Yuki Kanazawa1, Toshiaki Sasaki2, Hiroaki Hayashi1, Kotaro Baba3, Ikuho Kosaka3, Yuki Matsumoto4, Mitsuharu Miyoshi5, and Masafumi Harada1
1Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan, 2Department of Radiology, Uji Tokushukai Hospital, Uji, Japan, 3School of Health Sciences, Tokushima University, Tokushima, Japan, 4Graduate school of Health Science, Tokushima University, Tokushima, Japan, 5Global MR Applications and Workflow, GE Healthcare Japan, Hino, Japan
Synopsis
The purpose of this study is
to develop a T1 mapping
method derived from the variable flip angle with an MT pulse. T1 mapping of the brain with an
MT pulse was performed in five healthy subjects. The mean T1_MT values were significantly decrease than the T1 in all regions (P < 0.05). The difference of T1 and T1_MT in deep gray matter (included caudate nucleus and
putamen) were more decreased than those in white matter. In conclusion, determination of T1 with MT pulse makes it
possible to obtain more detailed information of the macromolecular pool and the
free water pool.
Introduction
The magnetization transfer (MT) effect is cross relaxation and/or spin
exchange between mobile protons, i.e., bulk water and a proton. The magnetization transfer ratio (MTR) has been used as an index to
express the degree of signal attenuation by the MT effect1. MTR is
calculated using the ratio of water signal intensities between an MT pulse and
without. However, characterization of tissue with the MTR could not be evaluated
simply because the MTR value changes due to variations in pulse sequence,
imaging parameter and saturation pulse; the MTR is recognized as a semi-quantitative
method. Some quantitative MT (qMT) imaging reports have been published. The measurement
method of both T1 and MT
derived from selective inversion recovery (SIR) sequence was developed2;
only inversion times are varied while maintaining a constant delay between
repetition time (TR). Consequently, T1 is calculated using mono-exponential fitting, and qMT parameters are
calculated by bi-exponential fitting. Using this method, brain tumors of a rat
model in vivo had significantly
different T1 relaxation
and MT parameters, i.e., the macromolecular pool to the free water pool ratio3.
On the other hand, the pulse sequence having a multi-refocusing flip angle
(FA), e.g., fast spin-echo method, tends to cause high- specific absorption
rate (SAR). Now, we are focused on T1
mapping with a variable FA (VFA) derived from a gradient-echo sequence.Purpose
To assess
the relationship between T1
and MT effect in the human brain, we developed a T1 mapping method derived
from a VFA with MT pulse. Materials and Methods
On a
3.0 T magnetic resonance system (Discovery 750, GE Healthcare), T1 mapping of the brain with
MT pulse was performed in healthy volunteers (five men; ages, 21-26 years; mean
age, 23.8 years). An MR dataset was acquired with spoiled gradient-echo (SPGR)
sequence with MT pulse and without (offset frequency, 800 Hz). The imaging
parameters were 4.9 ms echo time, 500 ms TR, three FA (20, 40, and 80 degrees),
244.1 Hz/pixel bandwidth, 6 mm slice thickness, 192 × 256 matrix, and 25.6 cm
field of view. Moreover, B1
inhomogeneity correction was applied to each dataset. B1 correction was derived from the double angle method. This
method uses the MR images of two FA using a gradient echo (GRE) sequence. The dataset
for B1 correction were
acquired with 2000 ms TR, 5.8 ms TE, 40 degrees FA α, and 80 degrees FA 2α. The
B1 correction is given by
$$B_1^{flip\,angle}=\arccos\left(\frac{S_{2\alpha}}{2S_{\alpha}}\right)$$,
where Sα and S2α are the signal intensities of α and 2α FA data,
respectively. Then, calculated B1
was applied to pixel by pixel of MR imaging data. After B1 correction was performed, T1 or T1_MT
were derived from VFA datasets with MT pulse and without as follows:
$$S_{SPGR}=M_{0}\sin\alpha\left(\frac{1-\exp\left(-\frac{TR}{T_{1}}\right)}{1-\exp\left(-\frac{TR}{T_{1}}\right)\cos\alpha}\right)$$
$$\therefore \left[M_{0},T_{1} \right]=arg\min_{M_{0},T_{1} }\left(\sum_{i=1}^{N_{SPGR}}\left(s_{SPGR,i}-S_{SPGR,i}\left(\alpha_{i}\right)\right)^{2}\right)$$
where $$$S_{SPGR,i}$$$ is the MR signal of each FA after B1 correction, $$$s_{SPGR,i}$$$ is the theoretical signal value. Then, using
varying α values, a nonlinear curve fitting procedure could yield an estimation
of parameters (M0 and T1 or T1_MT)
according to the relationship between MR signal and TE. Then, T1,
T1_MT and MTR maps were
calculated from each dataset. After setting regions of interest (ROIs) on white
matter, gray matter, caudate nucleus, and putamen for each subject (Fig.1), we
measured the mean T1 values
and its standard deviation (SD). Measurements of T1 and T1_MT
were compared for each region.
Results and Discussion
Table 1
summarizes the measurement of each T1
value in white matter, gray matter, caudate nucleus, and putamen in healthy subjects.
Figure 2 shows MTR maps of each flip angle of a representative subject. Figure
3 and 4 show T1 maps
derived from the VFA method with MT pulse and without for each represented
subject.
The mean T1_MT values were
significantly decreased compared to the T1
in all regions (P < 0.05). Difference
in T1 and T1_MT of deep gray matter (included
caudate nucleus and putamen) shows higher than that of white matter. On the
other hand, the MTR map showed the appearance of an inhomogeneous high-signal field around
the center of the brain even though B1
correction was applied (white allows in Fig. 2). The MT pulse with mono-frequency
may cause B1 inhomogeneity;
an MTR map may need a correction method using various B1 offset frequencies. Thus, the
VFA method with MT pulse enabled to us to obtain a quantitatively uniform image
with a mono-frequency MT pulse. Conclusion
Determination
of T1 with MT pulse makes
it possible to obtain more detailed information for the macromolecular pool and
the free water pool, e.g., myelin water fraction.Acknowledgements
No acknowledgement found.References
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