.34 0.70 0.23 0.25 1.15 b.0001 0.45 0.67 99.99

b55 years 4 225 40.06 0.33 0.28 −0.21 0.87 b.0001 0.19 0.43 68.75

N55 years 7 917 70.29 0.92 0.31 0.31 1.52 b.0001 0.55 0.74 99.30

k = numberof samplesor sub-samplesincluded in analysis; s.e.= standard error; Qp = p-valuefor thesignicance testof theQ statistic;T2 = heterogeneity = estimated variance of true

effects; T = estimated standard deviation of true effects; I2

= proportion of observed variance (heterogeneity) that is real.



6/12

estimated onemissing study for theleft hippocampus andthree missing

for the right hippocampus, inclusion of the missing studies produced

adjusted estimates for left hippocampal atrophy of 0.74% per year

(95% CI 0.15, 1.33) and right hippocampal atrophy of 0.96% per year

(95% CI 0.50, 1.42). The adjusted estimates should be treated with cau-

tion for two reasons. Firstly theestimated missing studies hadvery large

effect sizes and are therefore unlikely to result from reporting bias, and

secondly, the estimates produced by the trim andll method have been

shown to be unreliable in the presence of signicant heterogeneity asobserved in the present results (Peters et al., 2007; Terrin et al., 2003).

Discussion

The aim of this review was to estimate hippocampal atrophy rate

across the adult lifespan in cognitively normal individuals and to inves

tigate theimpactof age, sample type andsegmentation approach on ob

served atrophy rates.

Overall, the estimated rate of total hippocampal atrophy across al

studies of 0.85% per year was consistent with previous longitudina

ndings and higher than the atrophy rates of 0.28–0.35% per year (Raet al., 2005; Raz et al., 2004b; Scahill et al., 2003) reported in cross

Fig. 2. Random effects model of total hippocampal atrophy with age based subsets. Studies are ordered by mean age.

Fig. 3. Random effects model of left hippocampal atrophy with age based subsets. Studies are ordered by mean age.



7/12

sectional studies. By bringing together the results for control partici-

pants in a range of research domains we were able to show that there

isa small yet signicant rate of atrophy from young adulthoodto middle

age of 0.38% per year. In contrast, individual studies that have measured

hippocampal change in younger age groups have provided equivocal

evidence of atrophy with many nding non-signicant hippocampal

volume changes, likely due to insuf cient power to detect small effects.

Hippocampal atrophy rates increase with age (Du et al., 2006) and

this meta-analysis further demonstrates that the most signicant atro-

phy occurs from midlife onwards. The hippocampal atrophy rate in-creased to 0.98% per year for studies with a mean age of 55 to less

than 70 years.The estimate from this transition group was theleast pre-

cise estimate dueto the smaller number of studies included. The rate of

atrophy further increasedto 1.12% peryear in the 70 years andolder age

group. While theestimates forthe older agegroupswere lower than the

rate of 1.41% per year estimated in a previous review, the difference was

not signicant (Barnes et al., 2009). The pattern of atrophy change with

age is consistentwith previous cross-sectional and longitudinal ndings

reporting a non-linear trajectory in hippocampal ageing (Fjell et al.,

2013; Raz et al., 2010; Schuff et al., 2012), but with few samples cover-

ing middle age, it was not possible to model the critical pointthat is be-

lieved to occur after the age of 50 years (Fjell et al., 2013). More

longitudinal research covering this critical time should be undertaken.

Laterality effects

Theestimated atrophy rates for the left and right hippocampus were

consistent with total hippocampal atrophy rates. There was little evi-

dence of laterality differences in the atrophy estimates produced by

the meta-analysis. This nding is of particular interest because a

Fig. 4. Random effects model of right hippocampal atrophy with age based subsets. Studies are ordered by mean age.

