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Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume

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Abstract

Objectives

To evaluate the added value of amide proton transfer (APT) imaging to the apparent diffusion coefficient (ADC) from diffusion tensor imaging (DTI) and the relative cerebral blood volume (rCBV) from perfusion magnetic resonance imaging (MRI) for discriminating between high- and low-grade gliomas.

Methods

Forty-six consecutive adult patients with diffuse gliomas who underwent preoperative APT imaging, DTI and perfusion MRI were enrolled. APT signals were compared according to the World Health Organization grade. The diagnostic ability and added value of the APT signal to the ADC and rCBV for discriminating between low- and high-grade gliomas were evaluated using receiver operating characteristic (ROC) analyses and integrated discrimination improvement.

Results

The APT signal increased as the glioma grade increased. The discrimination abilities of the APT, ADC and rCBV values were not significantly different. Using both the APT signal and ADC significantly improved discrimination vs. the ADC alone (area under the ROC curve [AUC], 0.888 vs. 0.910; P = 0.007), whereas using both the APT signal and rCBV did not improve discrimination vs. the rCBV alone (AUC, 0.927 vs. 0.923; P = 0.222).

Conclusions

APT imaging may be a useful imaging biomarker that adds value to the ADC for discriminating between low- and high-grade gliomas.

Key points

• Higher APT values were correlated with higher glioma grades.

• Adding the APT signal to the ADC improved glioma grading.

• Adding the APT signal to rCBV did not improve glioma grading.

• APT is a useful adjunct to the ADC for glioma grading.

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Abbreviations

ADC:

apparent diffusion coefficient

APT:

amide proton transfer

AUC:

area under the curve

BSA:

bovine serum albumin

DSC:

dynamic susceptibility contrast-enhanced

DTI:

diffusion tensor imaging

FOV:

field of view

IDI:

integrated discrimination index

MRI:

magnetic resonance imaging

MTRasym :

magnetization transfer ratio asymmetry

rCBV:

relative cerebral blood volume

RF:

radiofrequency

ROC:

receiver operating characteristic

ROI:

region of interest

TE:

echo time

TR:

repetition time

WHO:

World Health Organization

References

  1. Clarke J, Butowski N, Chang S (2010) Recent advances in therapy for glioblastoma. Arch Neurol 67:279–283

    Article  PubMed  Google Scholar 

  2. Bulakbasi N, Guvenc I, Onguru O et al (2004) The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. J Comput Assist Tomogr 28:735–746

    Article  PubMed  Google Scholar 

  3. Sugahara T, Korogi Y, Kochi M et al (1998) Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. AJR Am J Roentgenol 171:1479–1486

    Article  CAS  PubMed  Google Scholar 

  4. Shin JH, Lee HK, Kwun BD et al (2002) Using relative cerebral blood flow and volume to evaluate the histopathologic grade of cerebral gliomas: preliminary results. Am J Roentgenol 179:783–789

    Article  Google Scholar 

  5. Aronen HJ, Gazit IE, Louis DN et al (1994) Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology 191:41–51

    Article  CAS  PubMed  Google Scholar 

  6. Ahn SS, Shin N-Y, Chang JH et al (2014) Prediction of methylguanine methyltransferase promoter methylation in glioblastoma using dynamic contrast-enhanced magnetic resonance and diffusion tensor imaging. J Neurosurg 121:367–373

    Article  PubMed  Google Scholar 

  7. Sunwoo L, Choi SH, Park C-K et al (2013) Correlation of apparent diffusion coefficient values measured by diffusion MRI and MGMT promoter methylation semiquantitatively analyzed with MS-MLPA in patients with glioblastoma multiforme. J Magn Reson Imaging 37:351–358

    Article  PubMed  Google Scholar 

  8. Pope WB, Lai A, Mehta R et al (2011) Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newly diagnosed bevacizumab-treated glioblastoma. Am J Neuroradiol 32:882–889

    Article  CAS  PubMed  Google Scholar 

  9. Romano A, Calabria LF, Tavanti F et al (2013) Apparent diffusion coefficient obtained by magnetic resonance imaging as a prognostic marker in glioblastomas: correlation with MGMT promoter methylation status. Eur Radiol 23:513–520

    Article  PubMed  Google Scholar 

  10. Van Zijl P, Yadav NN (2011) Chemical exchange saturation transfer (CEST): what is in a name and what isn’t? Magn Reson Med 65:927–948

    Article  PubMed  PubMed Central  Google Scholar 

  11. Woods M, Woessner DE, Sherry AD (2006) Paramagnetic lanthanide complexes as PARACEST agents for medical imaging. Chem Soc Rev 35:500–511

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ward KM, Aletras AH, Balaban RS (2000) A new class of contrast agents for MRI based on proton chemical exchange dependent saturation transfer (CEST). J Magn Reson 143:79–87

    Article  CAS  PubMed  Google Scholar 

  13. Zhou J, Lal B, Wilson DA et al (2003) Amide proton transfer (APT) contrast for imaging of brain tumors. Magn Reson Med 50:1120–1126

    Article  PubMed  Google Scholar 

  14. Zhou J, Payen J-F, Wilson DA et al (2003) Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med 9:1085–1090

    Article  CAS  PubMed  Google Scholar 

  15. Zhu H, Jones CK, van Zijl P et al (2010) Fast 3D chemical exchange saturation transfer (CEST) imaging of the human brain. Magn Reson Med 64:638–644

