assessment of cerebral vasoreactivity with transcranial ... · tfa – transfer function analysis...
TRANSCRIPT
2015/2016
João Pedro Brandão Madureira da Silva
Assessment of cerebral vasoreactivity with transcranial
doppler in healthy portuguese adults
março, 2016
Mestrado Integrado em Medicina
Área: Neurologia
Tipologia: Dissertação
Trabalho efetuado sob a Orientação de:
Doutora Elsa Irene Peixoto Azevedo Silva
E sob a Coorientação de:
Dr. Pedro Miguel Araújo Campos de Castro
Trabalho organizado de acordo com as normas da revista:
Journal of the Neurological Sciences
João Pedro Brandão Madureira da Silva
Assessment of cerebral vasoreactivity with transcranial
doppler in healthy portuguese adults
março, 2016
Projeto de Opção do 6º ano - DECLARAÇÃO DE INTEGRIDADE
Eu, João Pedro Brandão Madureira da Silva, abaixo assinado, nº mecanográfico 201006158, estudante do 6º ano do Ciclo de Estudos Integrado em Medicina, na Faculdade de Medicina da Universidade do Porto, declaro ter atuado com absoluta integridade na elaboração deste projeto de opção.
Neste sentido, confirmo que NÃO incorri em plágio (ato pelo qual um indivíduo, mesmo por omissão, assume a autoria de um determinado trabalho intelectual, ou partes dele). Mais declaro que todas as frases que retirei de trabalhos anteriores pertencentes a outros autores, foram referenciadas, ou redigidas com novas palavras, tendo colocado, neste caso, a citação da fonte bibliográfica.
Faculdade de Medicina da Universidade do Porto, 23/03/2015
Assinatura conforme cartão de identificação:
_________________________
Projecto de Opção do 6º ano – DECLARAÇÃO DE REPRODUÇÃO
NOME
João Pedro Brandão Madureira da Silva
NÚMERO DE ESTUDANTE DATA DE CONCLUSÃO
201006158
DESIGNAÇÃO DA ÁREA DO PROJECTO
Neurologia
TÍTULO DISSERTAÇÃO/MONOGRAFIA (riscar o que não interessa)
Assessment of cerebral vasoreactivity with transcranial doppler in healthy portuguese adults
ORIENTADOR
Doutora Elsa Irene Peixoto Azevedo Silva
COORIENTADOR (se aplicável)
Dr. Pedro Miguel Araujo Campos de Castro
ASSINALE APENAS UMA DAS OPÇÕES:
É AUTORIZADA A REPRODUÇÃO INTEGRAL DESTE TRABALHO APENAS PARA EFEITOS DE INVESTIGAÇÃO,
MEDIANTE DECLARAÇÃO ESCRITA DO INTERESSADO, QUE A TAL SE COMPROMETE.
É AUTORIZADA A REPRODUÇÃO PARCIAL DESTE TRABALHO (INDICAR, CASO TAL SEJA NECESSÁRIO, Nº
MÁXIMO DE PÁGINAS, ILUSTRAÇÕES, GRÁFICOS, ETC.) APENAS PARA EFEITOS DE INVESTIGAÇÃO, MEDIANTE
DECLARAÇÃO ESCRITA DO INTERESSADO, QUE A TAL SE COMPROMETE.
DE ACORDO COM A LEGISLAÇÃO EM VIGOR, (INDICAR, CASO TAL SEJA NECESSÁRIO, Nº MÁXIMO DE PÁGINAS,
ILUSTRAÇÕES, GRÁFICOS, ETC.) NÃO É PERMITIDA A REPRODUÇÃO DE QUALQUER PARTE DESTE TRABALHO.
Faculdade de Medicina da Universidade do Porto, 23 / 03 / 2016
Assinatura conforme cartão de identificação: ______________________________________________
X
À minha família, em particular aos meus pais e irmã,
aos meus amigos e a todos aqueles que me apoiaram
durante o meu percurso académico… e fora dele.
1
Clinical Research Paper
Assessment of cerebral vasoreactivity with transcranial
doppler in healthy portuguese adults
Authors:
João Brandão Madureira a, Pedro Miguel Castro b, Elsa Azevedo c
Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro,
4200-319 Porto, Portugal; [email protected] a
Neurology Department, São João Hospital Center, Faculty of Medicine of
University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto,
Portugal; [email protected] b
Neurology Department, São João Hospital Center, Faculty of Medicine of
University of Porto, Alameda Professor Hernâni Monteiro, 4200-319 Porto,
Portugal; [email protected] c
Corresponding author:
João Brandão Madureira
Faculty of Medicine of University of Porto,
Alameda Professor Hernâni Monteiro,
4200-319 Porto, Portugal
E-mail: [email protected]
2
Abbreviations
ABP – Arterial blood pressure
CA – Cerebral autoregulation
CBF – Cerebral blood flow
CBFV – Cerebral blood flow velocity
CBFVIDX – CBFV during Identify X
CBFVNB – CBFV during the N-Back
CVR – Cerebrovascular reactivity
CVRi – Cerebrovascular resistance index
EtCO2 – End-tidal CO2
HF – High frequency
HR – Heart rate
LF – Low frequency
MoCA – Montreal Cognitive Assessment
NVC – Neurovascular coupling
TCD – Transcranial Doppler
TFA – Transfer function analysis
VLF – Very-low frequency
VMR – Vasomotor reactivity
3
Abstract
Background: Cerebrovascular reactivity (CVR) maintains an adequate cerebral
blood flow by three major regulatory mechanisms: cerebral autoregulation (CA),
vasomotor reactivity (VMR) to CO2 variations and neurovascular coupling (NVC).
However, most studies generalize their results based in the response to only one
of these tests. Using a neurovascular stress tests battery, our study aims to
evaluate if there is any relationship between CVR mechanisms and how they might
be influenced by demographic and systemic hemodynamic factors. Methods:
Fifty-eight healthy adults from 20 to 80 years-old were included. Arterial blood
pressure (Finometer), cerebral blood flow velocity in both middle cerebral arteries
(transcranial Doppler), electrocardiogram and end-tidal-CO2 were monitored. We
assessed CA by transfer function analysis, VMR at hypo and hypercapnia
(carbogen 5%) and NVC response during N-Back Task. Montreal Cognitive
Assessment score was recorded. Results: Neurovascular stress tests were not
affected by age or gender and no correlation was found between their outputs
(p>0.05). Baseline and variations of hemodynamic parameters had no correlation
with their outputs (p>0.05). Cognitive score was uncorrelated with NVC (p>0.05).
