Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma

Abstract

Background: 

Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed.

Materials and Methods: 

The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings.

Results: 

Some imaging parameters that are effective in glioma management include: ADC, FA, K^trans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of ¹⁸F-FET (for diagnostic application), RD, ADC, ve, vp, K^trans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of ¹⁸F-FET, ¹¹C-MET, and ¹⁸F-FLT (for prognostic and predictive application). Cerebral blood volume and K^trans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic ¹⁸F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations.

Conclusion: 

Parameters including ADC, RD, FA, rCBV, K^trans, vp, and uptake of ¹⁸F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.