Purpose
To quantify APT and NOE contributions to in vivo chemical exchange saturation transfer MRI signals in tumors.
Theory and Methods
Two-pool (free water and semi-solid protons) and four-pool (free water, semi-solid, amide, and upfield NOE-related protons) tissue models combined with the super-Lorentzian lineshape for semi-solid protons were used to fit wide and narrow frequency-offset magnetization-transfer (MT) data, respectively. Extrapolated semi-solid MT signals at 3.5 and −3.5 ppm from water were used as reference signals to quantify APT and NOE, respectively. Six glioma-bearing rats were scanned at 4.7 T. Quantitative APT and NOE signals were compared at three saturation power levels.
Results
The observed APT signals were significantly higher in the tumor (center and rim) than in the contralateral normal brain tissue at all saturation powers, and were the major contributor to the APT-weighted image contrast (based on MT asymmetry analysis) between the tumor and the normal brain tissue. The NOE (a positive confounding factor) enhanced this APT-weighted image contrast. The fitted amide pool sizes were significantly larger, while the NOE-related pool sizes were significantly smaller in the tumor than in the normal brain tissue.
Conclusion
The EMR provides a relatively accurate approach for quantitatively measuring pure APT and NOE signals.
Purpose
To evaluate the use of three EMR methods to quantify APT and NOE signals in human glioma.
Methods
Eleven patients with high-grade glioma were scanned at 3 T. aEMR2 (asymmetric magnetization-transfer or MT model to fit two-sided, wide-offset data), sEMR2 (symmetric MT model to fit two-sided, wide-offset data), and sEMR1 (symmetric MT model to fit one-sided, wide-offset data) were assessed. ZEMR and experimental data at 3.5 ppm and −3.5 ppm were subtracted to calculate the APT and NOE signals (APT# and NOE#), respectively.
Results
The aEMR2 and sEMR1 models provided quite similar APT# signals, while the sEMR2 provided somewhat lower APT# signals. The aEMR2 had an erroneous NOE# quantification. Calculated APT# signal intensities of glioma (~4%), much larger than the values reported previously, were significantly higher than those of edema and normal tissue. Compared to normal tissue, gadolinium-enhancing tumor cores were consistently hyperintense on the APT# maps and slightly hypointense on the NOE# maps.
Conclusion
The sEMR1 model is the best choice for accurately quantifying APT and NOE signals. The APT-weighted hyperintensity in the tumor was dominated by the APT effect, and the MT asymmetry at 3.5 ppm is a reliable and valid metric for APT imaging of gliomas at 3 T.
Objectives
To show the ability of using the amide-proton-transfer-weighted (APTW) MRI signals as imaging biomarkers to differentiate primary central-nervous-system lymphomas (PCNSLs) from high-grade gliomas (HGGs).
Methods
Eleven patients with lymphomas and 21 patients with HGGs were examined. Magnetization-transfer (MT) spectra over an offset range of ±6 ppm and the conventional MT ratio (MTR) at 15.6 ppm were acquired. The APTW signals, total chemical-exchange-saturation-transfer signal (integral between 0 and 5 ppm, CESTtotal), and MTR signal were obtained and compared between PCNSLs and HGGs. The diagnostic performance was assessed with the receiver-operating-characteristic-curve analysis.
Results
The PCNSLs usually showed more homogeneous APTW hyperintensity (spatially compared to the normal brain tissue) than the HGGs. The APTWmax, APTWmax-min, and CESTtotal signal intensities were significantly lower (P < 0.05, 0.001, and 0.05, respectively), while the APTWmin and MTR were significantly higher (both P < 0.01) in PCNSL lesions than in HGG lesions. The APTW values in peritumoral oedema were significantly lower for PCNSLs than for HGGs (P < 0.01). APTWmax-min had the highest area under the receiver-operating-characteristic curve (0.963) and accuracy (94.1%) in differentiating PCNSLs from HGGs.
Conclusions
The protein-based APTW signal would be a valuable MRI biomarker by which to identify PCNSLs and HGGs presurgically.
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