Table 3

Mixed effects models of hippocampal atrophy rates. Model 1: age, segmentation technique and sample type; Model 2: age and segmentation technique; Model 3: age effect on studies

using manual segmentation; Model 4: age effect on studies using automated segmentation.

k Coef s.e. z p 95% CI τ r2

Model 1 35

Intercept −

0.5720 0.3699 −

1.5466 0.1220 −

1.2970 0.1529 0.4558 41.84Age 0.0256 0.0061 4.2053 b0.0001 0.0136 0.0375

Segmentation −0.5222 0.2075 −2.5165 0.0119 −0.9289 −0.1155

Sample type 0.1878 0.2540 0.7394 0.4597 −0.3100 0.6857

Model 2 35

Intercept −0.6026 0.365 −1.6508 0.0988 −1.318 0.1129 0.4521 42.78

Age 0.0263 0.006 4.414 b .0001 0.0146 0.0379

Segmentation −0.4656 0.1917 −2.429 0.0151 −0.8413 −0.0899

Model 3 23

Intercept −0.7237 0.4368 −1.6567 0.0976 −1.5798 0.1325 0.4542 45.26

Age 0.0284 0.0072 3.9188 b .0001 0.0142 0.0425

Model 4 12

Intercept −0.7727 0.7722 −1.0006 0.3170 −2.2862 0.7408 0.4827 29.98

Age 0.0219 0.0112 1.9651 0.0494 0.0001 0.0438

k = number of samples or sub-samples included in analysis; s.e. = standard error; τ = standard deviation of true effects; r2 = proportion of observed dispersion accounted for by the

model.



8/12

number of studies have suggested earlier and faster atrophy in the left

hippocampus. Consequently if this effect is not present in generally

healthy individuals it may be more indicative of developing neurode-

generative pathology which has been reported to be asymmetrical

(Cherbuin et al., 2010; Thompson et al., 2003).

Moderators & heterogeneity

There was considerable heterogeneity between studies and the

moderators of age and segmentation technique accounted for just

under half of the heterogeneity. Unsurprisingly, age had the largest ef

fect, accounting for most of the explained heterogeneity. Given tha

many studies had wide age ranges, exceeding 25 years in some cases

it is possible that age may have a greater moderating effect than quan

tied by the meta-regression. Another salient feature of this meta

analysis is that heterogeneity between studies was higher in studie

with a mean age greater than 55 years. This is probably due to chroni

disease and non-clinical brain changes which become more prevalen

in ageing. However, more targeted research is required to understan

the factors driving increased variability in older samples.

The other signicant moderator of heterogeneity identied was th

segmentation technique used to measure hippocampal volume. Th

meta-regression suggested that automated segmentation results i

lower atrophy rate estimates. It is possible that automated approachemay include some non-hippocampaltissue that has a lower rate of atro

phy than hippocampal tissue (Wenger et al., 2014). Indeed, Cherbui

et al. (2009) found that the hippocampal segmentation implemente

in Freesurfer produced signicantly larger volumes compared t

Fig. 5. Meta-regression of atrophy rate and mean age. The size of circles is proportional to

the weight given to the study. Larger studies and more precise studies are given more

weight in the meta-analysis. Magenta circles represent studies using manual segmenta-

tion and blue circles represent studies using automated segmentation. The magenta line

is the predicted mean atrophy rate change with age with manual segmentation

(Model 3) and the blue line represents the predicted mean atrophy rate with age for au-

tomated segmentation (Model 4).

Fig. 6. Funnel plot of total hippocampal atrophy using trim and ll method. Filled circles

represent studies included in the meta-analysis. Open circles represent possible missing

studies.

Fig. 7. Funnel plot of left hippocampal atrophy using trim and ll method. Filled circle

represent studies included in the meta-analysis. Open circles represent possible missin

studies.

Fig. 8. Funnel plot of right hippocampal atrophy using trim and ll method. Filled circle

represent studies included in the meta-analysis. Open circles represent possible missin

studies.



9/12

manual segmentation of the same images. This explanation would also

be consistentwith ndings by Mulder et al., (2014)indicating that man-

ual segmentation produced higher atrophy rates than Freesurfer

(Reuter et al., 2012) or FIRST (Patenaude et al., 2011). Differential atro-

phy rates between the hippocampal head and tail could also contribute

to thedifferent atrophy rates between manually segmentedstudies (ex-

cluding thetail) and the studies using automated segmentation(includ-

ingthe tail) consistent with the Wang et al. (2003)ndings that atrophy

was mostly con

ned to the head of the hippocampus and subiculum innon-demented controls. One possible implication of these results is that

specic atrophy benchmarks may be required for segmentation tech-

niques relying on substantially different methods, protocols or

landmarks.

