Researchers from the Biomedical Data Science Laboratory (BDSLab) at the ITACA Institute of the Universitat Politècnica de València have developed a new method based on magnetic resonance imaging that enables objective quantification of tumor growth, particularly in the most aggressive brain tumor, glioblastoma.
The study, published in the scientific journal Medical Physics, addresses one of the main clinical challenges in the diagnosis and treatment of this tumor: its high capacity to infiltrate healthy brain tissue.
In their work, the BDSLab team at UPV presents a new biomarker, the Dynamic Infiltration Rate (DIR), capable of identifying distinct tumor growth patterns and independently predicting patient survival.
“Until now, evaluation methods have mainly been based on measuring increases in tumor size or the displacement of brain structures, without adequately capturing how the tumor grows or its biomechanical impact on the surrounding brain”, explains Carles López Mateu, main author of the study.
The research has been developed by Carles López Mateu, María Gómez Mahiques, F. Javier Gil Terrón, Víctor Montosa i Micó, Juan M. García-Gómez and Elies Fuster García, in collaboration with researchers from Oslo University Hospital.
Brain biomechanics
The biomarker developed by the BDSLab-ITACA team combines volumetric tumor growth over time with the mechanical effects this growth exerts on adjacent brain tissue. From longitudinal magnetic resonance image analysis, the researchers generated tissue compression maps that allow evaluation of how the tumor pushes or infiltrates healthy tissue.
The DIR biomarker integrates both phenomena and enables differentiation between more proliferative tumors, which generate greater brain compression, and more infiltrative tumors, which expand without producing significant compression.
“This index allows us to characterize the biological behavior of the tumor beyond its size and provides key information about its aggressiveness”, notes Carles López.
The method has been validated both with synthetic data and in two international clinical cohorts of patients with glioblastoma. The results show that DIR enables robust stratification of patients by prognosis.
“Patients with low DIR values have an average survival of 35.2 weeks, compared to 16.0 weeks in those with high values”, highlights María Gómez Mahiques, ITACA researcher and co-author of the study.
These results demonstrate the potential of DIR as a tool to support clinical decision-making by enabling a more precise characterization of tumor aggressiveness.
Toward more personalized medicine
The study by the UPV team and Oslo University Hospital opens the door to more personalized medicine by enabling therapeutic strategies and follow-up protocols to be tailored to each tumor’s growth pattern.
“It is a quantitative, reproducible, and non-invasive biomarker, based exclusively on medical imaging, that reinforces the role of biomedical engineering and data science in precision oncology and, at the same time, uses accessible methodologies that facilitate its future transfer to clinical practice”, the authors conclude.
Reference: Carles López-Mateu, María Gómez-Mahiques, F. Javier Gil-Terrón, Víctor Montosa-i-Micó, Donatas Sederevičius, Kyrre E. Emblem, Juan M. García-Gómez, Elies Fuster-García. Biomechanical mapping of tumor growth: A novel method to quantify glioma infiltration and mass effect. Medical Physics. DOI: https://doi.org/10.1002/mp.70334
