The role of Dynamic contrast-enhanced MRI perfusion imaging in post treatment surveillance of patients with high grade gliomas

Introduction: High-Grade gliomas are the most common form of malignant brain tumours. The incidence rate of this aggressive form of brain tumour is steadily rising, with survival rates averaging approximately only 1 year, indicating that there is a need for a quicker and more proactive response during treatment and prevention. Neuroimaging is a valuable diagnostic and surveillance tool for high-grade gliomas. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is a perfusion imaging technique, which can quantitatively evaluate tumour biology, concentrating mostly on the microcirculation and the enhancement patterns in the surrounding tissue. By determining disease development and differentiating between stable disease, pseudo-progression and true progression, management strategies may be more effective and relevant to patient status.
Hypotheses: (1) DCE-MRI will prove an accurate and clinically useful tool in the surveillance of high-grade gliomas, by differentiating, clearly and accurately, between tumour growth and treatment related changes, such as pseudo-progression. (2) The addition of a secondary DCE-MRI assessment will enhance the survival prediction and subsequently the accuracy of the prognosis of patients with high-grade gliomas.
Subjects and Methods: This project is a retrospective observational study, with 48 post-treatment patients having been diagnosed with high-grade glioma of the brain. Measurements were taken using DCE-MRI at baseline and at 3-month, 6-month, 9-month and 12-month follow-ups. All data was collected from the UCLH electronic health records (EHR). Perfusion maps, BF, AUC, Ktrans, Kep, Ve and Vp, were generated using commercially available software. The structural images were segmented to provide the volume of the tumour tissue under surveillance and was superimposed onto the perfusion maps, where the ROI values were determined. The imaging data were analysed using descriptive statistics, correlation analysis, and survival analysis. The eight survival analysis models differentiated progression from stable disease and pseudo-progression from true progression, across the 6- and 12-month timepoints.
Results: Models 1 through 4 assessed disease progression based on the initial baseline scan, while models 5 through 8 assessed progression based on the baseline and the 3-month DCE-MRI scan. All survival analysis models were statistically significant with high sensitivity and specificity.
Discussion and Conclusion: The starting hypotheses were verified, with DCE-MRI being an accurate and clinically useful tool in the surveillance of high-grade gliomas, by being able to depict the differences, clearly and accurately, between tumour growth and treatment related changes, such as pseudo-progression. Additionally, the use of the measurements from the secondary DCE-MRI scan can enhance the diagnostic accuracy and subsequently produce more reliable results. Causations for pseudo-progression in patients is discussed in relation to both gold standard treatment and experimental treatments, such as immunotherapy.