ESTRO 2024 - Abstract Book

S5145

Physics - Radiomics, functional and biological imaging and outcome prediction

ESTRO 2024

Keywords: breast cancer, radiotherapy, cardiotoxicity

References:

Díaz-Gavela, A. A., Figueiras-Graillet, L., Luis, Á. M., Segura, J. S., Ciérvide, R., Peñalver, E. D. C., Couñago, F., Arenas, M., & López-Fernández, T. (2021). Breast radiotherapy-related cardiotoxicity. When, how, why. risk prevention and control strategies. In Cancers (Vol. 13, Issue 7). MDPI AG. https://doi.org/10.3390/cancers13071712 McWilliam, A., Khalifa, J., Vasquez Osorio, E., Banfill, K., Abravan, A., Faivre-Finn, C., & van Herk, M. (2020). Novel Methodology to Investigate the Effect of Radiation Dose to Heart Substructures on Overall Survival. International Journal of Radiation Oncology Biology Physics, 108(4), 1073–1081. https://doi.org/10.1016/j.ijrobp.2020.06.031 Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: A Cancer Journal for Clinicians, 71(3), 209–249. https://doi.org/10.3322/caac.21660 Finnegan, R. N., Chin, V., Chlap, P., Haidar, A., Otton, J., Dowling, J., Thwaites, D. I., Vinod, S. K., Delaney, G. P., & Holloway, L. (2023). Open-source, fully-automated hybrid cardiac substructure segmentation: development and optimisation. Physical and Engineering Sciences in Medicine. https://doi.org/10.1007/s13246-023-01231-w Agatston, A. S., Janowitz, W. R., Hildner, F. J., Zusmer, N. R., Viamonte, M., & Detrano, R. (1990). Quantification of coronary artery calcium using ultrafast computed tomography. Journal of the American College of Cardiology, 15(4). https://doi.org/10.1016/0735-1097(90)90282-T

2984

Digital Poster

Radiomics-based Risk Stratification for GBM: Training, Validation, and Clinical Applicability

Abdulkerim Duman 1 , James Powell 2 , Solly Thomas 3 , Xianfang Sun 4 , Emiliano Spezi 1

1 Cardiff University, School of Engineering, Cardiff, United Kingdom. 2 Velindre NHS Trust, Department of Oncology, Cardiff, United Kingdom. 3 Velindre NHS Trus, Department of Oncology, Cardiff, United Kingdom. 4 Cardiff University, School of Computer Science and Informatics, Cardiff, United Kingdom

Purpose/Objective:

Glioblastoma Multiforme (GBM) is the most prevalent aggressive brain tumor in adults. It requires precise risk stratification based on survival for individualized patient care and treatment choices due to its rapid progression and high fatality. In this context, accurate and automated early survival risk assessment becomes especially important for patients with GBM, given that their poor prognosis necessitates prompt and informed treatment decisions. We have built a radiomics-based risk stratification model focused on overall survival (OS) in GBM. The radiomics risk stratification model was trained on a multi-institutional public dataset and validated on a local dataset, with both