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Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor
S Wang1, M Martinez-Lage2, Y Sakai1
1From the Departments of Radiology (S.W., Y.S., S.M., R.L.W., H.P.).
AJNR. American Journal of Neuroradiology
|October 10, 2015
Summary
Advanced MRI techniques, including diffusion tensor imaging (DTI) and dynamic susceptibility contrast (DSC) perfusion, accurately differentiate true glioblastoma progression from treatment effects. These imaging parameters aid in personalized patient treatment strategies.
Area of Science:
- Neuroimaging
- Radiology
- Oncology
Background:
- Accurate assessment of glioblastoma treatment response is crucial for patient management.
- Distinguishing true tumor progression from treatment-related changes like pseudoprogression is challenging.
Purpose of the Study:
- To evaluate the combination of diffusion tensor imaging (DTI) and dynamic susceptibility contrast (DSC) perfusion parameters for differentiating true glioblastoma progression from mixed response and pseudoprogression.
- To identify imaging biomarkers that improve the accuracy of treatment response assessment in glioblastoma patients.
Main Methods:
- Retrospective analysis of 41 glioblastoma patients with enhancing lesions post-chemoradiation.
- Measurement of DTI parameters (mean diffusivity, fractional anisotropy, anisotropy coefficients) and DSC parameter (maximum relative cerebral blood volume) in enhancing tissues.
- Multivariate logistic regression analysis to develop a classification model for true progression versus non-true progression.
Main Results:
- True progression showed significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient, with decreased spheric anisotropy coefficient compared to pseudoprogression.
- A combined model of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume achieved an area under the curve of 0.905 for distinguishing true progression.
- Fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from other groups with an area under the curve of 0.807.
Conclusions:
- DTI and DSC perfusion imaging parameters offer improved accuracy in assessing glioblastoma treatment response.
- These advanced imaging techniques can assist in the individualized treatment planning for glioblastoma patients.
- The study highlights the potential of multiparametric MRI in clinical decision-making for glioblastoma management.