Thehypothesis that population studiesproduce higheratrophy rates

due to less restrictive exclusion criteria was not supported. This may be

because the exclusion criteria for the population samples were similar

to the other studies in excluding participants with neurological and se-

vere chronic conditions.

Reporting bias

Reporting bias was not expected given that this review utilised sam-

ples where the decision to publish or not publish was unlikely to be in

u-enced by the atrophy rate of control groups. There was no evidence of

reporting bias for total hippocampal atrophy. However, there wasan indi-

cation of missing studies reporting left and right hippocampal atrophy. If

these missing studies had non-signicant effect sizes, it may be an indica-

tion of reporting bias. However, in this case all three missing studies had

signicant effect sizes. While the adjusted estimates for left and right at-

rophy, after inclusion of the estimated missing studies, did not represent

a signicant change, they didmovethe estimates closer to that of the total

hippocampal atrophy.

Dropouts

In longitudinal studies carriedout over many yearsthere is likely to be

a high dropout rate, especially when participants are over 60 years old.Since drop out tends to be highest in thefrail and sick, it could bias the re-

sults of studies examined. Most of the studies reported the characteristics

of dropouts in comparison to those that didnot drop out. In older cohorts,

the dropouts tended to be older and less healthy than the participants

who were not lost to follow-up, consequently the atrophy rates in the

older cohorts may be understated.

Gender

Hippocampal atrophy was not separately measured in males and fe-

males in any of the studies. Therefore it was not possible to perform any

gender based meta-analyses. However, a number of studies controlled

or testedforgendereffects, with onestudy reporting greater hippocampal

atrophyrates in males while a secondreported higher temporal lobe atro-phy in males(Cherbuin et al., 2012; Driscoll et al., 2009). In addition, one

of the male-only studies, Whitworth et al. (2005), found annualised atro-

phy of 1.25% per year in young men, which is somewhat higher than the

meta-analysis estimate, but in line with the limited information from the

few studies investigating gender effects in hippocampal atrophy. Signi-

cant negative correlations have been found between hippocampal vol-

ume and age in men, but not in women, from around 20 to 46 years of

age (Pruessner et al., 2001; Raz et al., 2004a). Eberling et al. (2003) sug-

gested that oestrogen may protect against age related hippocampal atro-

phy. Given thesmall sample sizes of many MRI studies it is not surprising

thatfew studies measure hippocampal atrophyseparatelyin each gender.

The absence of studies that investigate gender effects represent a poten-

tial gap in the current research literature and needs to be investigated in

detail.

Limitations of the study

This review took a novel approach of utilising control samples from a

range of research areas including schizophrenia, AD and ageing to enable

the analysis of studies covering the entire adult life span. The potential

limitations of this approach are fourfold. Firstly, combining samples

from different research domains mayhave ledto increasedheterogeneity.

Secondly, in some studies the controlsamples were not as thoroughly de-

scribed as the observational treatment samples and this could have re-duced the effectiveness of the screening process. Thirdly, the wide age

ranges of many studies limited the number of age groups that could be

used in the meta-analysis and this limited precision of the estimates.

More studies with narrow age ranges are required to enable greater pre-

cision in estimates of age effects. Finally, it is possible that preclinical neu-

rodegenerative processes have contributed to the atrophy rates reported

in this study for the older age groups.

Conclusions

To our knowledge this is the rst meta-analysis of hippocampal atro-

phy, investigated in studies employing a longitudinal design, across the

adult lifespan. Hippocampal volumes remain relatively stable with low

levels of atrophy up to the middle of adulthood from which time

atrophy progressively increases as age increases. The heterogeneity be-

tween studies also increases in studies surveying older individuals.

