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Apparent diffusion coefficient maps obtained from high b value diffusion-weighted imaging in the preoperative evaluation of gliomas at 3T: comparison with standard b value diffusion-weighted imaging

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To assess whether ADC maps obtained from high b value DWI were more valuable in preoperatively evaluating the grade, Ki-67 index and outcome of gliomas.

Methods

Sixty-three patients with gliomas, who underwent preoperative multi b value DWI at 3 T, were enrolled. The ADC1000, ADC2000 and ADC3000 maps were generated. Receiver operating characteristic analyses were conducted to determine the area under the curve (AUC) in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG). Pearson correlation coefficients (R value) were calculated to investigate the correlation between parameters with the Ki-67 proliferation index. Survival analysis was conducted by using Cox regression.

Results

The AUC of the mean ADC1000 value (0.820) was lower than that of the mean ADC2000 value (0.847) and mean ADC3000 value (0.875) in differentiating HGG from LGG. The R value of the mean ADC1000 value (−0.499) was less negative than that of the mean ADC2000 value (−0.530) and mean ADC3000 value (−0.567). The mean ADC3000 value was an independent prognosis factor for gliomas (p = 0.008), while the mean ADC1000 and ADC2000 values were not.

Conclusion

ADC maps obtained from high b value DWI might be a better imaging biomarker in the preoperative evaluation of gliomas.

Key Points

• ADC 3000 maps could improve the differentiation between HGG and LGG.

• The mean ADC 3000 value had a closer correlation with the Ki-67 index.

• The mean ADC 3000 value was an independent prognosis factor for gliomas.

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Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

DWI:

Diffusion-weighted imaging

HGG:

High-grade gliomas

LGG:

Low-grade gliomas

NSA:

Number of scan averages

ROC:

Receiver operating characteristic

ROI:

Region of interest

SNR:

Signal-to-noise ratio

References

  1. Schwartzbaum JA, Fisher JL, Aldape KD, Wrensch M (2006) Epidemiology and molecular pathology of glioma. Nat Clin Pract Neurol 2:494–503

    Article  PubMed  Google Scholar 

  2. Weller M, van den Bent M, Hopkins K et al (2014) EANO guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma. Lancet Oncol 15:e395–e403

    Article  PubMed  Google Scholar 

  3. Soffietti R, Baumert BG, Bello L et al (2010) Guidelines on management of low-grade gliomas: report of an EFNS–EANO Task Force. Eur J Neurol 17:1124–1133

    Article  CAS  PubMed  Google Scholar 

  4. Murakami R, Hirai T, Kitajima M et al (2009) Magnetic resonance imaging of pilocytic astrocytomas: usefulness of the minimum apparent diffusion coefficient (ADC) value for differentiation from high-grade gliomas. Acta Radiol 49:462–467

    Article  Google Scholar 

  5. Bai Y, Lin Y, Tian J et al (2016) Grading of gliomas by using monoexponential, biexponential, and stretched exponential diffusion-weighted MR imaging and diffusion kurtosis MR imaging. Radiology 278:496–504

    Article  PubMed  Google Scholar 

  6. Higano S, Yun X, Kumabe T et al (2006) Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology 241:839–846

    Article  PubMed  Google Scholar 

  7. Zulfiqar M, Yousem DM, Lai H (2013) ADC values and prognosis of malignant astrocytomas: does lower ADC predict a worse prognosis independent of grade of tumor?—A meta-analysis. AJNR Am Neuroradiol 200:624–629

    Google Scholar 

  8. Server A, Kulle B, Gadmar ØB et al (2011) Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas. Eur J Radiol 80:462–470

    Article  PubMed  Google Scholar 

  9. Doskaliyev A, Yamasaki F, Ohtaki M et al (2012) Lymphomas and glioblastomas: Differences in the apparent diffusion coefficient evaluated with high b-value diffusion-weighted magnetic resonance imaging at 3T. Eur J Radiol 81:339–344

    Article  PubMed  Google Scholar 

  10. Kitajima K, Takahashi S, Ueno Y et al (2012) Clinical utility of apparent diffusion coefficient values obtained using high b-value when diagnosing prostate cancer using 3 tesla MRI: Comparison between ultra-high b-value (2000 s/mm2) and standard high b-value (1000 s/mm2). J Magn Reson Imaging 36:198–205

    Article  PubMed  Google Scholar 

  11. Han C, Huang S, Guo J et al (2015) Use of a high b-value for diffusion weighted imaging of peritumoral regions to differentiate high-grade gliomas and solitary metastases. J Magn Reson Imaging 42:80–86

