Quantitative assessment of amide proton transfer (APT) and nuclear overhauser enhancement (NOE) imaging with extrapolated semisolid magnetization transfer reference (EMR) signals: II. Comparison of three EMR models and application to human brain glioma at 3 Tesla

Hye Young Heo, Yi Zhang, Shanshan Jiang, Dong Hoon Lee, Jinyuan Zhou

Research output: Contribution to journalArticle

Abstract

Purpose To evaluate the use of three extrapolated semisolid magnetization transfer reference (EMR) methods to quantify amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) signals in human glioma. Methods Eleven patients with high-grade glioma were scanned at 3 Tesla. 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 with 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 3T.

Original languageEnglish (US)
Pages (from-to)1630-1639
Number of pages10
JournalMagnetic resonance in medicine
Volume75
Issue number4
DOIs
StatePublished - Apr 1 2016

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Keywords

  • APT
  • CEST
  • MT
  • NOE
  • brain glioma

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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