More targeted research is required to understand the factors that drive

this variability. Finally, manual segmentation studies produced higher at-

rophy estimates compared to automated and semi-automated studies. It

is unclear whether the difference relates to the segmentation technique

or the hippocampal boundaries used. The implication of this nding is

that separate benchmarks may need to be used when assessing ndings

based on differing segmentation approaches.

Acknowledgments

This study was funded by Australian Research Council project grant

number 120101705. The funding sources were not involved in the

design, collection, analysis or interpretation of data; or in the writingof the report or the decision to submit.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.

doi.org/10.1016/j.neuroimage.2015.03.035.

References

Anstey, K., Cherbuin, N., Budge, M., Young, J.,2011. Body mass index in midlifeand late life asa risk factor for dementia: a meta-analysis of prospective studies. Obes. Rev. 12,e426–e437.

Arnone, D., McKie, S., Elliott, R., Juhasz, G., Thomas, E.J., Downey, D., Williams, S., Deakin, J.F., Anderson, I.M., 2012. State-dependent changes in hippocampal grey matter indepression. Mol. Psychiatry 18, 1265–1272.

Barnes, J., Scahill, R.I., Frost, C., Schott, J.M., Rossor, M.N., Fox, N.C., 2008. Increased hippocam-pal atrophy rates in AD over 6 months using serial MR imaging. Neurobiol. Aging 29,1199–1203.

Barnes, J.,Bartlett, J.W.,van de Pol, L.A.,Loy, C.T., Scahill, R.I., Frost, C.,Thompson, P.,Fox, N.C.,2009. A meta-analysis of hippocampal atrophy rates in Alzheimer's disease. Neurobiol.Aging 30, 1711–1723.

Borenstein, M., Hedges, L.V., Higgins, J.P., Rothstein, H.R., 2011. Introduction to Meta-analysis. John Wiley & Sons.

Callisaya, M.L., Beare, R., Phan, T.G., Blizzard, L., Thrift, A.G., Chen, J., Srikanth, V.K., 2013.Brain structural change and gait decline: a longitudinal population-based study.

J. Am. Geriatr. Soc. 61, 1074–1079.Camicioli, R., Moore, M.M., Kinney, A., Corbridge, E., Glassberg, K., Kaye, J.A., 2003.

Parkinson'sdisease is associatedwith hippocampal atrophy. Mov. Disord. 18, 784–790.Cherbuin, N., Anstey, K.J., Réglade-Meslin, C., Sachdev, P.S., 2009. In vivo hippocampal mea-

surement and memory: a comparison of manual tracing and automated segmentationin a large community-based sample. PLoS One 4.

Cherbuin, N., Réglade-Meslin, C., Kumar, R., Sachdev,P., Anstey, K.J., 2010. Mildcognitive dis-orders are associated with different patterns of brain asymmetry thannormal aging: the

PATH through life study. Front. Psychiatry 1.


http://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0025http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0025http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0035http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0035http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0035http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0045http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0040http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0035http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0030http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0025http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0025http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0015http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0020http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0320http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0005http://dx.doi.org/10.1016/j.neuroimage.2015.03.035http://dx.doi.org/10.1016/j.neuroimage.2015.03.035


10/12

Cherbuin, N., Sachdev, P., Anstey, K.J., 2012. Higher normal fasting plasmaglucose is associated with hippocampal atrophy: the PATH study. Neurology 79,1019–1026.

Crivello, F., Lemaitre, H., Dufouil, C., Grassiot, B., D elcroix, N., Tzourio-Mazoyer, N.,Tzourio, C., Mazoyer, B., 2010. Effects of ApoE-epsilon4 allele load and age onthe rates of grey matter and hippocampal volumes loss in a longitudinal co-hort of 1186 healthy elderly persons. Neuroimage 53, 1064–1069.

den Heijer, T., van der Lijn, F., Koudstaal, P.J., Hofman, A., van der Lugt, A., Krestin,G.P., Niessen, W.J., Breteler, M.M., 2010. A 10-year follow-up of hippocampalvolume on magnetic resonance imaging in early dementia and cognitive de-cline. Brain 133, 1163–1172.