    Article  PubMed  Google Scholar 

  12. Zhang K, Shen Y, Zhang X et al (2016) Predicting prostate biopsy outcomes: a preliminary investigation on screening with ultrahigh b-value diffusion-weighted imaging as an innovative diagnostic biomarker. PLoS One 11, e0151176

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hyare H, Thornton J, Stevens J et al (2010) High-b-value diffusion MR imaging and basal nuclei apparent diffusion coefficient measurements in variant and sporadic Creutzfeldt-Jakob disease. AJNR Am Neuroradiol 31:521–526

    Article  CAS  Google Scholar 

  14. Cihangiroglu M, Citci B, Kilickesmez O et al (2011) The utility of high b-value DWI in evaluation of ischemic stroke at 3T. Eur J Radiol 78:75–81

    Article  PubMed  Google Scholar 

  15. Yamasaki F, Kurisu K, Aoki T et al (2012) Advantages of high b-value diffusion-weighted imaging to diagnose pseudo-responses in patients with recurrent glioma after bevacizumab treatment. Eur J Radiol 81:2805–2810

    Article  PubMed  Google Scholar 

  16. Chu HH, Choi SH, Ryoo I et al (2013) Differentiation of true progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide: comparison study of standard and high-b-value diffusion-weighted imaging. Radiology 269:831–840

    Article  PubMed  Google Scholar 

  17. Kang Y, Choi SH, Kim Y-J et al (2011) Gliomas: histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging–correlation with tumor grade. Radiology 261:882–890

    Article  PubMed  Google Scholar 

  18. Hu Y-C, Yan L-F, Sun Q et al. (2016) Comparison between ultra-high and conventional mono b-value DWI for preoperative glioma grading. Oncotarget. 10.18632/oncotarget.14180

  19. Jain R, Poisson LM, Gutman D et al (2014) Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor. Radiology 272:484–493

    Article  PubMed  PubMed Central  Google Scholar 

  20. Dietrich O, Raya JG, Reeder SB et al (2007) Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging 26:375–385

    Article  PubMed  Google Scholar 

  21. Mardor Y, Roth Y, Ocherashvilli A et al (2004) Pretreatment prediction of brain tumors response to radiation therapy using high b-value diffusion-weighted MRI. Neoplasia 6:136–142

    Article  PubMed  PubMed Central  Google Scholar 

  22. Seo HS, Chang KH, Na DG et al (2008) High b-value diffusion (b = 3000 s/mm2) MR imaging in cerebral gliomas at 3T: visual and quantitative comparisons with b = 1000 s/mm2. AJNR Am Neuroradiol 29:458–463

    Article  CAS  Google Scholar 

  23. Han H, Han C, Wu X et al (2017) Preoperative grading of supratentorial nonenhancing gliomas by high b-value diffusion-weighted 3 T magnetic resonance imaging. J Neurooncol 79:1–8

    Google Scholar 

  24. Cihangiroglu MM, Ozturk-Isik E, Firat Z et al (2017) Preoperative grading of supratentorial gliomas using high or standard b-value diffusion-weighted MR imaging at 3T. Diagn Interv Imaging 98:261–268

    Article  CAS  PubMed  Google Scholar 

  25. 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 

Download references

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Author notes

    Authors and Affiliations

    1. Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang, 310009, China

      Qiang Zeng, Chenhan Ling & Jianmin Zhang

    2. Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China

      Fei Dong & Biao Jiang

    3. Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China

      Feina Shi

    Authors
    1. Qiang Zeng
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    2. Fei Dong
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    3. Feina Shi
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    4. Chenhan Ling
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    5. Biao Jiang
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    6. Jianmin Zhang
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    Corresponding author

    Correspondence to Jianmin Zhang.

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    Guarantor

    The scientific guarantor of this publication is Jianmin Zhang.

    Conflict of interest

    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.

    Funding

    The authors state that this work has not received any funding.

    Statistics and biometry

    No complex statistical methods were necessary for this paper.

    Informed consent

    Written informed consent was obtained from all subjects (patients) in this study.

    Ethical approval

    Institutional review board approval was obtained.

    Methodology

    •retrospective

    •diagnostic or prognostic study

    •performed at one institution

    Additional information

    Qiang Zeng and Fei Dong contributed equally to this work.

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    Cite this article

    Zeng, Q., Dong, F., Shi, F. et al. Apparent diffusion coefficient maps obtained from high b value diffusion-weighted imaging in the preoperative evaluation of gliomas at 3T: comparison with standard b value diffusion-weighted imaging. Eur Radiol 27, 5309–5315 (2017). https://doi.org/10.1007/s00330-017-4910-0

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    • DOI: https://doi.org/10.1007/s00330-017-4910-0

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