One of the earliest and most commonly studied applications of diffusion tensor imaging to brain tumor imaging has been the attempt to use apparent diffusion coefficient and fractional anisotropy (FA) measurements to estimate glioma grade. But results have been mixed, and it is difficult to draw any firm conclusions. In contrast, ADC has consistently been reported to be useful in differentiating primary CNS lymphoma (PCNSL) from glioblastomas due to lower ADC in PCNSL, which is likely related to their higher tumor cellularity. However, discrimination of PCNSL from some glioblastomas with restricted diffusion^1,2 may be difficult, as both may appear bright on diffusion-weighted images and dark on ADC maps.

In this preliminary study, we found that, in addition to ADC, FA values of PCNSL were significantly lower than those of glioblastomas. The DTI differences between the two tumors, particularly the lower FA in PCNSL, have also been confirmed by subsequent research.³ Although both tumors appear predominantly hypointense on FA maps, some high FA foci could be seen in the enhancing portion of glioblastomas,⁴ but not in PCNSL. This feature potentially helps differentiate the two tumors on qualitative visual inspection.

The DTI differences between PCNSL and glioblastomas may reflect the histologic differences between the two. However, the primary histologic factor causing the DTI differences is difficult to identify. Until now, the cause of signal change in diffusion imaging is not entirely clear and may not be related just to cellularity. Vascularity, glial matrix, tissue microstructure, the presence of residual white matter, and even some unknown sources may

play a role. Could FA be an overall indicator of tissue heterogeneity due to presence focal high cellularity, pseudopalisades, micronecrosis, microvascular proliferation, etc? Could higher FA of glioblastomas reflect more heterogeneous microstructures typically seen in these tumors? Further studies are needed to answer these questions.

Finally, FA is a quantitative diffusion metric measuring directional variation of diffusivity, and it is different from ADC, which is the average of diffusivities measured in multiple directions. It is therefore worthwhile to investigate if FA could serve as an imaging biomarker for treatment response prediction and clinical outcome stratification in patients with PCNSL.

References

1. Hakyemez B, Erdogan C, Yildirim N, et al. Glioblastoma multiforme with atypical diffusion-weighted MR findings. Br J Radiol 2005;78:989–92, 10.1259/bjr/12830378
2. Toh CH, Chen YL, Hsieh TC, et al. Glioblastoma multiforme with diffusion-weighted magnetic resonance imaging characteristics mimicking primary brain lymphoma. Case report. J Neurosurg 2006;105:132–35, 10.3171/jns.2006.105.1.132
3. Wang S, Kim S, Chawla S, et al. Differentiation between glioblastomas, solitary brain metastases, and primary cerebral lymphomas using diffusion tensor and dynamic susceptibility contrast-enhanced MR imaging. AJNR Am J Neuroradiol 2011;32:507–14, 10.3174/ajnr.A2333
4. Toh CH, Wei KC, Ng SH, et al. Differentiation of tumefactive demyelinating lesions from high-grade gliomas with the use of diffusion tensor imaging. AJNR Am J Neuoradiol 2012;33:846–51, 10.3174/ajnr.A2871

 

Read this article at AJNR.org . . .