Conclusions: Neurovascular stress tests measure different aspects of CVR
control and a full battery might be more useful for future studies on neurovascular
control. Being independent of age and cognitive status, CVR tests seem promising
for studying several cerebrovascular conditions affecting the aging brain.
Keywords
Cerebrovascular reactivity; cerebral blood flow; cerebral autoregulation;
vasomotor reactivity; neurovascular coupling; transcranial Doppler.
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1. Introduction
Cerebrovascular reactivity (CVR) is crucial for the maintenance of an adequate
cerebral blood perfusion in response to a myriad of vasoactive stimuli [1-3]. In
order to compensate for high metabolic rate and limited energy stores of brain
tissue, a complex interplay of metabolic [4, 5], neuronal [6, 7], pressure- and
shear-dependent [4-6, 8] myogenic mechanisms modulate cerebral resistance,
allowing the cerebrovascular bed to constrict or dilate in response to
hemodynamic and neurophysiological stimuli [9].
Transcranial Doppler (TCD) is a powerful and versatile tool for non-invasive
assessment of intracranial vessels. With the advent of this technique, which has
a remarkable temporal resolution, it became possible to easily assess the health
of the cerebrovascular bed using neurovascular stress tests [10, 11]. These
procedures allow the evaluation of three major physiological processes that
underlie cerebral blood flow preservation: (i) cerebral autoregulation (CA), which
is regarded as the capacity of the cerebral blood vessels to maintain constant
cerebral blood flow (CBF) regardless of changes in cerebral perfusion pressure
(CBP) [12]; (ii) vasomotor reactivity (VMR), which allows flow control in response
to changes in carbon dioxide (CO2) and oxygen (O2) levels [13]; and (iii)
neurovascular coupling (NVC), or functional hyperaemia, which adapts local flow
in response to neuronal activity and metabolic demand [14].
Impairment of CVR has been linked to several disorders such as Alzheimer’s and
Parkinson’s diseases [15-18], head trauma [19], subarachnoid haemorrhage [20],
carotid artery disease [21], stroke [22], metabolic diseases [23] and autonomic
5
failure [24]. However, in most reports only one of the CVR components is studied.
Therefore, there is a lack of evidence on the interplay between CA, VMR and
NVC in both healthy and pathological states, and how age, gender and other
demographic factors influence them per se, regardless of disease. It is also
essential to test the reproducibility of TCD results across several populations, so
that confounding factors are identified.
Using a neurovascular stress tests battery, this study seeks to evaluate if there
is any relationship between CA, VMR and NVC and how they might be
individually influenced by age or gender. It also aims to standardize a reference
set of values for neurovascular stress tests in a healthy population.
2. Methods
This study was conducted in São João Hospital Center, a university hospital in
Porto, Portugal. It was approved by the appropriate local institutional ethical
committee and performed in accordance with the Declaration of Helsinki ethical
standards. All participants gave written and signed informed consent.
2.1. Population studied
Healthy subjects were selected from hospital or faculty staff and by advertising
within university facilities. We predefined to include 10 participants with the same
number of males and females in each decade of age strata, ranging from 20 to
80 years. All participants fulfilled a comprehensive medical questionnaire to
exclude if they had common cardiovascular risk factors (hypertension, diabetes,
6
smoking) or history of a cardiovascular or neurological disease affecting the
central nervous system. Systolic and diastolic blood pressure was averaged from
three measurements in the sitting position with an oscillometric cuff (Omron M6,
Japan). Body mass index was calculated for each participant. All participants
above 40 years underwent cervical and transcranial ultrasound studies (Vivid e;
GE) before evaluation to exclude hemodynamically significant extra- or
intracranial stenosis. All subjects were refrained from caffeinated beverages,
alcohol and exercise for at least 12 hours before the study.
2.2. Cognitive assessment
The subjects performed a formal cognitive assessment using Montreal Cognitive
Assessment (MoCA) test [25].
2.3. Monitoring protocol
Evaluations were carried out in a dim lighted room, with temperature around
20ºC. All participants were monitored in supine position in a bed with the head at
0º. Arterial blood pressure (ABP) was continuously monitored with a finger cuff in
non-dominant side using Finometer MIDI (FMS, Amsterdam, Netherlands). Heart
rate (HR) was assessed from lead II of a standard 3-lead electrocardiogram
(ECG). Cerebral blood flow velocity (CBFV) was recorded bilaterally from M1
segment of the middle cerebral artery (MCA), at a depth of 50-55 mm, with 2-
MHz monitoring probes secured with a standard headband (Doppler BoxX, DWL,
Singen, Germany). End-tidal carbon dioxide (EtCO2) was continuously recorded
with nasal cannula attached to Respsense capnograph (Nonin, Amsterdam,
Netherlands). All data were synchronized and digitized at 400 Hz with Powerlab
7
(AD Instruments, Oxford, UK) and stored for offline analysis. Data was recorded
in resting state for 10 minutes to posteriorly assess CA. Afterwards CO2 and
neurovascular coupling protocols were performed, as explained below.
2.3.1. CO2 vasoreactivity protocol
After a 2-minute resting period, subjects inspired a gas mixture of 5% CO2, 21%
O2 and balance nitrogen for 2 minutes, then rested for 2 minutes and finally
hyperventilated to an end-tidal CO2 of approximately 20 mmHg for another 2
minutes. VMR was determined as the slope of relationship between ETCO2
plotted against averaged mean CBFV at the last 30 seconds of hypo or
hypercapnia and expressed as change in cerebral blood flow per mmHg change
in ETCO2. VMR was calculated separately for hypercapnia and hypocapnia.
2.3.2. Neurovascular coupling protocol
N-Back Task was performed and analysed as described by Sorond F. et al [26].
