Zohaib Iqbal1 and M. Albert Thomas1
1Radiological Sciences, University of California - Los Angeles, Los Angeles, CA, United States
Synopsis
Measuring the transverse relaxation times (T2s)
of metabolites from different regions of the brain provides important insight
into different pathologies, but requires long acquisition. A novel k-space
acquisition using a hybrid technique involving both echo planar spectroscopic
imaging (EPSI) and concentrically circular echo planar trajectories (SI-CONCEPT) was
applied to simulated brain tumor spectroscopic imaging data. In addition, an
algorithm incorporating the backprojection information from the EPSI scan was
developed to enhance the spectroscopic images. This novel acquisition and
reconstruction technique, called SI-WEB, decreases the total duration of the
scan while producing similar results when compared to the true T2
spectroscopic images. Purpose:
It has been
shown that T
2 values of brain metabolites, including N-acetyl
aspartate (NAA) are altered in different pathologies such as brain tumor
1,2.
These studies have used Point resolved spectroscopy (PRESS) for single voxel
localization
3. Spectroscopic imaging
4 requires an
enormous amount of time even with the use of an echo planar bipolar gradient
for readout
5,6, and this may be the primary reason why T
2
spectroscopic imaging is not implemented in vivo. The purpose of
this study is to investigate the feasibility of a new type of k-space
acquisition, which uses both echo planar spectroscopic imaging (EPSI) and spectroscopic
imaging using concentrically circular echo planar trajectories (SI-CONCEPT)
7.
This type of acquisition has the potential to reduce scan time by two (2x) or
three (3x) fold. In order to improve the quality of metabolite maps,
backprojections from the acquired EPSI lines are used to reconstruct the images.
This method, called
spectroscopic
imaging
with
enhancement
by utilizing
backprojections
(SI-WEB), is applied to a virtual brain cancer phantom to assess performance.
Methods
Phantom: The virtual NAA
phantom was simulated to replicate a slice with a spatial resolution of 32x32
with the characteristics of a glioma patient. Multi-voxel NAA spectra were simulated
for B0 = 3T containing 512 temporal points (t) and a spectral
bandwidth of 1190Hz. NAA concentration was chosen to be uniform throughout the
brain phantom and decreased in the location of the tumor by a factor of two,
and was simulated for three TE values (TE= 30, 90, 180ms). The T2 of
the healthy tissue was set to 350ms and the T2 of the region
mimicking the cancer tissue was set to 250ms (usually a 2x2 or 3x3 region of
the tumor). These T2 values are similar to those reported in the
literature2. Ten phantoms with different tumor locations were
simulated and tested.
SI-WEB
acquisition:
The 2x SI-WEB sampling scheme can be seen in Figure 1. It is clear that k-space
is only partially acquired using ten EPSI phase encoding lines (in red) and six
SI-CONCEPT phase encoding lines (in blue). For the 3x SI-WEB mask (Figure 2), 6
EPSI and 4 SI-CONCEPT phase encoding lines are acquired.
Reconstruction
using Backprojections: Two backprojections were acquired using EPSI: kx = 17 and ky = 17 lines.
These two backprojections (0º and 90º) were used to ensure the data was
consistent using the following optimization: $$\min_{X}\|MX-K\|_2^2+\lambda\sum_{b=1}^2\|X_{b}-K_{b}\|_2^2$$ M, X, K, λ, Xb,
and Kb are the sampling mask, reconstructed data, acquired data,
regularization term, projection of the reconstructed data along either 0º or
90º, and the acquired backprojection along either 0º or 90º respectfully. Essentially,
the first term acted as a data fidelity term and the second term ensured
consistency between the backprojections and reconstructed data. T2
maps were created by fitting the three NAA maps to $$$e^{-{TE}/T_2}$$$.
Quality Evaluation: Normalized root mean
square error (nRMSE) images were calculated between the T2 maps of the
virtual phantom (truth) and the 2x and 3x SI-WEB NAA maps. Qualitative comparisons
were also made between the virtual phantoms and reconstructed SI-WEB maps at
each simulated TE.
Results
A comparison
between the virtual phantom and the reconstructed 2x SI-WEB at each TE can be
seen in Figure 3A. Figure 3B shows the resulting NAA T
2 maps by
fitting the three TE points for the virtual phantom and 2x SI-WEB acquisition.
Figure 4 shows the T
2 maps of the virtual phantom (A), 2x SI-WEB
(B), 3x SI-WEB (C), as well as the nRMSE for the 2x SI-WEB (D) and 3x SI-WEB
(E). The largest error in the region of the glioma for the 2x SI-WEB was 16%
and was 26% for the 3x SI-WEB for this particular phantom, whereas the smallest
error in the region of the lesion was 5% for the 2x SI-WEB and 23% for the 3x
SI-WEB. Other phantoms yielded very similar results.
Discussion and Conclusion
For ten
different versions of the virtual phantom, twice and thrice accelerated (2x and
3x) SI-WEB showed similar NAA T
2 maps when compared to the true T
2
maps. The reconstruction employed here helped minimize noise where signal was
not present, and this type of reconstruction would yield better results if more
backprojections were used. Future work will focus on applying this method in
human brain to validate this technique in vivo.
Acknowledgements
NIH R21 Grant
(NS080649-02)References
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