Associations between Total Cerebral Blood Flow and Age
Related Changes of the Brain
Adriaan C. G. M. van Es1*, Jeroen van der Grond1, V. Hester ten Dam2, Anton J. M. de Craen2, Gerard J.
Blauw2, Rudi G. J. Westendorp2, Faiza Admiraal-Behloul3, Mark A. van Buchem1, for the PROSPER Study
Group
1 Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands, 2 Section of Gerontology and Geriatrics, Department of General Internal Medicine,
Leiden University Medical Center, Leiden, The Netherlands, 3 Section of Image Processing (LKEB), Department of Radiology, Leiden University Medical Center, Leiden, The
Netherlands
Abstract
Background and Purpose: Although total cerebral blood flow (tCBF) is known to be related to age, less is known regarding
the associations between tCBF and the morphologic changes of the brain accompanying cerebral aging. The purpose of this
study was to investigate whether total cerebral blood flow (tCBF) is related to white matter hyperintensity (WMH) volume
and/or cerebral atrophy. Furthermore, we investigate whether tCBF should be expressed in mL/min, as was done in all
previous MR studies, or in mL/100 mL/min, which yielded good results in precious SPECT, PET and perfusion MRI studies
investigating regional cerebral blood flow.
Materials and Methods: Patients were included from the nested MRI sub-study of the PROSPER study. Dual fast spin echo
and FLAIR images were obtained in all patients. In addition, single slice phase contrast MR angiography was used for flow
measurements in the internal carotids and vertebral arteries. tCBF was expressed in both mL/min and mL/100 mL/min.
Results: We found a significant correlation between tCBF in mL/min and both age (r = 2.124; p = p#.001) and parenchymal
volume (r = 0.430; p#.001). We found no association between tCBF in mL/min and %-atrophy (r = 2.077; p = .103) or total
WMH volume (r = 2.069; p = .148). When tCBF was expressed in mL/100 mL/min the correlation between tCBF and age was
no longer found (r = 2.001; p = .985). Multivariate regression analyses corrected for age showed a significant correlation
between tCBF in mL/100 mL/min and WMH volume (r = 2.106; p = .044). No significant association between tCBF in mL/
100 mL/min and %-atrophy was found.
Conclusion: From this study we conclude that, when evaluating tCBF alterations due to various pathologies, tCBF should in
mL/100 mL/min instead of mL/min. Furthermore, changes or differences in WMH volume should be accounted for.
Citation: van Es ACGM, van der Grond J, ten Dam VH, de Craen AJM, Blauw GJ, et al. (2010) Associations between Total Cerebral Blood Flow and Age Related
Changes of the Brain. PLoS ONE 5(3): e9825. doi:10.1371/journal.pone.0009825
Editor: Cheng-Xin Gong, New York State Institute for Basic Research, United States of America
Received February 24, 2009; Accepted January 17, 2010; Published March 23, 2010
Copyright: ß 2010 van Es et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was funded with internal funds from the Leiden University Medical Center. The funders had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: A.C.G.M.van_Es@LUMC.nl
expected that the volume flow is getting too low to maintain normal
cerebral blood flow and function such as elderly subjects or patients
suffering from Alzheimer’s disease, diabetes or atherosclerosis.
White matter hyperintensities (WMHs) and cerebral atrophy
are common findings in the aging population and their prevalence
increases with age[10–12]. On T2-weighted Magnetic Resonance
Imaging (MRI) WMHs are seen as patchy or diffuse areas of
hyperintensity. Clinically they have been associated with gait
disturbance[13], cognitive impairment[14,15], mood disorder[16]
and dementia[17]. Changes in CBF might also reflect cerebral
changes such as atrophy. In addition to an increased WMH load,
cerebral atrophy is a common finding in the elderly and a
manifestation of neuronal degeneration contributing to cognitive
decline and dementia[18,19].