While in supine position, a sequence of single letters was displayed onto the
ceiling. While watching the sequence of letters, subjects were instructed to press
the button of a computer mouse each time a letter was repeated (1-Back) or each
time a letter was repeated every other letter (2-Back). A control task was
performed before each task – Identify the X; measured parameters were baseline
CBFV and its difference during the N-Back Tasks. The sequence of testing was
as follows: 2 minutes of control task; 2 minutes of 1-Back; 2 minutes of control
task; and finally 2 minutes of 2-Back. The mean percent change for each MCA
was calculated as a ratio of the percent difference between the CBFV during the
N-Back (CBFVNB) and its corresponding “Identify the letter X” control period
8
(CBFVIDX) divided by CBFV during Identify X (CBFVIDX) and multiplied by 100
using the following formula:
[(CBFVNB -CBFVIDX)/ (CBFVIDX)] *100.
2.4. Data analysis and CA calculations
All signals were inspected and artifacts removed by linear interpolation. Systolic,
mean and diastolic values of ABP and CBFV were calculated. For each
heartbeat, cerebrovascular resistance index (CVRi) was calculated by
ABP/CBFV reflecting vasomotor function [27]. Autoregulation was assessed in
conformity with a recent set of recommendations from the Cerebral
Autoregulation Research Network (CARNet) [28]. Transfer function analysis
(TFA) was used to assess dynamic CA by calculating coherence, gain and phase
parameters from beat-to-beat spontaneous oscillations in CBFV and ABP as
previously reported [29, 30]. In resume, 10 minutes of normalized data were
interpolated at 100 Hz into uniform time basis; averaged periodogram was
calculated by Welch [29] method with Hanning window of 100 seconds, with 50%
overlap. Coherence was calculated between input auto-spectra of ABP over
cross-spectra of CBFV/ABP and transfer functions of phase and gain were
determined by dividing the cross-spectrum by the input auto-spectrum [29].
Coherence, gain and phase are reported in three bands: very-low (VLF: 0.02-
0.07 Hz), low (LF: 0.07–0.20 Hz) and high (HF: 0.20-0.50 Hz) frequencies. CA is
usually believed to operate at VLF and LF bands [29-31]. In short, coherence is
the coefficient of correlation between the signals; higher coherence between the
oscillations is reflective of less effective CA. Gain quantifies the damping effect
of CA on the magnitude of ABP oscillations. Phase shift represents the time delay
9
between ABP and CBFV oscillations. Lower gain and higher phase represent
tighter, more effective autoregulatory response [29, 32].
2.5. Statistics
Normality of the variables was determined by Shapiro-Wilk test. Right and left
differences in MCA measurements were examined using paired t-tests and
Wilcoxon signed-rank test. As there were no significant differences between
sides, right and left mean CBFV was computed for all subsequent analysis.
Student’s t-test and one-way between subjects ANOVA test were used to
compare subjects baseline characteristics between genders and age groups.
MoCA scores were compared between age groups using Kruskal-Wallis H test.
Significant differences of hemodynamic parameters, CA, VMR and NVC results
between age strata and genders were evaluated by multiple linear regression.
Pearson or Spearman correlation coefficients were used as appropriate to assess
the influence of ABP, HR and EtCO2 on CA, VMR, NVC results as well as in the
relationship between these tests. Paired t-tests and Wilcoxon signed-rank tests
were used to assess the significance of the variation of ABP, HR and EtCO2
between the rest and activation phases of VMR and NVC protocols.
3. Results
Table 1 summarizes demographic and baseline measurements of all subjects
(n=58). Older participants had higher MAP (MAP F(53,1)=30.34, p<0.00001). No
other statistical significant differences were found between baseline
characteristics. A multiple regression studied the prediction of CBFV according
10
to gender and age (F(2, 50)=10.840, p=0.00012, R2=0.302) (table 2). Age was
analysed as a continuous variable. Mean CBFV decreased approximately 3.4%
by decade (β=-0.342, p=0.0002), and women had a mean CBFV 7,5 cm/s higher
than men (β=7.529, p=0.0134). The same analysis was performed with CVRi as
the dependent variable. This model was statistical significant (F(2, 50)=5.765,
p=0.00559, R2=0.187). However only age was a significant predictor of CVR
(β=0.008, p=0.0016). Increased age was also associated with lower MoCA
scores (χ2(5)=28.826, p=0.00003). This was particularly significant in the
visuospatial/executive (χ2(5)=12.949, p=0.02386), attention (χ2(5)=18.456,
p=0.00243), language (χ2(5)=14.118, p=0.01488), abstraction (χ2(5)=11.259,
p=0.04648) and delayed recall (χ2(5)=11.421, p=0.04364) domains (table A.1).
No statistical significant differences were detected between right and left MCA
hemodynamic measurements (table A.2). Thus, mean CBFV of right and left MCA
was calculated and used as parameter for subsequent analysis. We found no
effect of age and gender concerning CA, VMR and NVC tests.
Figure 1 summarizes transfer function gain, phase and coherence in the
frequency domains of VLF (0.02–0.07 Hz), LF (0.07–0.20 Hz) and HF (0.20-0.50
Hz) for spontaneous oscillations during the CA protocol. Coherence and gain
were positively correlated between themselves in the VLF and LF domains (VLF:
r(58)=0.518, p=0.00003; LF: r(58)=0.57122, p<0.000001) while phase was
largely independent (p>0.05) (table 3).
Figures 2 depicts the percentage of change in CBFV, MAP, HR and EtCO2 during
hypercapnia and hypocapnia. Mean values of MAP, HR and EtCO2 during the
11
resting and activation phases, as well as the value of variation during these
periods, are depicted in table 4. During the hypercapnic challenge there was an
increase in EtCO2 of approximately 9 ± 3 mmHg, while it decreased by 17 ± 3
mmHg during hyperventilation. Hypocapnia gain was correlated with EtCO2
observed during the procedure (r(55)=0.331, p=0.01365). While MAP increased
modestly during hypercapnia, HR was the main systemic hemodynamic
parameter changing during hyperventilation. These changes did not affect VMR
results (p>0.05). VMR global gain was positively correlated with hypercapnic
gains (r(56)=0.413, p=0.00155), but not with the hypocapnic (r(56)= 0.222;
p=0.09938). Curiously, hypercapnic and hypocapnic gains were not correlated
(r(56)=0.214, p=0.11311) (table 3).
