Alex Bhogal1, Jill B de Vis1, Jeroen C.W. Siero1, Esben T Petersen2, Peter R. Luijten1, Jeroen Hendrikse1, Marielle E.P. Philippens3, and Hans Hoogduin4
1Radiology, UMC Utrecht, Utrecht, Netherlands, 2Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark, 3Radiotherapy, UMC Utrecht, Utrecht, Netherlands, 4Utrecht, Netherlands
Synopsis
Characterizing
healthy, age-related changes in the BOLD-CVR response can provide a reference
point from which to distinguish abnormal CVR from the otherwise normal effects
of ageing. In this study, we
examine age-dependent differences in grey and white matter BOLD-CVR
response to progressive hypercapnia between young and elderly subjects. Introduction
Blood Oxygenation Level Dependent (BOLD) imaging in combination with
vasoactive stimuli can be used to probe cerebrovascular reactivity (CVR)[1]. Characterizing healthy, age-related changes
in the BOLD-CVR response can provide a reference point from which to
distinguish abnormal CVR from the otherwise normal effects of ageing. In this study, we examine age-dependent differences
in grey and white matter (GM/WM) BOLD-CVR response to progressive hypercapnia
between young and elderly subjects. Furthermore, we incorporate differences in
baseline T2* information to broaden our interpretation of the BOLD-CVR
response.
Materials & Methods
This study was approved by the Medical Ethics Committee of our
institution and informed consent was obtained from all subjects. Dual-echo
pseudo-continuous ASL (pCASL) data
(flip angle: 90, reconstructed resolution: 3 x 3mm2, slice
thickness: 7mm, slice gap: 1mm, TR: 4 s, TE1/TE2: 13.84/36.28 ms, FOV: 240 x
240 x 87 mm3, slices: 11, volumes: 140, label duration: 1650 ms, post-label
delay: 1550 – 2185 ms ) was acquired on a Philips 3T system. Scans were
performed in 16 young (28 ±3 years) and 30 elderly subjects ( 66 ±4 years). The computer controlled breathing
challenge (RespirAct, Thornhill Research, Toronto) was as follows: (1) 2min
baseline; (2) 75s hypercapnic ramp; (3) 100s plateau; (4) 2min baseline [2]. Since
the interest of this work lies in the BOLD signal/T2* response to
progressive hypercapnia, the ramp data was isolated for data analysis
T2* maps were generated via mono-exponential fitting of the
multi-echo data. Motion correction was performed (FSL-MCFLIRT) on the first
echo data and the resulting transformations were applied to second echo and T2*
data. GM/WM
masks were created as outlined in Fig 1. BOLD data was computed using a running
averaging which combined label/control dual-echo data. BOLD data was detrended using a linear fit to the pre/post-stimulusbaseline signal. PetCO2
traces were temporally aligned with BOLD data (normalized to baseline BOLD
signal) and the resulting BOLD-CVR curves were fit to the following sigmoidal
model [3]:
$$
\%\Delta BOLD= Initial\ Signal\
Amplitude + \frac{Sigmoid\ Span}{1+e^{\frac{-(PetCO_2-Sigmoid\
Midpoint)}{Linear\ Portion\ About\ Midpoint}}}
$$
Inter-subject normalization was done by calculating the mean response
curve as a function of PetCO2 increases from baseline (fig 2B/C) for
the young and elderly groups respectively [4]. Sigmoidal fitting and alignment
of T2* timeseries data was
performed in a similar manner .
Results
The range of
ΔPetCO
2 values surveyed were 6.9±2.2 mmHg and 6.1±1.3 mmHg for young
and elderly, respectively (no significant difference; p = 0.13). The GM and WM
BOLD-CVR response began displaying non-linear above approximately 4mmHg PetCO
2
from baseline (fig 3B). The initial slope of the GM response appeared
steeper in young subjects (fig 3B), while the point at which GM CVR was most
sensitive to changes in PetCO
2 was shifted to higher PetCO
2
values (from baseline) in elderly subjects (fig 4B). Overall GM CVR was
reduced amongst elderly (0.19±0.06 %ΔBOLD/mmHg) as compared with young subjects (0.26±0.07 %ΔBOLD/mmHg) (p<0.002),
while that in WM showed no significant differences (0.04±0.02 and 0.05±0.03 %ΔBOLD/mmHg for young
and old, respectively (p = 0.12)). GM/WM baseline T2* values were
48.0±2.2/49.7±3.6 ms and 50.9±3.0/ 54.6±3.2 ms (GM/WM significantly different:
p<0.002/p < 0.0001) for young and elderly subjects, respectively. The difference
between elderly GM and WM T2* values did reach statistical
significance (p< 0.0001), while those between young subjects did not (p =
0.12). Absolute T2* under hypercapnia
increased in both subject groups (Fig 3A).
Discussion & Conclusion
Our main findings were the amplitude of the BOLD-CVR response to
progressive hypercapnia was reduced in elderly subjects. More novel, was the
observation that the shape of the GM BOLD-CVR response curve showed age
dependent changes relating to PetCO
2 sensitivity, while that in WM
did not (fig 3). Finally, baseline T2* values were higher in elderly
subjects, suggesting increased partial volume effects with CSF, higher venous
oxygen saturation or B
0 related susceptibility effects. Elevated
baseline T2* translates into a brighter baseline BOLD signal that
may lead to an apparent reduction in the BOLD-CVR response upon normalization [5].
Baseline T2* can be modulated by increased partial voluming between
tissue and CSF resulting from atrophy of the cortex and enlargement of
peri-vascular spaces. Inhomogeneous tissue loss and variable decreases in
regional microvascular density may further explain
the differences seen in the age-dependent GM/WM CVR response. Finally,
morphological changes in the composition of control vessels may restrict the
sensitivity of the vasculature to changes in PetCO
2. These include
thickening of the basement layer, reductions in smooth muscle content and
increases in fibrous tissue within arterial walls [6]. The combined effect of
these changes is stiffening of the vasculature, which will modulate the CVR
response.
Acknowledgements
This study was part of
the EU Artemis High Profile project.References
[1] Lythgoe et
al., MRI 1999 [2] de Vis et al., HBM 2015 [3] Bhogal et al., Neuroimage 2014
[4] Bhogal et al., Neuroimage 2015 [4] Blockley et al., NMR in BioMed 2012, [5]
Farkas et al., Progress in Neurobiology 2001