Fan Qiuju1, Tan Hui1, Yang Zhen1, Yu Nan1, Yu Yong1, Wang Shaoyu2, Xue Yu3, and Li Yue3
1Affiliated Hospital of Shaanxi University of Chinese Medicine, Shaanxi, China, 2MR senior scientific marketing specialist, Shaanxi, China, 3Shaanxi University of Chinese Medicine, Shaanxi, China
Synopsis
This
study aimed to quantitative
measurement of cerebral blood flow in different brain regions of different
levels of blood pressure by mTI ASL. In the first part of this study, we evaluated the
reproducibility of mTI-ASL in healthy subjects, and then mTI-ASL was used to
evaluate 55 primary hypertension patients. There was no major variation between
two consecutive mTI-ASL measurements in healthy volunteers. Furthermore, the
rCBF and ATT values provided valuable information for the classification of
hypertension, which can be used as a non-invasive quantitative monitoring MRI
tool for hypertension progression.
Introduction
Hypertension influence brain by microvascular brain injury and induces
cerebrovascular remodeling, but its direct influence on the cerebral
circulation is not fully clear. The aim of this study was to quantitative
measurement of cerebral blood flow in different brain regions of different
levels of blood pressure by multi-TI arterial spin labeling (mTI-ASL) at 3 T
MRI.Methods
Twenty
healthy volunteers (10 male; mean age, 45 years; test-time blood pressure (BP)
=110±11/73±8mmHg) and fifty-five patients with hypertension (30 male; mean age,
46 years; test-time BP=162±21 /99±10mmHg) were consecutively recruited in this
study. All the MRI examination were performed on a 3T MR scanner (MAGNETOM
Skyra, Siemens Healthcare, Erlangen, Germany) with a 32-channel head coil. The patients were divided into three groups
according to the systolic blood pressure (SBP): grade 1 (n=20, SBP=149±10mmHg),
grade 2 (n=20, SBP=171±9mmHg), grade 3 (n=15, SBP=187±8mmHg). The mTI-ASL
images were acquired with the following parameters: TR/TE =3200/26 ms, FOV =
220×220 mm2, slice thickness = 4 mm, slices = 30, 4 TIs from 1000 to
2500 ms, and total acquisition time was 5 min. The relative cerebral blood flow
(rCBF) and arterial transit time (ATT) values in various regions of interest
(ROIs) were extracted from gray matter (frontal lobe, temporal lobe and
occipital lobe), white matter(bilateral centrum semiovale, anterior and
posterior horns of paraventricular white matter, genu and spleniu of
corpus callosum), basal ganglia and thalamus. Independent-sample t test were
performed to evaluate the significance of the inter-group difference in rCBF
and ATT.Results
The
rCBF was negatively correlated to BP,and ATT values, but positively correlated to BP. Except
for the gray matter (frontal lobe, temporal lobe and occipital lobe), grade 1
hypertension patient showed significantly lower rCBF and ATT than the control
group in each brain region (P<0.05). Compared with grade 1 hypertension, no
significant differences of rCBF in bilateral centrum semiovale and corpus
callosum, and the ATT in the bilateral centrum semiovale were found between
patients with grade 1 and 2 hypertension(P > 0.05). Compared with grade 2, in addition to the
anterior and posterior horns of paraventricular white matter, there were
statistical differences in rCBF and ATT values of the other brain regions in
grade 3 [YX1] (P < 0.05).
[YX1]Look strangeDiscussion
Assessment of cerebral blood flow is of particular
interest in hypertension due to the risk of microvascular brain injury and
induces cerebrovascular remodeling. The traditional ASL has only one inversion
time (TI). If the TI is not properly set, the marked arterial blood has not
fully reached or has passed the imaging plane, resulting in decrease of CBF
value. Our results suggested that
the rCBF and ATT values obtained by mTI-ASL could quantitative reflect of the
cerebral hemodynamics change in patients with hypertension.Conclusion
mTI-ASL has the ability to detect subtle hemodynamic
abnormalities in hypertension at different stage. Quantitative rCBF and ATT
values usage as a biomarker for disease progression in hypertension is
potentially a powerful tool for longitudinal patient monitoring.Acknowledgements
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