The average CBFV increase during 2-back task was 6.27 ± 4.64 % (figure 3).
There was a statistical significant but mild change in MAP, HR and EtCO2
(p<0.01) during the task, as reported on table 4. Systemic hemodynamic
parameters did not influence test outcomes. NVC results did not correlate with
MoCA global and subtotal scores (p>0.05).
CA, VMR and NVC results did not correlated significantly with each other except
for VMR global gain, which was correlated with both LF and HF TFA gain
(r(56)=0.326, p=0.01406; r(56)=0.324; p=0.01481; respectively) (table 3).
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4. Discussion
This study suggests, for the first time, that there is no clear correlation between
the outputs of CA, VMR and NVC protocols. Neurovascular stress tests seemed
to be independent of age and gender, making it easier to compare results across
different demographic groups. Thus far, no consensus has been reached on the
role of aging on CVR. In fact, while some studies point to a negative correlation
between age and CVR [33-36], others report no association [37-40]. In the
present study, aging was associated with a decrease of CBFV and an increase
in CVRi. These findings might result from systemic changes in the vascular tree
that are known to accumulate during lifetime. Thus, it would be expected that
aging per se would result in an impairment of CVR. However, we demonstrated
that aging had no influence on neurovascular stress tests, in spite of CBFV
decline with age [41-45]. Past reports on cognitive performance have shown that
successful aging is associated with higher brain activation, compensating for age-
related neural changes and achieving an accuracy that equals young subjects
[40]. These compensatory mechanisms have been reported in other studies, not
only during neuronal activation, but also during metabolic and autoregulatory
stimuli [39, 46]. Globally, data seems to suggest that cerebrovascular adaptive
mechanisms have a functional reserve, compensating for the age-related
deterioration of the cerebrovascular bed and enabling the maintenance of
cerebrovascular homeostasis.
Several studies have reported higher CBFV in women, compared to men [47].
Similarly, gender-related differences have been noticed in CA and VMR studies
[47, 48]. Aging seems to be related to this findings, since women have higher
13
hypercapnic gains than men in younger ages, but lower values after menopause
in the absence of hormonal supplements [49]. Thus, hormonal status might play
an important role in the maintenance of cerebrovascular homeostasis. Changes
in the microcirculation, such as vessel tonus, reactivity and metabolism might also
be related to this finding. Our results show that, although there is a decrease of
CBFV with age in both genders, women have higher mean velocities, regardless
of age. On the other hand, this difference does not seem to transpose to CA,
VMR or NVC. However, we did not evaluate the phase of menstrual cycle, if
women were pre or postmenopausal, or if they were on hormonal supplements,
which might have an effect on cerebrovascular hemodynamics, thus acting as a
potential confounding factor.
Cerebral autoregulation might be assessed using a correlation coefficient [50],
autoregulatory index [51] or transfer function analysis [52], although no
consensus exists on what should be the gold standard. In this study we used
TFA, which has been increasing in popularity amongst research groups [28].
Gain, phase shift and coherence were computed using fast-Fourrier
transformation. The curves obtained for each of these parameters were similar to
those reported in literature [53]. Taking into account that coherence values were
lower than 0.5 below 0.05 Hz, any assumption below this frequency should be
made with caution, since linearity may not be applicable. However, it steadily
increases and surpasses 0.5 after 0.05 Hz. On the other hand, high frequency
(HF) domains show high coherence and gain values, suggesting that
autoregulatory mechanisms are unable to control these oscillations. Phase shift
values are approximately 0 from 0.30 Hz onwards. Therefore, there is no lag
14
between systemic and cerebral oscillations in the HF range and ABP is
transmitted undamped to CBFV. The opposite occurs towards the LF band, with
low gain and high phase shift values. Thus, it is thought that CA exerts its effects
in the lower band of frequencies, presumably below 0.30 Hz.
There is still a large heterogeneity between the various methods of TFA in the
literature. Phase shift has been shown to be more stable than other CA
parameters. Our results show lower dispersion of values for phase shift than for
gain or correlation, as can be noted in figure 1. It also shows less variation after
0.30 Hz, which is pointed as the limit for the cerebral autoregulatory capacity. On
the other hand, phase was not correlated with gain or coherence, which might
favour the use of this parameter as an indicator of autoregulation. However, it has
one major drawback: it requires the assumption of stationary conditions, which
might be difficult to accomplish even in controlled protocols where multiple
sources of non-linearities are possible.
CVR, which is dependent on cerebrovascular endothelial function, can be
assessed from the CBFV responses to rapid changes in EtCO2. Vascular tonus
reacts to these changes, favouring vasodilation in the onset of hypercapnia and
vasoconstriction with hypocapnia. In this study, hypercapnia was induced by CO2
administration and hypocapnia by hyperventilation. VMR global gain, as well as
hypercapnic and hypocapnic gains were independent of age and gender and no
correlation was found between these gains. However, global gain was correlated
with the hypercapnic gain. Thus, it seems that VMR is more linked to vasodilatory
than vasoconstrictive responses. A higher dispersion of values for the
15
hypercapnic gains than for hypocapnic was also observed, suggesting an
increased variability in the response to hypercapnia than to hypocapnia. Since
the tone of cerebral vessels seems to be the function of arterial blood gases, pH,
cerebrospinal fluid composition and nitric oxide [9], it is possible that these
mechanisms might play a differential role during vasodilatory or constrictive
responses.
Neuronal activation is related to increased metabolic activity which demands for
a higher regional blood supply. We observed that there was a significant increase
during 2-Back Task (compared to 1-Back), which was expected since 2-Back is
a more demanding task. The lack of statistical significant differences between
right and left CBFV measurements during NVC tasks suggests that there is a
bilateral activation during this protocol. No correlation between the results of
MoCA test score and NVC gains was found. Similarly, no correlation was found
between NVC and any of the subtotal scores of the tests. Sorond et al
demonstrated that there was a positive association between 2-Back Task
performance and Trail B scores, which specifically tests for executive function
[54]. However, no correlation was found between 2-Back Task performance and
the Mini-mental examination, which assesses global cognitive impairment,
similarly to MoCA test. Consequently, it is possible that more refined and specific
cognitive tests are better predictors of NVC performance. On the other hand, it is
also possible that N-Back Task is not specifically dependent on the cognitive level
of the subject, but rather on the activation status, possibly mediated by the
sympathetic nervous system, once HR and MAP increase during this task. Thus,
it would be interesting to compare our results with outcomes obtained from the
16
application of other NVC protocols which elicit neuronal activation independently
of cognition.