Low regional cerebral blood flow is one of the processes thought
to underlie the development of both WMHs and atrophy as strong
Introduction
Determination of total cerebral (tCBF) blood flow to the brain, by
measuring flow in the internal carotid arteries (ICA) and posterior
circulation has been applied in patients with obstructive disease of
the ICA or posterior circulation[1,2], arteriovenous malformations[3], acute neurotrauma[4], cerebral ischemia[5], and the
evaluation of vascular interventions such as bypass surgery[6] or
carotid endarterectomy[7]. In these studies tCBF was expressed in
mL/min, regardless of the volume of the supplied brain. However,
for interpretation of the data, Buijs et al. have published a flow
decrease of 4.8 ml/min per year in a normal population[8]. In
addition, Hendrikse and coworkers have shown that the distribution
of flow in the brain is strongly influenced by the anatomy of the
circle of Willis[9]. Determination of flow to the vessels that supply
the brain seems especially useful in subjects in whom it may be
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tCBF and Cerebral Aging
associations with vascular risk factors exist[10,20–24]. Moreover,
declining blood pressure has also been associated with global brain
atrophy[25]. The associations between flow and WMHs have been
investigated in positron emission topography (PET), single photon
emission topography (SPECT) and perfusion weighted MRI
studies, showing a relationship between low regional cerebral
blood flow (rCBF) and WMHs in small populations[26–33]. All
these studies expressed the rCBF in mL/100mL/min. Therefore,
contrary to previous MR studies, these flow measurements are not
influenced by potential influence of the volume of the provided
(part of the) brain.
Despite this evidence for an important role of the cerebral blood
supply in the development of both WMHs and atrophy, only one
study has investigated the association between tCBF and
WMHs[34]. This study found that patients in the quartile with
the highest tCBF had a lower number and severity of WMHs
suggesting an association between tCBF and the presence of
WMHs. However this study has two major limitations. First,
WMHs were scored quantitatively and analyzed in quartiles.
Second, similar to previous MR studies, the tCBF was expressed as
mL/min and therefore the effect of parenchyma volume was not
taken into account.
The aim of this study is two-fold: 1) to investigate whether tCBF
is related to WMHs volume and/or cerebral atrophy and 2)
whether these associations are influenced by expressing tCBF in
mL/100 mL/min instead of mL/min.
Table 1. Demographic and clinical characteristics.
Continuous variates
Age, y
75 (3)
Systolic blood pressure, mm Hg
158 (23)
Diastolic blood pressure, mm Hg
86 (11)
Total cholesterol, mmol/L
5.8 (0.8)
LDL cholesterol mmol/L
3.9 (0.7)
HDL cholesterol, mmol/L
1.2 (0.3)
Triglycerides, mmol/L
1.5 (0.7)
Total WMH volume, ml
5.2 (9.6)
Categorical variates
n (%)
Male gender
262 (56)
Current smoker
96 (21)
History of diabetes
76 (16)
History of hypertension
293 (63)
History of myocard infarction
56 (12)
History of stroke or TIA
75 (16)
History of any vascular disease
202 (44)
MRI stroke
178 (38)
LDL = Low-density lipoprotein.
HDL = High-density lipoprotein.
WMH = White matter hyperintensity.
n = number of patients.
% = percentage of patients.
doi:10.1371/journal.pone.0009825.t001
Methods
Ethics Statement
The PROSPER study had ethics review board approval of all
locations and written informed consent of all participants. In
addition, the Leiden University Medical Center institutional ethics
review board approved the protocol for the prospective MR study
and subsequent retrospective analyses. Moreover, all participants
gave written informed consent. Participants of this MR study also
agreed with future retrospective analysis of their MR data for
research purposes.
recovery (FLAIR) (TE = 100 msec; TR = 8000 msec; flip angle = 90u; section thickness = 3 mm; sections = 48; no section
gap; whole brain coverage; FOV = 220; scan matrix = 2566204,
nsa = 1) images were obtained from all subjects. In addition, single
slice phase contrast MR angiography (TR/TE = 16/9 msec; flip
angle = 7.5u; slice thickness = 5 mm; FOV = 250; RFOV = 75%;
scan percentage = 80%; matrix = 256; 8 signal averages) with a
velocity encoding of 100 cm/second was used for flow measurements[36]. The scans were performed in a plane perpendicular to
the left and right internal carotid artery and the vertebral arteries,
at the level of the vertical segment of the petrous portion of the
internal carotid artery (Figure 1).