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kim M, Gillen J, Landman BA et al (2009) Water saturation shift referencing (WASSR) for chemical exchange saturation transfer (CEST) experiments. Magn Reson Med 61:1441–1450

    Article  PubMed  PubMed Central  Google Scholar 

  17. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 837–845

  18. Pencina MJ, D’Agostino RB, D’Agostino RB, Vasan RS (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27:157

    Article  PubMed  Google Scholar 

  19. Zhou J, Tryggestad E, Wen Z et al (2011) Differentiation between glioma and radiation necrosis using molecular magnetic resonance imaging of endogenous proteins and peptides. Nat Med 17:130–134

    Article  CAS  PubMed  Google Scholar 

  20. Sagiyama K, Mashimo T, Togao O et al (2014) In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma. Proc Natl Acad Sci 111:4542–4547

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Togao O, Yoshiura T, Keupp J et al (2014) Amide proton transfer imaging of adult diffuse gliomas: correlation with histopathological grades. Neuro-Oncology 16:441–448

    Article  CAS  PubMed  Google Scholar 

  22. Park JE, Kim HS, Park KJ et al (2015) Histogram analysis of amide proton transfer imaging to identify contrast-enhancing low-grade brain tumor that mimics high-grade tumor: increased accuracy of MR perfusion. Radiology 277:151–161

    Article  PubMed  Google Scholar 

  23. Sun PZ, Benner T, Kumar A, Sorensen AG (2008) Investigation of optimizing and translating pH-sensitive pulsed-chemical exchange saturation transfer (CEST) imaging to a 3T clinical scanner. Magn Reson Med 60:834–841

    Article  PubMed  Google Scholar 

  24. Jones CK, Huang A, Xu J et al (2013) Nuclear Overhauser enhancement (NOE) imaging in the human brain at 7 T. NeuroImage 77:114–124

    Article  PubMed  Google Scholar 

  25. McVicar N, Li AX, Gonçalves DF et al (2014) Quantitative tissue pH measurement during cerebral ischemia using amine and amide concentration-independent detection (AACID) with MRI. J Cereb Blood Flow Metab 34:690–698

    Article  PubMed  PubMed Central  Google Scholar 

  26. Zhao X, Wen Z, Huang F et al (2011) Saturation power dependence of amide proton transfer image contrasts in human brain tumors and strokes at 3 T. Magn Reson Med 66:1033–1041

    Article  PubMed  PubMed Central  Google Scholar 

  27. Wen Z, Hu S, Huang F et al (2010) MR imaging of high-grade brain tumors using endogenous protein and peptide-based contrast. NeuroImage 51:616–622

    Article  PubMed  PubMed Central  Google Scholar 

  28. Howe FA, Barton SJ, Cudlip SA et al (2003) Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 49:223–232

    Article  CAS  PubMed  Google Scholar 

  29. Salhotra A, Lal B, Laterra J et al (2008) Amide proton transfer imaging of 9L gliosarcoma and human glioblastoma xenografts. NMR Biomed 21:489–497

    Article  PubMed  PubMed Central  Google Scholar 

  30. Herholz K, Hölzer T, Bauer B et al (1998) 11C-methionine PET for differential diagnosis of low-grade gliomas. Neurology 50:1316–1322

    Article  CAS  PubMed  Google Scholar 

  31. Pöpperl G, Kreth FW, Mehrkens JH et al (2007) FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading. Eur J Nucl Med Mol Imaging 34:1933–1942

    Article  PubMed  Google Scholar 

  32. Sakata A, Okada T, Yamamoto A et al (2015) Grading glial tumors with amide proton transfer MR imaging: different analytical approaches. J Neuro-Oncol 122:339–348

    Article  CAS  Google Scholar 

  33. Ahn SJ, Shin HJ, Chang J-H, Lee S-K (2014) Differentiation between primary cerebral lymphoma and glioblastoma using the apparent diffusion coefficient: comparison of three different ROI methods. PLoS One 9, e112948

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank Ha-Kyu Jeong (Korea Basic Science Institute, Chungcheongbuk-do, Korea) for his help with protocol optimization and valuable suggestions.

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Authors and Affiliations

  1. Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea

    Yoon Seong Choi, Sung Soo Ahn & Seung-Koo Lee

  2. Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea

    Jong Hee Chang & Seok-Gu Kang

  3. Department of Pathology, Yonsei University College of Medicine, Seoul, Korea

    Se Hoon Kim

  4. Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Jinyuan Zhou

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  1. Yoon Seong Choi
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  4. Jong Hee Chang
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  5. Seok-Gu Kang
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Corresponding author

Correspondence to Sung Soo Ahn.

Ethics declarations

No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was waived by the institutional review board. No study subjects or cohorts have been previously reported. Methodology: retrospective, observational, performed at one institution.

Funding

This research received funding from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2014R1A1A1002716) and National Institutes of Health (P41 EB015909, R01 CA166171, R01 EB009731).

Conflict of interest

The scientific guarantor of this publication is Sung Soo Ahn. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

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Choi, Y.S., Ahn, S.S., Lee, SK. et al. Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume. Eur Radiol 27, 3181–3189 (2017). https://doi.org/10.1007/s00330-017-4732-0

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  • DOI: https://doi.org/10.1007/s00330-017-4732-0

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