At last we analysed the association between neurovascular stress tests results.
There was a lack of correlation between CVR components, apart from some
occasional findings in the autoregulatory HF domain. Since autoregulation is
thought to be inexistent above 0.30 Hz, these findings lack significance.
One limitation of the Doppler studies is the use CBFV measurements instead of
CBF. However, it is unlikely that the calibre of insonated vessels changed in the
limited time of the procedures, as shown by Serrador et al [55]. On the other
hand, some participants had mild dyslipidaemia and were on pharmacological
control with statins. However, none of them had episodes of vascular disease
and carotid atherosclerosis was excluded by cervical and transcranial ultrasound
studies. Although it is unlikely that these factors had influence in the results, we
cannot exclude the presence of microvascular disease or the presence of CVR
impairment caused by the disease or drug. It is also important to state that we
had a small sample size and, although we did not find evidence of the role of
aging on CVR, data on elderly individuals, especially on those older than 80
years, continues to be sparse.
Overall, our data suggests that neurovascular stress tests measure different
aspects of CVR control and that a full battery might be more useful in future
studies on neurovascular control. It is possible that autonomic, myogenic or
metabolic stimuli might have a differential role in each of CVR components, even
17
if some common mechanisms might exist between themselves. We have also
demonstrated that age and gender do not have an influence in cerebrovascular
regulation or neurovascular stress tests. Being independent of age and cognitive
status, CVR tests seem promising for studying several cerebrovascular
conditions affecting the aging brain. On the other hand, cerebrovascular
regulation did not seem to be affected by MAP, HR or EtCO2. However, even if
fluctuations of these physiological functions might not influence CVR, it seems
important to include them on monitoring routines as a control parameter. The lack
of correlation between protocols’ results supports the need to define gold
standards for each component of CVR and clarify the terminology in use. Thus,
CA, VMR and NVC should not be used interchangeably to describe individual
response to CVR stimuli. Analysis of the mechanisms that underlie CVR, by both
laboratory and imaging studies, are needed to understand the intricate interplay
of factors that are responsible for CBF regulation and their role on pathology.
Conflicts of interest
None.
Acknowledgements
The authors thank Joana Carvalho, PhD, from the Faculty of Sport Sciences and
Physical Education of the University of Porto, and São João Hospital Center
Volunteers Association for their help recruiting participants for the present study.
This study is part of Madureira JP MD thesis.
18
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25
Table 1 – Baseline characteristics stratified by gender
Total Male Female
n 58 28 30
Age, y
21-30 23 (22-26) 24 (22-26) 22 (23-23)
31-40 34 (32-39) 35 (32-39) 33 (32-34)
41-50 46 (41-50) 46 (41-50) 47 (44-50)
51-60 55 (51-60) 56 (55-60) 54 (51-58)
61-70 65 (61-69) 63 (61-66) 66 (62-69)
71-80 75 (71-80) 77 (74-80) 74 (71-78)
BMI, kg.m-2 24.6 ± 3.6 25.1 ± 3.0 24.1 ± 4.0
MoCA test score 26.6 ± 3.1 27.1 ± 2.6 26.2 ± 3.4
SBP, mmHg 125.5 ± 16.3 126.6 ± 11.6 124.5 ± 19.5
DBP, mmHg 77.3 ± 9.1 78.0 ± 8.0 76.8 ± 10.0
MAP, mmHg 93.4 ± 10.7 94.2 ± 8.5 92.7 ± 12.4
HR, bpm 68.8 ± 9.5 69.1 ± 10.9 68.5 ± 8.3
PP, mmHg 61.7 ± 14.6 58.2 ± 15.7 64.6 ± 13.3
EtCO2, mmHg 38.2 ± 2.8 39.0 ± 2.6 37.6 ± 2.9
CVRi, mmHg·cm-1.s-2 1.3 ± 0.3 1.3 ± 0.4 1.2 ± 0.3
All values are given in mean ± SD, except for age which is given in mean
with ranges in parentheses. BMI = Body mass index; MoCA test = Montreal
Cognitive Assessment; SBP = Systolic blood pressure; DBP = Diastolic
blood pressure; MAP = Mean arterial blood pressure; HR = Heart Rate; PP
= Pulse pressure; EtCO2 = End-tidal CO2; CVRi = Cerebrovascular
resistance index.
26
Figure 1 – Transfer function gain (A and B), phase (C and D) and coherence
(E and F) between changes in MAP and mean CBFV during a resting period.
Group-averaged results are shown. Solid lines and shaded regions represent
Mean ± SE. Vertical lines limit the intervals for VLF = Very-low frequencies (0.02–
0.07 Hz); LF = Low-frequencies (0.07–0.20 Hz); HF = High frequencies (0.20-
0.50 Hz). MCA = Middle cerebral artery; MAP = Mean arterial pressure; CBFV =
Cerebral blood flow velocity; a.u. = arbitrary units.
