Shi Su1, Yanan Ren1, Caiyun Shi1, Xiaoyong Zhang1,2, Hairong Zheng1, Xin Liu1, and Guoxi Xie1
1Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, People's Republic of, 2Centers for Biomedical Engineering, College of Information Science and Technology, University of Science and Technology of China, Hefei, China, People's Republic of
Synopsis
T2* mapping provides a means to
quantitatively estimate the iron load of tissue, which is closely related to
numerous diseases, such as thalassemia, hereditary
hemochromatosis and sickle cell disease. However, blood signal would
induce artifacts which lead to T2* estimation inaccurate. To address this
issue, a novel black-blood T2* mapping technique utilizing Delay Alternating
with Nutation for Tailored Excitation (DANTE) preparation module followed by
multi-echo gradient echo (GRE) readout (DANTE-GRE) was developed to obtain
blood suppressed T2* maps. The proposed method is shown to acquire more
accurate T2* maps due to its high SNR and effective blood
signal suppression.Introduction
T2* mapping can directly quantify the iron load of tissue, which is
closely related to numerous diseases, such as thalassemia, hereditary hemochromatosis and sickle cell disease. However, blood
signal would induce artifacts which lead to T2* estimation inaccurate. To
address this issue, a novel black-blood T2* mapping technique utilizing Delay
Alternating with Nutation for Tailored Excitation (DANTE) preparation module
(1)
followed by multi-echo gradient echo (GRE) readout (DANTE-GRE) was developed to
acquire more accurate T2* maps.
Purpose
To eliminate the artifacts
originating from flowing blood by effectively suppressing blood signal,
consequently, to acquire accurately black-blood T2* map.
Methods
Figure 1 shows the sequence diagram of DANTE-GRE. The DANTE preparation module is
followed by multi-echo GRE readouts to sample ten images with different
contrasts in one TR.
To testify the accuracy of T2* map obtained by
DANTE-GRE, both phantom and in vivo experiments were conducted on a 3T scanner
(Siemens Tim Trio, Germany), and compared with those obtained by Motion-Sensitive Driven Equilibrium (MSDE) prepared
multi-echo GRE readout (MSDE-GRE) (2) and conventional GRE.
In the phantom experiments, five SPIO solutions with
different concentrations of 0.05 mmol/L, 0.08 mmol/L, 0.10 mmol/L, 0.15 mmol/L
and 0.20 mmol/L, were mapped. Two groups of parameters for the DANTE module
were conducted. The first one was to fix the pulse train length as 80 and vary
the pulse flip angle from 10° to 20°. While the second one was to fix the pulse
flip angle as 15° and vary the pulse train length from 25 to 150. For
comparison, MSDE-GRE and conventional GRE were also conducted. The field of
speed (FOS) for MSDE-GRE were set to 10 cm/s, 15 cm/s, 20 cm/s, 30
cm/s, 50 cm/s and 75 cm/s, respectively. The same parameters for the GRE readout were used for above
experiments: TR’ = 300 ms and Tes = 49.5 ms. TEs ranged
from 1.62 ms to 64.62 ms with gap 7 ms.
In the in vivo
experiments, 12 healthy volunteers (5 males and 7 females) were recruited, and
7 of them were randomly chosen for neck scan and the others for lower limb
scan. Parameters for the neck scan included: DANTE pulse flip angle of 15° and
pulse train length of 80. GRE repetition time TR' of 300 ms and echo space Tes
of 50.4 ms. TEs ranging from 1.62 ms to 46.62 ms with gap of 5 ms. Voxel size
of 0.7×0.7×2 mm3, GRE
flip angle of 30° and averages of 3. Parameters for the lower limb scan were:
DANTE pulse flip angle of 15° and pulse train length of 100. GRE repetition
time TR' of 300 ms and echo space Tes of 49.5 ms. TEs ranging from 1.4 ms to
46.4 ms with gap of 5 ms. Voxel size of 1.1×1.1×3 mm3,
GRE flip angle of 40° and averages of 3. For MSDE-GRE and convertional GRE, the
same parameters of GRE readout as those of DANTE-GRE were used. And the FOS of
37 cm/s was used for MSDE-GRE.
T2* maps acquired in all
experiments were calculated by fitting ten images to a three-parameter model $$$S_{i}=A\cdot{exp(-TE_{i}/T_2^*)}+C$$$, where
Si represents the sampled
signal intensity,
A is the signal amplitude and
C is used to fit the noise.
Levenberg-Marquardt algorithm in MATLAB was utilized to solve the above
function.
Results and Discussions
Phantom experiments
validate the superiority of DANTE-GRE over MSDE-GRE in acquiring less
deteriorated maps (Figure 2a-c) because it provides higher SNR. Generally,
quantitative analysis (Table 1) shows that T2* values calculated from DANTE-GRE
and MSDE-GRE are smaller than GRE. However, DANTE-GRE calculated T2* values own
smaller differences to GRE than MSDE-GRE. Moreover, standard deviations of
DANTE-GRE are larger than GRE while smaller than MSDE-GRE in most cases. In the
in vivo experiments, DANTE-GRE own better performance in suppressing signal
from slow flowing blood than MSDE-GRE (Figure 3a). Images acquired by DANTE-GRE
display much higher SNR than those of MSDE-GRE, even though lower than those of
GRE (Figure 3a and 4a). Additionally, T2* maps acquired by DANTE-GRE from both
neck and lower limb scans show more homogeneity than those by MSDE-GRE and GRE
with less noise points around flow blood and muscle area.
Conclusion
Accurate T2* maps are obtained by DANTE-GRE due to its high SNR and
effective blood signal suppression. Both the phantom and in vivo experiments
demonstrated that DANTE-GRE may outperform MSDE-GRE and conventional GRE for
T2* mapping.
Acknowledgements
This work was supported in part by the International Cooperation and
Exchange of the National Science Foundation of China (No. 81328013, No.
81120108012), the National Natural Science Foundation of China (No. 81571669,
No. 61201442, No.81501463), and the Natural Science Foundation of Shenzhen (No.
GJHZ20150316143320494, No. JCYJ20140417113430603, No. KQCX2015033117354154).References
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