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Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient

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Abstract

Objectives

To evaluate the ability of the initial area under the curve (IAUC) derived from dynamic contrast-enhanced MR imaging (DCE-MRI) and apparent diffusion coefficient (ADC) in differentiating between primary central nervous system lymphoma (PCNSL) and atypical glioblastoma (GBM).

Methods

We retrospectively identified 19 patients with atypical GBM (less than 13 % necrosis of the enhancing tumour), and 23 patients with PCNSL. The histogram parameters of IAUC at 30, 60, 90 s (IAUC30, IAUC60, and IAUC90), and ADC were compared between PCNSL and GBM. The diagnostic performances and added values of the IAUC and ADC for differentiating between PCNSL and GBM were evaluated. Interobserver agreement was assessed via intraclass correlation coefficient (ICC).

Results

The IAUC and ADC parameters were higher in GBM than in PCNSL. The 90th percentile (p90) of IAUC30 and 10th percentile (p10) of ADC showed the best diagnostic performance. Adding p90 of IAUC30 to p10 of ADC improved the differentiation between PCNSL and GBM (area under the ROC curve [AUC] = 0.886), compared to IAUC30 or ADC alone (AUC = 0.789 and 0.744; P < 0.05 for all). The ICC was 0.96 for p90 of IAUC30.

Conclusions

The IAUC may be a useful parameter together with ADC for differentiating between PCNSL and atypical GBM.

Key Points

• High reproducibility is essential for practical implementation of advanced MRI parameters.

• IAUC and ADC are highly reproducible parameters.

• IAUC values were higher in atypical GBM than in PCNSL.

• Adding IAUC to ADC improved the differentiation between PCNSL and GBM.

• IAUC with ADC are useful for differentiating PCNSL from GBM.

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Abbreviations

ADC:

apparent diffusion coefficient

AUC:

area under the receiver operating characteristic curve

DCE:

dynamic contrast-enhanced

DSC:

dynamic susceptibility contrast-enhanced

DTI:

diffusion tensor imaging

GBM:

glioblastoma

IAUC:

initial area under the curve

PCNSL:

primary central nervous system lymphoma

p10:

10th percentile

p90:

90th percentile

ROI:

region of interest

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Acknowledgments

The scientific guarantor of this publication is Seung-Koo Lee. 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. The authors state that this work has not received any funding. 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. Some study subjects or cohorts have been previously reported in the American Journal of Neuroradiology and Radiology as the following:

Choi YS, Kim DW, Lee S-K, et al (2015) The Added Prognostic Value of Preoperative Dynamic Contrast-Enhanced MRI Histogram Analysis in Patients with Glioblastoma: Analysis of Overall and Progression-Free Survival. AJNR Am J Neuroradiol 36:2235–2241.

Choi YS, Ahn SS, Kim DW, et al (2016) Incremental Prognostic Value of ADC Histogram Analysis over MGMT Promoter Methylation Status in Patients with Glioblastoma. Radiology doi: 10.1148/radiol.2016151913

Methodology: retrospective, observational, performed at one institution.

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Authors and Affiliations

  1. Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea

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

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

    Jong Hee Chang, Seok-Gu Kang & Eui Hyun Kim

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

    Se Hoon Kim

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  1. Yoon Seong Choi
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Choi, Y.S., Lee, HJ., Ahn, S.S. et al. Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient. Eur Radiol 27, 1344–1351 (2017). https://doi.org/10.1007/s00330-016-4484-2

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