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Grading of Cerebral Glioma with Multiparametric MR Imaging and 18F-FDG-PET: Concordance and Accuracy

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Abstract

Objectives

To retrospectively evaluate concordance rates and predictive values in concordant cases among multiparametric MR techniques and FDG-PET to grade cerebral gliomas.

Methods

Multiparametric MR imaging and FDG-PET were performed in 60 consecutive patients with cerebral gliomas (12 low-grade and 48 high-grade gliomas). As the dichotomic variables, conventional MRI, minimum apparent diffusion coefficient in diffusion-weighted imaging, maximum relative cerebral blood volume ratio in perfusion-weighted imaging, choline/creatine ratio and (lipid and lactate)/creatine ratio in MR spectroscopy, and maximum standardised uptake value ratio in FDG-PET in low- and high-grade gliomas were compared. Their concordance rates and positive/negative predictive values (PPV/NPV) in concordant cases were obtained for the various combinations of multiparametric MR techniques and FDG-PET.

Results

There were significant differences between low- and high-grade gliomas in all techniques. Combinations of two, three, four, and five out of the five techniques showed concordance rates of 77.0 ± 4.8 %, 65.5 ± 4.0 %, 58.3 ± 2.6 % and 53.3 %, PPV in high-grade concordant cases of 97.3 ± 1.7 %, 99.1 ± 1.4 %, 100.0 ± 0 % and 100.0 % and NPV in low-grade concordant cases of 70.2 ± 7.5 %, 78.0 ± 6.0 %, 80.3 ± 3.4 % and 80.0 %, respectively.

Conclusion

Multiparametric MR techniques and FDG-PET have a concordant tendency in a two-tiered classification for the grading of cerebral glioma. If at least two examinations concordantly indicated high-grade gliomas, the PPV was about 95 %.

Key Points

• Modern imaging techniques can help predict the aggressiveness of cerebral gliomas.

• Multiparametric MRI and FDG-PET have a concordant tendency to grade cerebral gliomas.

• Their high-grade concordant cases revealed at least 95 % positive predictive values.

• Their low-grade concordant cases revealed about 70–80 % negative predictive values.

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Acknowledgements

We would like to thank So Young Yun for her invaluable assistance in coordinating this study and helping with data collection. This study was funded by 2010 Man Chung Han Research Grant.

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Authors and Affiliations

  1. Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea

    Jeong Hee Yoon, Ji-hoon Kim, Chul-Ho Sohn, Seung Hong Choi, Tae Jin Yun, Yong Sub Song & Kee-Hyun Chang

  2. Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Korea

    Won Jun Kang

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

    Won Jun Kang

  4. College of Medicine, Seoul National University, Seoul, Korea

    Yong Eun

  5. Department of Radiology, Soonchunhyang University Bucheon Hospital, Bucheon, Korea

    Kee-Hyun Chang

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  1. Jeong Hee Yoon
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  2. Ji-hoon Kim
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Correspondence to Ji-hoon Kim.

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Yoon, J.H., Kim, Jh., Kang, W.J. et al. Grading of Cerebral Glioma with Multiparametric MR Imaging and 18F-FDG-PET: Concordance and Accuracy. Eur Radiol 24, 380–389 (2014). https://doi.org/10.1007/s00330-013-3019-3

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  • DOI: https://doi.org/10.1007/s00330-013-3019-3

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