Patients
Patients were included from the nested MRI substudy of the
PROspective Study of Pravastatin in the Elderly at Risk
(PROSPER). Inclusion criteria for this study were: men or women
aged 70–82 years; total cholesterol 4.0–9.0 mmol/L; stroke,
transient ischemic attack, myocardial infarction, arterial surgery,
or amputation for vascular disease .6 months before study entry;
$1 of the following risk factors for vascular disease: current
smoker; hypertension, currently receiving drug treatment; known
diabetes mellitus or fastening blood glucose .7 mmol/L.
Exclusion criteria have been described in detail elsewhere[35].
All subjects had a history of, or were at increased risk for, vascular
disease. In total, 464 subjects underwent MRI including flow
measurements. 17 patients dropped out because flow measurements of the ICAs or vertebral arteries or segmentation of the
intracranial structures failed because of technical problems.
Patient characteristics are shown in Table 1.
Image Analysis
WMHs, intracranial volume, and brain parenchyma were
assessed semiautomatically. That is, segmentations of WMHs,
intracranial volume, and brain parenchyma were generated
automatically using Software for Neuro-Image Processing in
Experimental Research (SNIPER), an in-house developed program for image processing (Figure 2.). The WMH volume was
calculated automatically[37]. Infarcted areas were counted being
CSF. All measurements were performed blinded to subject
identity, age and sex. Atrophy was calculated using the formula:
atrophy (%) = ((intracranial volume – parenchymal volume)/
intracranial volume) 6100%. For tCBF assessment, images were
analyzed using the software package FLOWH[38]. For this
analysis a region of interest (ROI) was manually drawn around
the left and right internal carotid and the right and left vertebral
arteries in the magnitude image by one observer (ACGMvE). The
flow in these four vessels was summed giving the tCBF in mL/min.
TCBF was also expressed in mL blood per 100 mL of brain
parenchyma per min (mL/100 mL/min).
MRI
All imaging was performed on an MR system operating at a
field strength of 1.5 Tesla (Philips Medical Systems, Best, The
Netherlands). Dual fast spin echo (TE = 27/120 msec; TR = 3000
msec; flip angle = 90u; section thickness = 3 mm; number of
sections = 48; no section gap; whole brain coverage; FOV = 220;
scan matrix = 2566204; nsa = 1) and fluid-attenuated inversion
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means (SD)
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tCBF and Cerebral Aging
Statistical analysis
SPSS for Windows (release 12.0; SPSS, Chicago, IL) was used
for data analysis. Linear regression analysis was used to investigate
correlations between parameters. Age was entered as an
independent variable as previous studies have reported an inverse
correlation between tCBF and age[8,9]. The level of significance
was set at p,0.05.
Results
The MRI characteristics of the subjects included in this study are
shown in Table 2. In this study an inverse correlation between age
and tCBF in mL/min was found (r = –.124; p = 0.008; Figure 3a).
This corresponds with an annual flow decrease of 6.2 mL. Figure 3b
shows the association between tCBF in mL/min and parenchymal
volume, indicating a significant correlation (r = 0.430; p#.001)
between the two. When tCBF was expressed in mL/100 mL/min
the correlation between tCBF and age was no longer found
(r = –.001; p = .985) (Figure 3c). The volume flow (mL/min) in the
individual vessels contributing to the tCBF did not show an
association with age. However, significant correlations with
parenchymal volume were found for both left (r = .114; p = .016)
and right (r = .119; p = .012) vertebral artery and both left (r = .293;
p#.001) and right (r = .284; p#.001) internal carotid artery.
