Differentiation of Central Nervous System Lymphoma and Gliomas using Dynamic Susceptibility Contrast and Dynamic Contrast-Enhanced MRI
Kazuhiro Murayama1, Takahiro Ueda1, Takashi Fukuba2, Shigeharu Ohyu3, Ayako Ninomiya3, Masato Ikedo3, Kazuhiro Katada4, and Hiroshi Toyama1

1Radiology, Fujita Health University, Toyoake, Japan, 2Radiology, Fujita Health University Hospital, Toyoake, Japan, 3Toshiba Medical Systems, Otawara, Japan, 4Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University, Toyoake, Japan

Synopsis

A combination of Ktrans, Ve, and rCBV would be useful in differentiating between central nervous system lymphoma and gliomas. Dynamic contrast-enhanced MRI parameters have been successfully applied to obtain quantitative estimates of the permeability of brain tumors for characterization of the vascular microenvironment.

Objective

The relationships between cerebral blood volume (CBV) using dynamic susceptibility contrast (DSC) MRI and tumor grade of glioma, and distinction brain tumors have been demonstrated [1]. However, CBV values don’t necessarily allow accurate classification of tumor grade, and differentiation. The purpose of this study was to evaluate the diagnostic performance of dynamic contrast-enhanced (DCE) MRI in differentiating central nervous system lymphoma (CNSL) from high-grade glioma (HGG) and low-grade glioma (LGG) comparison of DSC-MRI.

Materials and Methods

From January 2015 to September 2015, 21 consecutive patients who underwent preoperative MRI examination, including DSC and DCE-MRI at 3T MRI (Vantage Titan 3T with Saturn Gradient Option, Toshiba) and 5 CNSLs, 11 HGGs, 5 LGGs were enrolled in this study. For getting both vascularity and permeability information within routine dose of contrast media at the same examination, contrast media of 0.05mmol/kg body weight was injected as a bolus twice. Volume transfer coefficient (Ktrans), extravascular extracellular space (EES) volume per unit volume of tissue (Ve), blood plasma volume per unit volume of tissue (Vp), rate constant between EES and plasma (Kep) in DCE-MRI parameters and relative cerebral blood volume (rCBV) in DSC-MRI parameter were measured by manual region of interest. The differences between CNSL, HGG and LGG were investigated by histogram analysis.

Results

Statistically significant differences were observed between CNSL and LGG (p<0.005), HGG and LGG (p<0.05) in Ktrans , CNSL and LGG (p<0.005) in Ve, CNSL and HGG (p<0.05) in rCBV, HGG and LGG (p<0.05) in Vp. There were no significant differences in Kep. Ktrans of CNSL and HGG were significantly higher than that of LGG (Ktrans of CNSL; 0.20±0.07, Ktrans of HGG; 0.11±0.09, Ktrans of LGG; 0.01±0.001). Ve of CNSL were significantly higher than that of LGG (Ve of CNSL; 0.71±0.18, Ve of LGG; 0.01±0.007). rCBV of CNSL were significantly lower than that of HGG (rCBV of CNSL; 1.52±1.42, rCBV of HGG; 3.74±2.02). Susceptibility artifacts had relatively little influence in DCE-MRI as compared with DSC-MRI.

Discussion

CNSL demonstrated significantly higher Ktrans and Ve than LGG, lower rCBV than HGG, implying Ktrans, Ve and rCBV were useful of differentiation CNSL from gliomas. Improvements in diagnostic capabilities by employing several of these perfusion parameters have been reported in some papers as multiparametric MRI [2]. A combination of DCE and DSC-MRI parameters may enable more accurate classification and differential diagnosis of brain tumors. Furthermore, susceptibility artifacts have relatively little influence in DCE-MRI as compared with DSC-MRI, implying DCE-MRI were able to apply to lesions with hemorrhage and lesions at the skull base.

Conclusion

A combination of Ktrans, Ve, and rCBV would be useful in differentiating between CNSL and gliomas. DCE-MRI parameters have been successfully applied to obtain quantitative estimates of the permeability of brain tumors for characterization of the vascular microenvironment.

Acknowledgements

No acknowledgement found.

References

1. Law M1, Cha S, Knopp EA et al. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology. 2002 Mar;222(3):715-21.

2. Roy B1, Gupta RK, Maudsley AA et al. Utility of multiparametric 3-T MRI for glioma characterization. Neuroradiology. 2013 May;55(5):603-13.

Figures

Fig1. The case of glioblastoma. A). Axial post-contrast T1-weighted image shows a ringed enhanced lesion in the left frontal lobe. B). Axial CBV map shows increased vascularity. C,D) Axial Ktrans and Ve maps show increased vascular permeability and extravascular extracellular space in the peripheral lesion.

Fig2. The case of central nervous system lymphoma. A). Axial post-contrast T1-weighted image shows a enhanced lesion in the right middle cerebellar peduncle. B). Axial rCBV map shows decreased vascularity. C,D) Axial Ktrans and Ve maps show extremely increased vascular permeability and extravascular extracellular space in the whole lesion.

Fig3. Scatter plot shows values of rCBV, Ktrans and Ve for CNSL, HGG and LGG. CNSL demonstrates significantly higher Ktrans (p<0.005) and Ve (p<0.005) than LGG, lower rCBV (p<0.05) than HGG. HGG demonstrates significantly higher Ktrans (p<0.05) than LGG.




Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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