Glioblastoma is an aggressive, killer disease. While victims of this fast-moving brain tumor comprise only about 15% of all people with brain cancer, its victims rarely survive more than a few years after diagnosis.
[R]esearchers used the tools of Artificial Intelligence (AI)–in this case, computer image analysis of the initial MRI scans taken of brain cancer patients–and compared that image analysis with genomic research to analyze the cancer.
The result: A new and more accurate way to not only determine the relative life expectancy of glioblastoma victims–but identify who could be candidates for experimental clinical drug trials, said [researcher] Pallavi Tiwari.
The AI model used by the researchers leveraged features from the region adjacent to the tumor, as well as inside the tumor to identify which patients had a poor prognosis, Pallavi said. Then, they used gene-expression information to shed light on which biological pathways were associated with those images.
“Our results demonstrated that image features associated with poor prognosis were also linked with pathways that contribute to chemo-resistance in glioblastoma. This could have huge implications in designing personalized treatment decisions in glioblastoma patients, down the road.” she said.