27
Table 2 – Hemodynamic characterisation of age groups: linear regression modelling examining the influence of age and gender on cerebrovascular measurements
Total 21-30 31-40 41-50 51-60 61-70 70-80 Model Age Gender
R2 β p β p
N (M:F ratio) 58 (14:15) 10 (1:1) 10 (1:1) 12 (1:1) 10 (1:1) 7 (3:4) 9 (4:5) -------- -------- -------- -------- -------- Mean CBFV, cm.sec-1 65.67 ± 12.51 73.68 ± 14.85 67.68 ± 8.69 68.94 ± 10.49 63.13 ± 12.16 62.88 ± 11.92 55.80 ± 11.58 0.302** -0.343 <0.001 7.529 0.013 Male 62.05 ± 13.59 70.60 ± 19.08 63.29 ± 7.12 62.39 ± 11.37 60.65 ± 11.71 66.56 ± 18.49 45.81 ± 10.57 0.186* -0.352 0.031 -------- -------- Female 68.91 ± 10.69 76.15 ± 12.28 74.99 ± 5.87 74.39 ± 6.16 65.60 ± 13.43 60.11 ± 5.71 61.79 ± 7.69 0.330* -0.336 0.001 -------- -------- Mean CVRi, mmHg·cm-1.s-2 1.27 ± 0.34 1.10 ± 0.34 1.13 ± 0.28 1.28 ± 0.32 1.30 ± 0.45 1.36 ± 0.28 1.51 ± 0.27 0.183* 0.008 0.002 -0.069 0.434 Male 1.30 ± 0.40 1.15 ± 0.51 1.25 ± 0.30 1.30 ± 0.40 1.32 ± 0.60 1.22 ± 0.26 1.64 ± 0.30 0.107 0.008 0.120 -------- -------- Female 1.25 ± 0.30 1.06 ± 0.20 0.98 ± 0.20 1.27 ± 0.28 1.29 ± 0.36 1.46 ± 0.29 1.42 ± 0.25 0.295* 0.009 0.002 -------- -------- Autorregulation
Coherence, a.u.
VLF 0.47 ± 0.16 0.48 ± 0.17 0.46 ± 0.17 0.42 ± 0.15 0.54 ± 0.12 0.47 ± 0.23 0.49 ± 0.18 0.010 0.001 0.510 -0.015 0.726 LF 0.63 ± 0.16 0.62 ± 0.11 0.68 ± 0.11 0.63 ± 0.20 0.69 ± 0.14 0.56 ± 0.09 0.61 ± 0.22 0.035 -0.001 0.406 0.047 0.254 HF 0.74 ± 0.14 0.74 ± 0.11 0.80 ± 0.06 0.75 ± 0.17 0.71 ± 0.15 0.67 ± 0.20 0.77 ± 0.11 0.019 -0.001 0.524 -0.029 0.439 Gain, cm.sec-1.mmHg-1 VLF 0.68 ± 0.28 0.70 ± 0.23 0.70 ± 0.36 0.68 ± 0.36 0.64 ± 0.18 0.63 ± 0.19 0.71 ± 0.34 0.001 <0.001 0.913 0.013 0.863 LF 1.03 ± 0.29 1.05 ± 0.45 1.12 ± 0.27 1.08 ± 0.27 1.02 ± 0.20 0.91 ± 0.24 0.92 ± 0.28 0.055 -0.004 0.105 0.057 0.460 HF 1.32 ± 0.40 1.41 ± 0.55 1.48 ± 0.52 1.34 ± 0.31 1.30 ± 0.29 1.15 ± 0.15 1.18 ± 0.43 0.071 -0.006 0.052 0.056 0.591 Phase, radius VLF 1.04 ± 0.45 1.05 ± 0.44 0.83 ± 0.52 1.31 ± 0.27 1.20 ± 0.29 0.91 ± 0.53 0.81 ± 0.51 0.025 -0.002 0.483 0.115 0.340 LF 0.63 ± 0.23 0.74 ± 0.20 0.60 ± 0.26 0.56 ± 0.19 0.69 ± 0.24 0.49 ± 0.21 0.65 ± 0.25 0.014 -0.001 0.403 -0.014 0.820 HF 0.17 ± 0.21 0.19 ± 0.17 0.14 ± 0.18 0.13 ± 0.25 0.19 ± 0.23 0.24 ± 0.26 0.15 ± 0.21 0.006 <0.001 0.788 -0.029 0.609 Vasoreactivity Hypercapnia, %.mmHg-1 4.87 ± 1.75 5.15 ± 2.71 4.82 ± 2.35 4.29 ± 1.11 5.56 ± 1.75 4.89 ± 0.96 4.58 ± 0.72 0.015 -0.004 0.793 -0.396 0.402 Hypocapnia, %.mmHg-1 1.74 ± 0.46 1.64 ± 0.61 1.79 ± 0.58 1.84 ± 0.31 1.69 ± 0.38 1.77 ± 0.45 1.66 ± 0.47 0.041 <0.001 0.924 -0.182 0.140 Global, %.mmHg-1 4.19 ± 1.76 4.31 ± 1.29 5.16 ± 3.49 4.03 ± 1.35 4.37 ± 1.1 3.54 ± 0.49 3.55 ± 1.2 0.047 -0.022 0.114 -0.015 0.974 Neurovascular coupling 1-Back gain, %-1 0.22 ± 7.31 4.96 ± 17.12 -0.80 ± 2.45 -1.51 ± 2.21 0.23 ± 3.46 -1.54 ± 2.01 0.07 ± 3.40 0.067 -0.058 0.298 -3.088 0.115 2-Back gain, % -1 6.27 ± 4.64 5.63 ± 4.93 6.10 ± 6.50 7.14 ± 4.80 7.08 ± 3.88 3.41 ± 2.25 7.34 ± 4.00 0.014 -0.001 0.983 1.103 0.384
All values are given as mean ± SD. CBFV = Cerebral blood flow velocity; CVRi = Cerebrovascular resistance index; a.u. = arbitrary units;
VLF = Very-low frequencies (0.02–0.07 Hz); LF = Low-frequencies (0.07–0.20 Hz); HF = High frequencies (0.20–0.50 Hz).
* p value < 0.05
** p value < 0.001
27
28
Figure 2 – Time-course of CBFV (A and D), MAP/HR (B and E) and EtCO2 (C
and F) during the hypercapnic challenge (left) and hyperventilation induced
hypocapnia (right). Graphs of all subjects were synchronized and averaged.
Solid lines and shaded regions represent Mean ± SE. The arrows ( ) in the
horizontal axis mark the beginning and end of each challenge. Vasodilatory
range, which measures the % of variation between the lowest and highest CBFV
values, was 61 ± 16 %. CBFV = Cerebral blood flow velocity; MCA = Middle
cerebral artery; MAP = Mean arterial pressure; HR = Heart rate; EtCO2 = End-
tidal CO2.
