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Updated: Feb 24, 2026

Quantitative Immunohistochemistry of the Cellular Microenvironment in Patient Glioblastoma Resections
Published on: July 31, 2017
Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Differentiation
Shanshan Lu1, Siqi Wang, Qianqian Gao
1From the *Department of Radiology, The First Affiliated Hospital of Nanjing Medical University; †National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine; ‡Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing; and §GE Healthcare Life Science, Shanghai, China.
Objective:
This study aimed to evaluate the utility of diffusion and permeability parameters derived from diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for differentiating primary central nervous system lymphoma (PCNSL) and glioblastoma multiforme (GBM) and to assess the correlation among these parameters.
Materials And Methods:
Forty-two patients with GBM and 18 patients with PCNSL underwent conventional 3.0-T MRI, diffusion-weighted imaging, and DCE-MRI before surgery. Normalized apparent diffusion coefficient ratio (rADC) and DCE-MRI-derived parameters (the volume transfer constant [K], the flux rate constant, the volume fraction of extravascular extracellular space [Ve], and the fractional plasma volume) were measured within the entire enhancing tumor and compared between the 2 groups. The diagnostic ability of each parameter and their optimal combination for differentiating between PCNSL and GBM, and the correlation among these parameters, were statistically analyzed.
Results:
The PCNSLs demonstrated significantly lower rADC (P = 0.000), higher K (P = 0.000), and higher Ve (P = 0.001) than GBMs. With the combination of rADC and K, the diagnostic ability for discriminating between PCNSL and GBM was significantly improved (area under the receiver operating characteristic curve [AUC] = 0.930) as compared with rADC (AUC = 0.858) and K (AUC = 0.852) alone (P < 0.001 for both). The rADC did not correlate with K or Ve derived from DCE-MRI.
Conclusions:
Apparent diffusion coefficient ratio, K, and Ve are useful parameters for differentiating between PCNSL and GBM. The combination of rADC and K helps to improve the diagnostic accuracy. The rADC may not show correlation with K or Ve.
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