We found no association between tCBF in mL/min and
%-atrophy (r = –.077; p = .103) or total WMH volume (r = –.069;
p = .148) (Figure 4a & 4b). TCBF in mL/100 mL/min was
associated with WMH volume (r = –.106; p = .044) (Figure 5). No
significant association between tCBF in mL/100 mL/min and
%-atrophy was found. Furthermore, no association between
parenchyma volume and WMH volume existed (r = .05; p = .317).
Discussion
The findings of the present study are fourfold. First, the most
important finding is the strong correlation between tCBF in mL/
min and both age and parenchymal volume. However, the
association between tCBF and age was no longer found when flow
was expressed in mL/100 mL/min. Second, when analysed
separately, the flow in mL/min over each individual vessels
contributing to the cerebral blood flow was associated with
parenchymal volume as well. Third, when expressing tCBF in
mL/100 mL/min a correlation between tCBF and total WMH
volume was found. Fourth, no association was found between
tCBF in mL/100 mL/min and atrophy.
Figure 1. Single slice phase contrast MR angiography. Saggital
MRA scout image of the main brain feeding arteries (a). The white slab
represents the position of the transverse angiographic phase image.
This image shows the carotid arteries (arrows) and vertebral arteries
(arrowheads) over which flow was measured (b).
doi:10.1371/journal.pone.0009825.g001
Figure 2. The segmentation process using SNIPER (Software for Neuro-Image Processing in Experimental Research). T2-weighted
image (a) and FLAIR image (b). Result of automated segmentation process based on both sequences (c).
doi:10.1371/journal.pone.0009825.g002
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tCBF and Cerebral Aging
Table 2. MR characteristics.
mean
SD
minimum
maximum
tCBF in mL/min
510
87.4
315
846
tCBF in mL/100 mL/min
50.4
7.8
30.9
74.3
Parenchymal vol. (mL)
1016
98.7
752
1259
Atrophy (%)
27.3
3.2
15.6
38.4
tot. WMH vol. (mL)
7.1
10.6
0
76.2
tCBF = Total cerebral blood flow.
WMH = White matter hyperintensity.
doi:10.1371/journal.pone.0009825.t002
In the present study we found a significant association between
tCBF in mL/min and age, corresponding with an annual flow
decrease of 6.2 mL. This confirms a previous study by Buijs et al.
showing an average flow decrease of 4.8 mL/min per year[8]. The
slightly higher decline of tCBF in mL/min with age found in our
study is likely due to the fact that we included relatively older
subjects and that all subjects had cardiovascular disease or risk
factors for developing this condition. A strong association between
tCBF in mL/min and parenchymal volume was found and
remained after the adjustment for age. However, when the tCBF
was expressed in mL/100 mL/min no significant association with
age was found. Therefore it seems that parenchymal volume
underlies the previous reported associations between age and
tCBF mL/min.
In the present study the tCBF is obtained by the summation of
the volume flow over the two carotid arteries and the two vertebral
arteries. If the blood flow over these individual vessels is analysed
separately, no association between the flow volume and age is
found. This may be due to variation caused by the different
conformations of the Circle of Willis as described by Hendrikse et
al.[9] However, an association with parenchymal volume, the
most important determinant of cerebral blood flow, was still
present. Our data show a much higher association between the
volume flow over internal carotid arteries and parenchymal
volume than for the flow over the vertebral arteries. Both vertebral
arteries contribute to the posterior circulation, which for a large
part supplies the cerebellum. In this respect, it could be that
parenchymal volume loss due to aging is different in the
cerebellum than in the cerebrum.
