ESTRO 2024 - Abstract Book

S4434

Physics - Machine learning models and clinical applications

ESTRO 2024

Conclusion:

RapidPlan models represent a data-driven tool that significantly enhances radiation therapy by reducing subjectivity and saving time. They facilitate protocol discussions, support the selection of statistical plans, and boost confidence in adopting innovative techniques. While physicists remain crucial for individual patient evaluation, RapidPlan consistently delivers high-quality results efficiently, underscoring its importance in the field of radiotherapy.

Keywords: RapidPlan, Machine Learning, Models

References:

Referências

[1] Fogliata, A., Cozzi, L., Reggiori, G. et al. RapidPlan knowledge based planning: iterative learning process and model ability to steer planning strategies. Radiat Oncol 14, 187 (2019). https://doi.org/10.1186/s13014-019-1403-0

[2] Chua, L., Pang, E., Master, Z., Sultana, R., Tuan, J., & Bragg, C. (2021). Dosimetric comparison of RapidPlan and manually optimised volumetric modulated arc therapy plans in prostate cancer. Journal of Radiotherapy in Practice, 20(3), 257-264. doi:10.1017/S1460396920000345 [3] Clark GM, Popple RA, Prendergast BM, Spencer SA, Thomas EM, Stewart JG, Guthrie BL, Markert JM, Fiveash JB. Plan quality and treatment planning technique for single isocenter cranial radiosurgery with volumetric modulated arc therapy. Pract Radiat Oncol. 2012 Oct-Dec;2(4):306-313. doi: 10.1016/j.prro.2011.12.003. Epub 2012 Jan 30. PMID: 24674169.