MR imaging based fractal analysis for differentiating primary CNS lymphoma and glioblastoma
The aim of this study was to differentiate primary central nervous system lymphoma (PCNSL) from glioblastomas (GBM) using the fractal analysis of conventional MRI data.
Materials and methods
Sixty patients with PCNSL and 107 patients with GBM with MRI data available were enrolled. Fractal dimension (FD) and lacunarity values of the tumour region were calculated using fractal analysis. A predictive model combining fractal parameters and anatomical characteristics was built using logistic regression. The role of FD, lacunarity and the predictive model in differential diagnosis was evaluated using receiver-operating characteristic (ROC) curve analysis. The association between fractal parameters and anatomical characteristics of tumours was also investigated.
PCNSL had lower FD values (p < 0.001) and higher lacunarity values (p < 0.001) than GBM. ROC curve analysis revealed that FD, lacunarity, and the predictive model could distinguish PCNSL from GBM (area under the curve: 0.895, 0.776, and 0.969, respectively). The following associations were observed between fractal parameters and anatomical characteristics: multiple lesions were significantly associated with higher lacunarity (p = 0.024), necrosis with higher FD (p = 0.027), corpus callosum involvement with higher lacunarity (p < 0.001) in PCNSL and subventricular zone involvement with higher FD (p < 0.001) in GBM.
The findings of the study indicate that fractal analysis on conventional MRI performs well in distinguishing PCNSL from GBM.
• Fractal dimension and lacunarity were capable of differentiating PCNSL from GBM.
• PCNSL and GBM exhibited different anatomical characteristics.
• Fractal parameters were associated with some of these anatomical characteristics.
KeywordsLymphoma Glioblastoma Diagnosis Magnetic resonance imaging Fractals
Area under the curve
Magnetic resonance imaging
Primary central nervous system lymphoma
Receiver operating characteristic
Regions of interest
This study has received funding by the Capital Medical Development Research Fund (2016-2-1073), the National Key Research and Development Plan (No. 2016YFC0902500) and the Beijing Postdoctoral Research Foundation (2017-ZZ-116).
Compliance with ethical standards
The scientific guarantor of this publication is Tao Jiang.
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 obtained from all subjects (patients) in this study.
Institutional Review Board approval was obtained.
• Diagnostic or prognostic study
• Performed at one institution
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