Differentiation between primary CNS lymphoma and glioblastoma: qualitative and quantitative analysis using arterial spin labeling MR imaging
- 353 Downloads
To evaluate the diagnostic performance of arterial spin labelling perfusion weighted images (ASL-PWIs) to differentiate primary CNS lymphoma (PCNSL) from glioblastoma (GBM).
ASL-PWIs of pathologically confirmed PCNSL (n = 21) or GBM (n = 93) were analysed. For qualitative analysis, tumours were visually scored into five categories based on ASL-CBF maps. For quantitative analysis, normalised CBF values were derived by contralateral grey matter (GM) in intra- and peritumoral areas (nCBFintratumoral and nCBFperitumoral, respectively). Visual scoring scales and quantitative parameters from PCNSL and GBM were compared. In addition, the area under the receiver-operating characteristic (ROC) curve was used to determine the diagnostic accuracy of ASL-PWI for differentiating PCNSL from GBM. Weighted kappa or intraclass correlation coefficients (ICCs) were used to assess reliability between two observers.
In qualitative analysis, scores 5 (CBFintratumoral>CBFGM, 68.8% [64/93]) and 4 (CBFintratumoral ≈ CBFGM, 47.6% [10/21]) were the most frequently reported scores for GBM and PCNSL, respectively. In quantitative analysis, both nCBFintratumoral and nCBFperitumoral in PCNSL were significantly lower than those in the GBM (nCBFintratumoral, 0.89 ± 0.59 [mean and SD] vs. 2.68 ± 1.89, p < 0.001; nCBFperitumoral, 0.17 ± 0.08 vs. 0.45 ± 0.28, p < 0.001). nCBFperitumoral demonstrated the best diagnostic performance (area under the ROC curve: visual scoring, 0.814; nCBFintratumoral, 0.849; nCBFperitumoral, 0.908; p < 0.001 for all). Interobserver agreements for visual scoring (weighted kappa = 0.869), nCBFintratumoral_GM (ICC = 0.958) and nCBFperitumoral_GM (ICC = 0.947) were all excellent.
ASL-PWI performs well in differentiating PCNSL from GBM in both qualitative and quantitative analyses.
• ASL-PWI performs well (AUC > 0.8) in differentiating PCNSL from GBM.
• The visual scoring template demonstrated good diagnostic performance, similar to quantitative analysis.
• nCBFperitumoral demonstrated better diagnostic performance than nCBFintratumoral or visual scoring.
KeywordsLymphoma Glioblastoma Brain neoplasms Magnetic resonance imaging Perfusion imaging
Arterial spin labelling perfusion weighted images
Contralateral grey matter CBF
Contralateral white matter CBF
CBFintratumoral/CBFcontralateral grey matter
CBFintratumoral/CBFcontralateral white matter
CBFperitumoral/CBFcontralateral grey matter
CBFperitumoral/CBFcontralateral white matter
Primary CNS lymphoma
The authors state that this work has not received any funding.
Compliance with ethical standards
The scientific guarantor of this publication is Tae Jin Yun.
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.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was waived by the Institutional Review Board.
Institutional Review Board approval was obtained.
• diagnostic or prognostic study
• performed at one institution
- 17.Yoo RE, Choi SH, Cho HR et al (2013) Tumor blood flow from arterial spin labeling perfusion MRI: A key parameter in distinguishing high-grade gliomas from primary cerebral lymphomas, and in predicting genetic biomarkers in high-grade gliomas. J Magn Reson Imaging 38:852–860CrossRefPubMedGoogle Scholar
- 24.Petersen E, Zimine I, Ho YL, Golay X (2006) Non-invasive measurement of perfusion: a critical review of arterial spin labelling techniques. Br J Radiol 79:688–701Google Scholar