Atherosclerotic patients have a relative high prevalence of
WMHs and atrophy. In our population suffering from vascular
pathology and cardiovascular riskfactors it was shown that tCBF in
mL/100 mL/min was associated with WMH volume. No
association was found between tCBF in mL/100 mL/min and
atrophy. Although we can not draw a solid conclusion from our
cross-sectional study, this finding indirectly suggests that blood
flow to the brain probably plays a minor role in the development
of atrophy. However, atrophy is best assessed using two time
points, therefore the absence of associations between atrophy and
tCBF should be replicated in a longitudinal study.
A potential limitation of our study is the small age range of the
included patients. All patients in the present study were aged
between 72 and 85 years, which makes extrapolation of our results
to younger individuals arbitrary. On the other hand, WMHs and
atrophy are highly prevalent and are thought to be clinically
significant in this specific age span. Furthermore, the crosssectional design of this study could not elucidate whether
decreased tCBF precedes WMH or that reduced brain function
due to the presence WMH reduces tCBF flow parameters.
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Figure 3. Association of tCBF with age and parenchyma
volume. Scatterplot of tCBF (mL/sec) versus age (yrs) (r = –.124;
p = 0.008) (a) and parenchymal volume (mL) (r = 0.430; p#.001) (b).
Box-and-whisker plot of average tCBF (mL/100 mL/min) found for each
age (yrs) (c).
doi:10.1371/journal.pone.0009825.g003
Conclusion
In conclusion, we found that tCBF in mL/min is strongly
associated with the parenchymal volume rather than age.
Although this finding seems obvious, this is the first study showing
this strong association. In addition, we found a much weaker
association between tCBF in mL/100 mL/min and the severity of
WMHs. These findings have important implications for future
studies in which flow measurements are being used as diagnostic
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tCBF and Cerebral Aging
Figure 5. Association of tCBF (mL/100 mL/min) with WMH
volume. Scatterplot of tCBF (mL/100 mL/min) versus WMH volume
(mL).
doi:10.1371/journal.pone.0009825.g005
elderly patients or patients with a pathological increase of WMHs,
such as diabetic type II subjects, tCBF measurements should also
be corrected for WMH volumes.
Acknowledgments
PROSPER Study Group
Executive Committee: (Glasgow) J. Shepherd (chairman and principal
investigator), S.M. Cobbe, I. Ford, A. Gaw, P.W. Macfarlane, C.J.
Packard, D.J. Stott; (Leiden) G.J. Blauw (principal Investigator), E.L.E.M.
Bollen, A.M. Kamper, R.G J. Westendorp; (Cork) M.B. Murphy (principal
investigator), B.M. Buckley, M. Hyland, I.J. Perry.
End Point Committee: S.M. Cobbe (chairman), J.W. Jukema, P.W.
Macfarlane, A.E. Meinders, D.J. Stott, B.J. Sweeney, C. Twomey.
Data and Safety Monitoring Committee: W.V. Brown (chairman), H.C.
Diener, J. Feely, I. Ford (nonvoting), T. Pearson, S. Pocock, P.A. van
Zwieten.
Figure 4. Association of tCBF (in mL/min) with atrophy
and WMH volume. Scatterplot of tCBF (mL/sec) versus atrophy (%)
(r = –.077; p = .103) (a) and total WMH volume (mL) (r = –.069; p = .148)
(b). Atrophy was defined by the following equation: intracranial volume
- parenchyma volume/intracranial volume. Therefore, number reflects
the percentage of intracranial volume occupied by cerebrospinal fluid.
doi:10.1371/journal.pone.0009825.g004
Author Contributions
Conceived and designed the experiments: ACGMvE JvdG VHtD AJMdC
GJB RGJW FAB MAvB. Performed the experiments: ACGMvE JvdG
VHtD FAB. Analyzed the data: ACGMvE JvdG AJMdC GJB RGJW
MAvB. Contributed reagents/materials/analysis tools: ACGMvE AJMdC
GJB RGJW FAB. Wrote the paper: ACGMvE JvdG MAvB.
tool: All future volume flow measurements should be expressed in
mL/100 mL/min rather than mL/min. Moreover, when studying
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March 2010 | Volume 5 | Issue 3 | e9825