Zhuozhi Dai1,2, Phillip Zhe Sun3, Gang Xiao4, Gen Yan2, Yanlong Jia2, Zhiwei Shen5, Alan H. Wilman1, and Renhua Wu2,5
1Biomedical engineering, University of Alberta, Edmonton, AB, Canada, 2Medical Imaging, 2nd Affiliated Hospital of Shantou University Medical College, Shantou, China, People's Republic of, 3Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH and Harvard Medical School, Charlestown, MA, United States, 4Math and Information Technology, Hanshan Normal University, Chaozhou, China, People's Republic of, 5Provincial key laboratory of medical molecular imaging, Shantou, China, People's Republic of
Synopsis
pH
is a very important biochemical property that changes in many pathological
states. Monitoring pH is of significance in early diagnosis and treatment
therapy. However, there is lack of non-invasive methods to image pH in vivo
effectively. Our study quantified the pH value using a chemical exchange
saturation transfer (CEST) method in rat brain and established a strong
correlation of pH between CEST and 31P-MRS in vivo, Pearson correlation factor
is 0.819, P < 0.01. Because CEST imaging has superior spatial resolution to
31P-MRS, CEST may provide an alternative, straightforward, and effective way to
obtain quantitative pH images in vivo.Purpose
pH is a very important biochemical property that changes in many
pathological states
1-4, such as tumor, stroke etc. Monitoring
pH is of significance in early diagnosis and treatment therapy. However, there
is lack of non-invasive methods to image pH in vivo effectively. The purpose of
our study was to quantify the pH value using a chemical exchange saturation
transfer (CEST) method in rat brain and to establish a correlation to pH
measurement using phosphorous spectroscopy (31P-MRS).
Materials and Methods
MRI: Data were collected at 7.0 T on an animal MRI
system using a standard 1H body coil and 31P
surface coil for RF pulse transmitting and receiving. Image sequences
included Z-spectra, T1
fitting, T2 fitting and 31P-MRS. For CEST, we used a continuous wave as the presaturated component,
saturation time=3
s, saturation power=0.75 μT, 1 μT
and 2 μT respectively, amino
proton frequency offset=3.5ppm, reference offset=-3.5 ppm. For Z-spectra, we serially altered the frequency offset from -5.6 ppm to
5.6 ppm, in steps of 0.2 ppm. We used a Point Resolved
Spectroscopy (PRESS)
sequence as a readout component to obtain the
Z-spectra. Seven
water spectra signals were acquired for T1 measurement using a PRESS sequence
with different TR, ranging from 1.1 s to 6 s. Six water spectra signals were
obtained for T2 measurement with TEs from 6.5 to 70 ms. After 1H-imaging,
the body coil was detuned and 31P-MRS were tuned to obtained the
spectra in the same voxel.
Animal
models:
Brains of five normal adult male Sprague-Dawley (SD) rats were scanned in vivo.
The animals were euthanized with overdose of Phenobarbital by intravenous
injection after the first scanning to create whole brain stroke models, which
were scanned immediately in the first 3 hours after stroke.
Analysis: All data were post-processed in Matlab
and SPSS. Quantitative pH was calculated by fitting Z spectra and by 31P-MRS.
Both the standard two pools quantifying exchange rates in chemical exchange
saturation transfer agents using saturation power dependencies (QUESP) and a
homemade Nuclear Overhauser Effect including constrained nonlinear
multivariable (NICN) fitting methods were using to calculate the quantitative
pH value. 31P-MRS used the chemical shift difference between
pH-dependent inorganic phosphate and phosphocreatine to calculate the pH value.
Assessment of the correlation between CEST pH and 31P-MRS pH was performed via
Pearson correlation analysis. Means and standard variance in each method were
calculated and analysed with one-way ANOVA to compare the mean differences, p
< 0.01 was considered as statistically significant.
Results and
discussion
The quantitative pH values from CEST
effect and from 31P-MRS are shown in Figure 1. Statistical results
indicated strong correlation, Pearson correlation factor is 0.819, P < 0.01
(Fig. 2). Moreover, AVONA results show F = 23.2, which was significant (P <
0.01), the effect size is 81.2%. The pH difference between normal brain tissues
and stroke brain lesions was significant (P < 0.01). The difference between
CEST and 31P-MRS methods was insignificant (P = 0.945
for stroke and P = 0.901 for normal tissues) (Fig. 3). Compare the two CEST
fitting methods, the standard two pools QUESP method could not fit the in vivo
data well because of the existing NOE effect, while our NICN method had a
superior fitting both at CEST effect and NOE sides of the spectrum (Fig. 4).
Conclusion
Our study established a strong correlation of pH between CEST and 31P-MRS
in vivo. Because CEST imaging has superior spatial resolution to 31P-MRS,
CEST may provide an alternative, straightforward, and effective way to obtain
quantitative pH images in vivo.
Acknowledgements
This study was funded in part by NSFC- 81471730 (RH. Wu),
MSF of
Guangdong Province-B2013281 (ZZ. Dai).
References
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