Driscoll,I., Davatzikos,C., An,Y., Wu, X., Shen, D.,Kraut, M.,Resnick, S.M., 2009. Longitudinalpattern of regional brain volume change differentiates normal aging from MCI. Neurol-ogy 72, 1906–1913.

Du, A.T., Schuff, N., Kramer, J.H., Ganzer, S., Zhu, X.P., Jagust, W.J., Miller, B.L., Reed,B.R., Mungas, D., Yaffe, K., Chui, H.C., Weiner, M.W., 2004. Higher atrophy rateof entorhinal cortex than hippocampus in AD. Neurology 62, 422–427.

Du, A.T., Schuff, N., Chao, L.L., Kornak, J., Jagust, W.J., Kramer, J.H., Reed, B.R., Miller, B.L.,Norman, D., Chui, H.C., Weiner, M.W., 2006. Age effects on atrophy rates of entorhinalcortex and hippocampus. Neurobiol. Aging 27, 733–740.

Duval, S., Tweedie, R., 2000a. A nonparametric “trimand ll” method of accounting for pub-lication bias in meta-analysis. J. Am. Stat. Assoc. 95, 89–98.

Duval, S., Tweedie,R., 2000b. Trim andll:a simplefunnel plot-based method of testing andadjusting for publication bias in meta-analysis. Biometrics 56, 455–463.

Eberling, J., Wu, C., Haan, M., Mungas, D., Buonocore, M., Jagust, W., 2003. Prelim-inary evidence that estrogen protects against age-related hippocampal atro-phy. Neurobiol. Aging 24, 725–732.

Fjell, A.M., Westlye, L.T., Grydeland, H., Amlien, I., Espeseth, T., Reinvang, I., Raz, N., Holland,D., Dale, A.M., Walhovd, K.B., 2013. Critical ages in thelifecourse of theadult brain:non-linear subcortical aging. Neurobiol. Aging 34, 2239–2247.

Fox, N.C., Crum, W.R., Scahill, R.I., Stevens, J.M., Janssen, J.C., 2001. Imaging of onset and pro-gression of Alzheimer's disease with voxel-compression mappingof serial magneticres-onance images. Lancet 358, 201–205.

Fratiglioni, L., De Ronchi, D., Agüero-Torres, H., 1999. Worldwide prevalence and inci-dence of dementia. Drugs Aging 15, 365–375.

Frodl, T., Jager, M., Smajstrlova, I., Born, C., Bottlender, R., Palladino, T., Reiser, M.,Moller, H.J., Meisenzahl, E.M., 2008. Effect of hippocampal and amygdala vol-umes on clinical outcomes in major depression: a 3-year prospective magneticresonance imaging study. J. Psychiatry Neurosci. 33, 423–430.

Geuze, E., Vermetten, E., Bremner, J., 2005. MR-based in vivo hippocampal volu-metrics: 2. Findings in neuropsychiatric disorders. Mol. Psychiatry 10,160–184.

Harlein, J., Dassen, T., Halfens, R.J., Heinze, C., 2009. Fall risk factors in older people withdementia or cognitive impairment: a systematic review. J. Adv. Nurs. 65, 922–933.

Honaker, J., King, G., Blackwell, M., 2011. Amelia II: a program for missing data. J. Stat.Softw.45, 1–47.

Jack Jr., C.R., Petersen, R.C., Xu, Y., O'Brien, P.C., Smith, G.E., Ivnik, R.J., Tangalos, E.G., Kokmen,E., 1998. Rate of medial temporal lobe atrophy in typical aging and Alzheimer's disease.Neurology 51, 993–999.

Jack Jr., C.R., Petersen, R.C., Xu, Y., O'Brien, P.C., Smith, G.E., Ivnik, R.J., Boeve, B.F., Tangalos,E.G., Kokmen, E., 2000. Rates of hippocampal atrophy correlate with change in clinicalstatus in aging and AD. Neurology 55, 484–489.

Jack Jr.,C.R., Shiung, M.M., Gunter, J.L., O'Brien, P.C., Weigand,S.D., Knopman, D.S., Boeve, B.F.,Ivnik, R.J., Smith, G.E., Cha, R.H., Tangalos, E.G.,Petersen, R.C., 2004. Comparison of differ-ent MRI brain atrophy rate measures with clinical disease progression in AD. Neurology62, 591–600.