29
Table 3 - Correlation between CVR measurements
1 2 3 4 5 6 7 8 9 10 11 12
1 Autoregulation Coherence, a.u. VLF
2 LF 0.11
3 HF -0.02 0.25
4 Gain, cm.sec-1 VLF 0.52** -0.13 -0.06
5 LF -0.23 0.57** 0.16 -0.17
6 HF -0.20 0.30* 0.10 -0.34** 0.65**
7 Phase, radius VLF -0.04 0.09 0.15 -0.09 -0.02 0.05
8 LF -0.14 0.01 -0.03 -0.24 0.14 0.27* 0.17
9 HF 0.18 -0.03 -0.22 -0.11 -0.21 0.10 -0.04 0.37**
10 Vasoreactivity Hypercapnia, %.mmHg-1 0.24 0.05 -0.17 0.16 0.05 0.01 -0.07 0.07 0.04
11 Hypocapnia, %.mmHg-1 -0.22 -0.16 -0.04 -0.02 0.04 -0.02 0.05 0.04 0.04 0.21
12 Global, %.mmHg-1 -0.01 0.14 -0.06 0.10 0.33* 0.32* 0.02 0.06 -0.08 0.41** 0.22
13 Neurovascular coupling 1-Back gain, % 0.16 -0.02 -0.08 -0.04 0.13 0.19 -0.04 0.11 0.19 0.20 0.13 0.07
14 2-Back gain, % -0.02 0.13 -0.01 0.04 0.05 -0.02 -0.18 -0.18 -0.08 0.05 -0.03 -0.01
CVR = Cerebrovascular reactivity; a.u. = arbitrary units; VLF = Very-low frequencies (0.02–0.07 Hz); LF = Low-frequencies (0.07–0.2
Hz); HF = High frequencies (0.2–0. 5).
† Spearman’s correlation coefficient between cerebrovascular measurements is significant at < 0,05
‡ Spearman’s correlation coefficient between cerebrovascular measurements is significant at < 0,01
29
30
Table 4 – MAP, HR and EtCO2 variation during CVR protocols and their correlation with CVR measurements
Resting phase Activation phase Difference (95% CI)
MAP
mmHg
HR
bpm
EtCO2
mmHg
MAP,
mmHg
HR
bpm
EtCO2
mmHg
MAP
mmHg
HR
bmp
EtCO2
mmHg
Autorregulation 80 ± 13 69 ± 9 38 ± 3 -------- -------- -------- -------- -------- --------
Vasoreactivity
Hypercapnia, %.mmHg-1 80 ± 15 68 ± 9 37 ± 4 91 ± 17 68 ± 10 46 ± 4 11 ± 8 † 1 ± 7 † 9 ± 3 †
Hypocapnia, %.mmHg-1 81 ± 15 69 ± 10 36 ± 4 83 ± 17 88 ± 15 19 ± 3 ʄ 2 ± 8 † 20 ± 13† -17 ± 3 †
Neurovascular coupling
1-Back gain, % 88 ± 18 70 ± 12 37 ± 4 88 ± 18 72 ± 12 38 ± 6 0 ± 3 † 1 ± 2 † 1 ± 4 †
2-Back gain, % 87 ± 18 71 ± 12 38 ± 4 90 ± 18 76 ± 14 37 ± 5 3 ± 5 † 5 ± 6 † 0 ± 2 †
All values are given as mean ± SD. MAP = Mean arterial pressure; HR = Heart rate; EtCO2 = End-tidal CO2; CVR = Cerebrovascular
reactivity.
† Paired t test p value for comparisons between resting phase and activation phase monitoring parameters is significant at < 0.001
ʄ Spearman’s correlation coefficient P score for correlations between cerebrovascular measurements and monitoring parameters
is significant at < 0.05
30
31
Figure 3 – Time-course of CBFV (A), MAP/HR (B) and EtCO2 (C) during the
2-Back Task. Graphs of all subjects were synchronized and averaged. Solid lines
and shaded regions represent Mean ± SE. The arrows ( ) in the horizontal axis
mark the beginning and end of the respective challenge. CBFV = Cerebral blood
flow velocity; MCA = Middle cerebral artery; MAP = Mean arterial pressure; HR =
Heart rate; EtCO2 = End-tidal CO2.
32
Appendices
Table A.1 – Influence of age on MoCA scores
Scores Mean 21-30 31-40 41-50 51-60 61-70 70-80 p
MoCA test score 26.57 (17-30) 29.44 (27-30) 27.3 (23-30) 27.91 (22-30) 26.75 (25-28) 24.00 (18-28) 23.11 (17-29) <0.001
Visuospatial/Executive 4.56 (2-5) 4.89 (4-5) 5.00 (5-5) 4.64 (3-5) 4.50 (4-5) 4.29 (2-5) 3.89 (2-5) 0.024
Naming 2.96 (2-3) 3.00 (3-3) 3.00 (3-3) 3.00 (3-3) 3.00 (3-3) 3.00 (3-3) 2.78 (2-3) 0.070
Attention 5.17 (1-6) 5.78 (5-6) 5.50 (4-6) 5.73 (5-6) 5.25 (4-6) 4.43 (2-6) 4.00 (1-6) 0.002
Language 2.11 (0-3) 2.89 (2-3) 2.30 (1-3) 2.27 (1-3) 1.63 (1-3) 1.86 (0-3) 1.56 (1-3) 0.015
Abstraction 1.80 (0-2) 2.00 (2-2) 1.80 (1-2) 1.91 (1-2) 2.00 (2-2) 1.57 (1-2) 1.44 (0-2) 0.046
Delayed recall 4.15 (0-5) 4.78 (3-5) 4.30 (2-5) 4.45 (3-5) 4.38 (3-5) 3.14 (0-5) 3.56 (1-5) 0.044
Orientation 5.92 (5-6) 6.00 (6-6) 6.00 (6-6) 5.91 (5-6) 6.00 (6-6) 5.71 (5-6) 5.89 (5-6) 0.234
All values are given as mean with ranges in parentheses. MoCA = Montreal Cognitive Assessment.
32
33
Table A.2 – Comparison of CVR measurements between right and left MCA
Right MCA Left MCA Mean MCA p
Autorregulation
Coherence, a.u.
