Rajakumar Nagarajan1, Zohaib Iqbal1, Manoj K Sarma1, Mario Guerrero 2, Vanessa Correa 2, Eric S Daar2, and M.Albert Thomas1
1Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, 2Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA, United States
Synopsis
HIV
affects more than 1 million individuals In the US and over 40 million people
worldwide. CNS is commonly involved in the early stage HIV infection. Conventional
3D MRSI is time-consuming because it involves a large number of phase
encodings. EPSI approaches have been used to reduce the long acquisition time
required for multiple spatial encoding steps. In our study, non-uniformly undersampled (NUS) semi LASER based 3D
EPSI was used to quantitate changes in brain metabolites, NAA, Cr, Cho and
myo-inositol in a group of HIV adults in comparison to age matched control
sample using compressed sensing reconstruction by minimizing total variation.Purpose/Introduction
Human immunodeficiency virus (HIV) affects more than 1
million individuals in the United States (US) and over 40 million people
worldwide (1). Central nervous system (CNS) is commonly involved in the early
stage of HIV infection. Magnetic resonance spectroscopy (MRS) offers a valuable
method for monitoring HIV-associated neuropathologic changes (2-4). MRS measures may detect subtle early changes associated
with HIV infection, and concentrations or ratios of cerebral metabolites
measured by MRS could be used as a quantitative indicator of the CNS involvement
(5, 6). Echo planar spectroscopic imaging (EPSI) enables
acceleration of MR Spectroscopic Imaging (MRSI) using conventional phase-encoding
gradients for spatial encoding. However, one of the drawbacks of the EPSI
technique is due to lower sensitivity compared to conventional MRSI. Reduced MRS
sensitivity of low concentrated brain metabolites limit the applicability of
parallel imaging. Conversely, Compressed Sensing (CS) is a technique for
accelerating the inherently slow data acquisition process, and is well suited
for MRSI due to its intrinsic denoising effect. In this study, semi LASER based
non-uniform undersampling (NUS) three dimensional (3D) EPSI was used to
quantitate changes in brain metabolites, N-acetyl aspartate (NAA), total creatine
(Cr), total-choline (Cho), glutamate and glutamine (Glx), and myo-inositol (mI)
in a group of HIV-infected adults in comparison to a matched control group using
compressed sensing reconstruction by minimizing total variation.
Materials and Methods
The
NUS based 3D EPSI sequence was evaluated cross-sectionally in 15 HIV-infected
adults (mean age 45.1 years) and five healthy controls (mean age 51.0 years) using
3T MRI scanner (Siemens Medical Systems, Germany) with 16-channel head
‘receive’ coil. Reliability was assessed by test –retest studies of brain
phantom (10 measurements). CS reconstruction was then performed by solving the total variation
minimization problem using the linearized Bregman iteration. The 3D EPSI
parameters were: FOV = 240x240x120 mm
3, image matrix = 32x32x8,
spectral width = 1190 Hz, number of spectral points = 256, TE = 41ms, TR =
1.5s, Avg=12. Data acquisition was 20 minutes long including water-suppressed (WS)
and non-water-suppressed (NWS) scans. The NWS scan was used to perform eddy
current and spectral phase correction. Acceleration by a factor of 4 (4X NUS)
scheme was imposed along the two spatial dimensions (k
y and k
z). Extractable
individual voxel volume in human brain was 0.84ml. The phantom, HIV and healthy
brain 3D EPSI data were extracted and post-processed using homebuilt
MATLAB-based (The Mathworks, Natick, MA, USA) library of programs. The full
width at half maximum (FWHM) of HIV adults and healthy controls were
approximately 18Hz. A p-value of <0.05 was considered significant.
Results
Fig.1a shows an axial MRI and semi LASER NUS
based 3D EPSI voxel placement in the brain of a 50 year old HIV patient.
Fig.1b.shows extracted spectra from the selected voxels marked in Fig.1a (0.84ml). Fig.2.
shows the right frontal and right parietal metabolites ratios of HIV patients
and healthy controls. Fig.3 shows the metabolites ratios of the right and left
basal ganglia regions of HIV patients and healthy controls. Metabolite ratios
with respect to Cr of semi-LASER NUS based 3D EPSI 4X compared with phantom
concentration are also shown in Fig 4. Creatine and phosphocreatine are widely considered to be unchanged
in numerous brain pathologies. However previous reports indicated changes in this metabolite levels. Metabolites were quantified in the following locations: right
frontal, left frontal, right parietal, left parietal, right basal ganglia, left
basal ganglia, right occipital, and left occipital. Significant metabolite
changes were observed in HIV infected adults in the following locations: Declined
NAA/Cr in the right frontal and right parietal elevated Cho/Cr in the right
basal ganglia and elevated Glx/Cr and mI/Cr in the left basal ganglia. Similar changes were observed with the choline ratios also.
Discussion
By
using NUS based 3D EPSI, we observed decreased NAA and increased mI, which provides evidence for both chronic
neuroinflammation and neuronal injury, which is consistent with earlier
findings (7). A decrease in NAA is detected in many diseases characterized by
neuronal damage, such as stroke and multiple sclerosis (8, 9). Myoinositol is
present mainly in glial cells and considered to be an important brain osmolyte.
Increased Cho levels may be due to increased cell membrane turnover, which may result
from cellular injury and increased glial proliferation. Glx, a major brain
excitatory neurotransmitter, is associated with HIV-induced neurotoxicity where
excessive activation of N-methyl-D-aspartate receptors results in increased
extracellular Glx and neuronal cell death.
Conclusion
This pilot study confirms evidence that
there are neurometabolic differences between HIV adults and healthy controls using
non-uniformly undersampled compressed sensing based EPSI.
Acknowledgements
Authors
acknowledge the support by NIH/NINDS: (#1R21NS086449-01A1).References
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