JPT, C.H.H., Green, S., 2011. CochraneHandbook for Systematic Reviews of Interventions Ver-sion 5.1.0. The Cochrane Collaboration (updated March 2011).

Kaye,J.A.,Moore, M.M.,Dame,A., Quinn,J., Camicioli, R.,Howieson, D.,Corbridge,E., Care,B.,Nesbit, G., Sexton, G., 2005. Asynchronousregionalbrain volume losses in presymptom-atic to moderate AD. J. Alzheimers Dis. 8, 51–56.

Koolschijn, P.C., van Haren, N.E., Cahn, W., Schnack, H.G., Janssen, J., Klumpers, F., Hulshoff Pol, H.E., Kahn, R.S., 2010. Hippocampal volume change in schizophrenia. J. Clin.Psychiatry 71, 737–744.

Liu, R.S.,Lemieux, L.,Bell, G.,Bartlett, P.,Sander,J., Sisodiya,S., Shorvon,S., Duncan, J.,2001. Alongitudinal quantitativeMRI study of community-based patients withchronicepilepsyand newly diagnosed seizures: methodology and preliminaryndings. Neuroimage 14,

231–

243.Liu, R.S., Lemieux, L., Bell, G.S., Sisodiya, S.M., Shorvon, S.D., Sander, J.W., Duncan, J.S., 2003. A

longitudinal study of brain morphometrics using quantitative magnetic resonance im-aging and difference image analysis. Neuroimage 20, 22–33.

MacLullich, A.M., Ferguson, K.J., Reid, L.M., Deary, I.J., Starr, J.M., Wardlaw, J.M.,Walker, B.R., Andrew, R., Seckl, J.R., 2012. 11beta-hydroxysteroid dehydroge-nase type 1, brain atrophy and cognitive decline. Neurobiol. Aging 33 (207),e201–208.

Majid, D.S., Aron, A.R., Thompson, W., Sheldon, S., Hamza, S., Stoffers, D., Holland, D.,Goldstein, J., Corey-Bloom, J., Dale, A.M., 2011. Basal ganglia atrophy in prodromalHuntington's disease is detectable over one year using automated segmentation. Mov.Disord. 26, 2544–2551.

Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., 2009. Preferred reporting items forsystematic reviews and meta-analyses: the PRISMA statement. Ann. Intern. Med. 151,264–269.

Mulder, E.R., de Jong, R.A., Knol, D.L., van Schijndel, R.A., Cover, K.S., Visser, P.J., Barkhof, F.,Vrenken,H., 2014. Hippocampal volume change measurement: quantitative assessmentof the reproducibility of expert manual outlining and the automated methodsFreeSurfer and FIRST. Neuroimage 92, 169–181.

Mungas, D., Harvey, D., Reed, B.R., Jagust, W.J., DeCarli, C., Beckett, L., Mack, W.J., Krame J.H., Weiner, M.W., Schuff, N., Chui, H.C., 2005. Longitudinal volumetric MRI changand rate of cognitive decline. Neurology 65, 565–571.

Patenaude, B., Smith, S.M., Kennedy, D.N., Jenkinson, M., 2011. A Bayesian modelof shapand appearance for subcortical brain segmentation. Neuroimage 56, 907–922.

Peters, J.L., Sutton, A.J., Jones, D.R., Abrams, K.R., Rushton, L., 2007. Performance othe trim and ll method in the presence of publication bias and betweenstudy heterogeneity. Stat. Med. 26, 4544–4562.

Pruessner, J., Collins, D., Pruessner, M., Evans, A., 2001. Age and gender predict volume decline in the anterior and posterior hippocampus in early adulthood. J. Neurosci. 21194–200.

R. Core Team, 2014. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Raz, N., Gunning-Dixon, F., Head, D., Rodrigue, K.M., Williamson, A., Acker, J.D

2004a. Aging, sexual dimorphism, and hemispheric asymmetry of the cerebracortex: replicability of regional differences in volume. Neurobiol. Aging 25377–396.