VLF 0.48 ± 0.17 0.47 ± 0.17 0.47 ± 0.16 0.530a
LF 0.64 ± 0.15 0.62 ± 0.17 0.63 ± 0.16 0.051a
HF 0.75 ± 0.14 0.74 ± 0.16 0.74 ± 0.14 0.297b
Gain, cm.sec-1.mmHg-1
VLF 0.69 ± 0.30 0.67 ± 0.29 0.68 ± 0.28 0.285b
LF 1.04 ± 0.30 1.01 ± 0.29 1.03 ± 0.29 0.048b
HF 1.33 ± 0.41 1.31 ± 0.41 1.32 ± 0.40 0.592b
Phase, radius
VLF 1.05 ± 0.50 1.02 ± 0.50 1.04 ± 0.45
LF 0.63 ± 0.24 0.62 ± 0.26 0.63 ± 0.23 0.615a
HF 0.17 ± 0.22 0.17 ± 0.22 0.17 ± 0.21 0.690a
Vasoreactivity
Hypercapnia, %.mmHg-1 4.93 ± 1.86 4.80 ± 1.76 4.87 ± 1.75 0.276a
Hypocapnia, %.mmHg-1 1.81 ± 0.63 1.79 ± 0.71 1.74 ± 0.46 0.495a
Neurovascular coupling
1-Back gain, % -0.61 ± 2.90 1.05 ± 13.88 0.22 ± 7.31 0.671b
2-Back gain, % 5.93 ± 4.86 6.61 ± 5.02 6.27 ± 4.64 0.242b
CVR = Cerebrovascular reactivity; MCA = Middle cerebral artery; a.u. =
arbitrary units; VLF = Very-low frequencies (0.02–0.07 Hz); LF = Low-
frequencies (0.07–0.20 Hz); HF = High frequencies (0.20-0.50). a Paired t test p value b Wilcoxon signed-rank test
34
Highlights
No correlation between cerebrovascular reactivity components was found;
Cerebrovascular reactivity variation seems to be independent of age and
gender;
MoCA test does not correlate with neurovascular coupling results;
Results suggest that cerebrovascular reactivity has a functional reserve
with age;
Cerebrovascular reactivity tests seem promising for studying the aging
brain.
35
Annexes
1. Guide for authors
2. São João Hospital Center Ethical Committee Approval
3. MoCA test
2. São João Hospital Center Ethical Committee Approval
Nome: _________________________
Género: __________
Escolaridade: _____
Idade: __________
Data de Nascimento: __________
Data de Avaliação: ____________
VISUO-ESPACIAL / EXECUTIVA Desenhar um Relógio (nove e dez)
(3 pontos)
Contorno Números Ponteiros
Pontos
NOMEAÇÃO
MEMÓRIA Barco Ovo Calças Sofá Roxo
1º ensaio
2º ensaio
Leia a lista de palavras. O sujeito deve repeti-la. Realize dois ensaios. Solicite a evocação da lista 5 minutos mais tarde.
Sem
Pontua-
ção
ATENÇÃO Leia a sequência de números.
(1 número/segundo)
O sujeito deve repetir a sequência.
O sujeito deve repetir a sequência na ordem inversa.
Dia do mês Mês Ano Dia da
semanaLugar Locali-
dadeORIENTAÇÃO
OpcionalPista de categoria
Pista de escolha múltipla
Deve recordar as palavras
SEM PISTAS
EVOCAÇÃO DIFERIDA
ABSTRACÇÃO
LINGUAGEM
Semelhança p.ex. entre banana e laranja = frutos olho - ouvido trompete - piano
Repetir: Ela soube que o advogado dele meteu um processo após o acidente.
As meninas a quem deram muitos doces ficaram com dores de barriga.
Fluência verbal: Dizer o maior número possível de palavras que comecem pela letra “M” (1 minuto).
Leia a série de letras (1 letra/segundo). O sujeito deve bater com a mão cada vez que for dita a letra A. Não se atribuem pontos se > 2 erros.
4 ou 5 subtracções correctas: 3 pontos; 2 ou 3 correctas: 2 pontos; 1 correcta: 1 ponto; 0 correctas: 0 pontos
Subtrair de 7 em 7 começando em 80.
Pontuação
apenas para
evocação
SEM PISTAS
Palavras
VERSÃO PORTUGUESA 7.3 – VERSÃO ALTERNATIVA
Examinador: _______________
Versão Portuguesa: Freitas, S., Simões, M. R., Santana, I., Martins, C. & Nasreddine, Z. (2013). Montreal Cognitive
Assessment (MoCA): Versão 3. Coimbra: Faculdade de Psicologia e de Ciências da Educação da Universidade de Coimbra.
Copiar o cilindro
5 4 1 8 7
1 7 4
73 66 59 52 45
Barco Ovo Calças Sofá Roxo
Início
Fim
3. MoCA test
36
Appendix
1. Medical Questionnaire
Assessment of cerebral vasoreactivity with
transcranial doppler in healthy portuguese adults
Cardiovascular R&D Unit (UnIC) Faculdade de Medicina da Universidade do Porto | Centro Hospitalar de São João
INCLUSION AND EXCLUSION QUESTIONNAIRE
File number:
Date of information retrieval:
Patient information
Gender:
Date of birth:
Place of birth:
Address:
Level of education:
Contact:
Anthropometry
Height:
Weight:
BMI:
Neurocognitive analysis
Please proceed to the cognitive evaluation of the subject using MOCA test. Attach the test file to this document. MOCA
score: /30
Medical history
Risk factors: Diabetes or anti-diabetic medication
Hypertension or anti-hypertension medication Smoking:
Dyslipidemia
Alcohol consumption
1. Medical Questionnaire
Neurological system:
Past illnesses:
Chronic conditions:
Eyes:
Past illnesses:
Chronic conditions:
Cardiovascular and respiratory systems:
Past illnesses:
Chronic conditions:
Psychiatric:
Past illnesses:
Chronic conditions:
Other:
Hospitalizations:
Trauma:
Medications
List any prescription medications
Current:
Past:
Family history
Please list any relevant familiar conditions (include grandparents, aunts and uncles, but exclude cousins, relatives by marriage). Exclude history
of neurovascular diseases.
Past:
Final comments: