Glioblastoma (GBM) is a highly aggressive primary brain tumor. Even after maximally safe tumor resection and chemoradiotherapy, GBM progression is inevitable, and patient prognosis remains poor. Currently, GBM monitoring strategies rely on contrast-enhanced magnetic resonance imaging (MRI). However, due to limited specificity, MRI often fails to distinguish true early progression (TeP) from pseudoprogression (PsP), particularly in the early post-radiation period. Inaccurate interpretation can delay effective treatment and may lead to ineffective treatment decisions and adversely affect clinical outcomes. This interdisciplinary study aims to develop an integrated, non-invasive GBM monitoring strategy by combining radiomics and liquid biopsy. Radiomics enables the extraction of quantitative features from conventional MRI scans, while liquid biopsy provides molecular insights into tumor progression by analyzing microRNAs isolated from extracellular vehicles (EVs) circulating in the patient’s blood. Although both approaches have shown promise individually, their diagnostic accuracy remains limited when used separately. Therefore, the study hypothesizes that integrating radiomics and liquid biopsy will enhance diagnostic accuracy, allow earlier detection of disease progression, and improve GBM prognosis assessment. This prospective longitudinal study will include 50 patients newly diagnosed with GBM. Following surgical tumor resection and chemoradiotherapy, patients will undergo follow-up every 3 months, involving repeated brain MRI scans and blood sample collection. Using machine learning techniques, a predictive model will be developed to enable early identification of GBM progression, differentiation between TeP and PsP, and survival prediction by integrating radiomic features with microRNA expression data derived from EVs.
Project funding:
Research Council of Lithuania, Projects carried out by researchers’ teams
Period of project implementation: 2025-11-03 - 2028-10-31
Project coordinator: Lithuanian University of Health Sciences
Project partners: Kaunas University of Technology, Lietuvos sveikatos mokslų universiteto ligoninė Kauno klinikos