Raz, N., Rodrigue, K.M., Head, D., Kennedy, K.M., Acker, J.D., 2004b. Differential aging othe medial temporal lobe: a study of a ve-year change. Neurology 62, 433–438.

Raz, N., Lindenberger, U., Rodrigue, K.M., Kennedy, K.M., Head, D., Williamson, A., DahleC., Gerstorf, D., Acker, J.D., 2005. Regional brain changes in aging healthy adults: general trends, individual differences and modiers. Cereb. Cortex 15, 1676–1689.

Raz, N., Ghisletta, P., Rodrigue, K.M., Kennedy, K.M., Lindenberger, U., 2010. Trajectories obrain aging in middle-aged and older adults: regional and individual differenceNeuroimage 51, 501–511.

Reuter, M., Schmansky, N.J., Rosas, D.H., Fischl, B., 2012. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 61, 1402–1418.

Ridha, B.H., Barnes, J.,Bartlett, J.W., Godbolt,A., Pepple, T., Rossor, M.N., Fox,N.C., 2006. Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study. LanceNeurol. 5, 828–834.

Samieri, C., Maillard, P., Crivello, F., Proust-Lima, C., Peuchant, E., Helmer, C., Amieva, HAllard, M., Dartigues, J.F., Cunnane, S.C., Mazoyer, B.M., Barberger-Gateau, P., 2012. Plasma long-chain omega-3 fatty acids and atrophy of the medial temporal lobe. Neurolog79, 642–650.

Scahill, R.I., Frost, C., Jenkins, R., Whitwell, J.L., Rossor, M.N., Fox, N.C., 2003. A longitudinastudy of brain volume changes in normal aging using serial registered magnetic resonance imaging. Arch. Neurol. 60, 989–994.

Schott, J.M., Fox, N.C., Frost, C., S cahill, R.I., Janssen, J.C., Chan, D., Jenkins, R., Rossor, M.N2003. Assessing the onset of structural change in familial Alzheimer's disease. AnnNeurol. 53, 181–188.

Schott, J.M., Bartlett, J.W., Barnes, J., Leung, K.K., Ourselin, S., Fox,N.C., 2010. Reducedsample sizes for atrophy outcomes in Alzheimer's disease trials: baseline adjustmentNeurobiol. Aging 31, 1452–1462 (1462 e1451-1452).

Schuff, N., Tosun, D., Insel, P.S., Chiang, G.C., Truran, D., Aisen, P.S., Jack Jr., C.R., WeinerM.W., 2012. Nonlinear time course of brain volume loss in cognitively normal animpaired elders. Neurobiol. Aging 33, 845–855.

Song, F., Parekh, S.,Hooper,L., Loke, Y.K., Ryder, J.,Sutton, A.J., Hing, C.,Kwok, C.S., Pang, CHarvey, I., 2010. Dissemination and publication of research ndings: an updated review of related biases. Health Technol. Assess. 14.

Steffens, D.C., McQuoid, D.R., Payne, M.E., Potter, G.G., 2011. Change in hippocampal voume on magnetic resonance imaging and cognitive decline among older depresseand nondepressed subjects in the neurocognitive outcomes of depression in the elderly study. Am. J. Geriatr. Psychiatry 19, 4–12.

Stoub, T.R., Rogalski, E.J., Leurgans, S., Bennett,D.A., deToledo-Morrell,L., 2010. Rate ofentorhinal and hippocampal atrophy in incipient and mild AD: relation to memorfunction. N eurobiol. Aging 31, 1089–1098.

Stroup, D.F., Berlin, J.A., Morton, S.C., Olkin, I., Williamson, G.D., Rennie, D., Moher, DBecker, B.J., Sipe, T.A., Thacker, S.B., 2000. Meta-analysis of observational studies iepidemiology: a proposal for reporting. Meta-analysis of Observational Studies inEpidemiology (MOOSE) group. JAMA 283, 2008–2012.

Terrin, N., Schmid, C.H., Lau, J., Olkin, I., 2003. Adjusting for publication bias in the presence of heterogeneity. Stat. Med. 22, 2113–2126.

