Integration of Artificial Intelligence in Magnetic Resonance Imaging analysis and Liquid Biopsy in diagnosing and monitoring Glioblastoma Multiforme - A Systematic Review - Zatyka, Antonina; Krupski, Aleksander; Marusza, Michał; Stielow , Victoria (Quality in Sport, 2026)
Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor among adults and is associated with rapid progressions and poor prognosis. Modern diagnostic techniques, including molecular biology, have improved the perception of disease development emphasizing the role of disturbed signaling pathways, genetic mutations and tumor microenvironment. The following review aims to conclude current comprehension of molecular mechanisms leading to GBM development and contemporary diagnostic and therapeutic approaches. Articles present in PubMed database published from 2022 onwards were researched to perform analysis of tumor biology, subcellular mechanisms and diagnostic possibilities. Magnetic resonance imaging (MRI) remains the most fundamental diagnostic method which enhanced by modern approaches such as radiomics and artificial intelligence (AI) supports proper diagnosis and enables tumor characteristics analysis. Moreover, combining imaging with modern pathomorphological methods such as liquid biopsy can lead to increased accuracy and personalization in diagnostics. To conclude, GBM development is a complex process combining genetic alterations and disturbed molecular pathways that can be detected using modern diagnostic techniques. Advanced pathomorphological methods and AI-supported imaging lead to accurate diagnosis, proper therapeutic decisions and better patient outcome.