ThiessenPhilbrook, H., Barrowman, N., Garg, A.,2007. Imputing varianceestimates do noalter the conclusions of a meta-analysis with continuous outcomes: a case study ochangesin renal functionafter living kidney donation. J. Clin. Epidemiol. 60,228–240

Thompson, P.M., Hayashi, K.M., De Zubicaray, G., Janke, A.L., Rose, S.E., Semple,J., HermaD., Hong, M.S., Dittmer, S.S., Doddrell, D.M., 2003. Dynamics of gray matter loss i

Alzheimer's disease. J. Neurosci. 23, 994–

1005.Valenzuela,M.J., Sachdev, P., Wen, W.,Chen, X., Brodaty, H., 2008. Lifespan mental activit

predicts diminished rate of hippocampal atrophy. PLoS One 3, e2598.Viechtbauer, W., 2010. Conducting meta-analyses in R with the metafor package. J. Sta

Softw. 36, 1–48.Wang, L., Swank, J.S., Glick, I.E., Gado, M.H., Miller, M.I., Morris, J.C., Csernansky, J.G., 2003

Changes in hippocampal volume and shape across time distinguish dementia of thAlzheimer type from healthy aging. Neuroimage 20, 667–682.

Wang, L., Mamah, D., Harms, M.P., Karnik, M., Price, J.L., Gado, M.H., Thompson, P.A., BarchD.M., Miller, M.I., Csernansky, J.G., 2008. Progressive deformation of deep brain nucleand hippocampal–amygdala formation in schizophrenia. Biol. Psychiatry 641060–1068.

Wang, P.N.,Liu, H.C.,Lirng, J.F., Lin, K.N.,Wu, Z.A., 2009. Accelerated hippocampal atrophrates in stable and progressive amnestic mild cognitive impairment. Psychiatry Re171, 221–231.

Wenger, E., Mårtensson, J., Noack, H., Bodammer, N.C., Kühn, S., Schaefer, S., Heinze, H.-JDüzel, E., Bäckman,L., Lindenberger, U., Lövdén, M., 2014. Comparing manual and automatic segmentation of hippocampal volumes: Reliability and validity issues iyounger and older brains. Hum. Brain Mapp. 35, 4236–4248.


http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0050http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0050http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0050http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0050http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0050http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0055http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0055http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0055http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0055http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0055http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0060http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0060http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0060http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0060http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0060http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0065http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0065http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0065http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0065http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0065http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0075http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0075http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0075http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0075http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0070http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0070http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0070http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0070http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0080http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0085http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0090http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0090http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0090http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0090http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0090http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0095http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0095http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0095http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0095http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0325http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0325http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0325http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0325http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0325http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0105http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0105http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0105http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0105http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0110http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0110http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0110http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0110http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0110http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0115http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0115http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0115http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0115http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0115http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0120http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0120http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0120http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0120http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0120http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0125http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0125http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0125http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0125http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0135http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0135http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0135http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0135http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0130http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0130http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0130http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0130http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0140http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0140http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0140http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0140http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0140http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0330http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0330http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0145http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0145http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0145http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0145http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0150http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0150http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0150http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0150http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0155http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0160http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0160http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0160http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0160http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0160http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0165http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0165http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0165http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0165http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0165http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0170http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0170http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0170http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0170http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0170http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0175http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0175http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0175http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0175http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0175http://refhub.elsevier.com/S1053-8119(15)00217-7/rf1000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf1000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf1000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf1000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf1000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0180http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0180http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0180http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0180http://refhub.elsevier.com/S1053-8119(15)00217-7/rf2000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf2000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf2000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf2000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf2000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0185http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0190http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0190http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0190http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0190http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0190http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0195http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0195http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0275http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0275http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf5000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0295http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0285http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0290http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0280http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0275http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0275http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0270http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0265http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0260http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0255http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0250http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0245http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0340http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0240http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0335http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0235http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0230http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0225http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0220http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf3000http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0200http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0210http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0215http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0205http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0195http://refhub.elsevier.com/S1053-8119(15)00217-7/rf0195http://refhub.elsevier.com/S1053-8

a systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing

Documents