ESTRO 2025 - Abstract Book

S678

Clinical - CNS

ESTRO 2025

Results: 290 lesions in 205 patients received SR. 57 patients met the selection criteria. Most common histologies were non small cell lung cancer and breast cancer. Median lesion volume was 4.9 cm³, with a prescribed dose of 24 Gy in 3 fractions. 29.82% received single-fraction treatment, and 33.3% had whole-brain radiation therapy afterwards. At a median follow-up of 12.5 months, 75% exhibited radiological signs of RN and 25% of tumor progression. Most RN cases were grade 2 (60%), with only 14% grade 3 or higher (CTCAE v5.0). Ten patients had surgical resection; true progression was confirmed in six. Lesion volume and time to progression showed no significant difference between RN and tumor progression groups. The analyzed radiomic features showed different values for patients who experienced progression and radionecrosis, but lacked statistical significance. The NGLDM (neighboring gray level dependence) feature approached significance. The mean values for each radiomic feature and their statistical significance are illustrated in the figures accessible via the QR code. Conclusion: In this single-center cohort, our data highlight the diagnostic uncertainty of RN after SR for brain metastases. Radiomic analysis can differentiate RN from tumor progression, reducing invasive procedures like surgery. A unified workflow across centers is crucial for advancing therapeutic decision support tools. References: Garsa A, Jang JK, Baxi S, Chen C, Akinniranye O, Hall O, et al. Radiation therapy for brain metastases: a systematic review. Pract Radiat Oncol. 2021;11(5):354-65. doi: 10.1016/j.prro.2021.04.002. Nowakowski A, Lahijanian Z, Panet-Raymond V, Siegel PM, Petrecca K, Maleki F, et al. Radiomics as an emerging tool in the management of brain metastases. Neurooncol Adv. 2022;4(1):vdac141. doi: 10.1093/noajnl/vdac141. Peng L, Parekh V, Huang P, Lin DD, Sheikh K, Baker B, et al. Distinguishing true progression from radionecrosis after stereotactic radiation therapy for brain metastases with machine learning and radiomics. Int J Radiat Oncol Biol Phys. 2018;102(4):1236-43. doi: 10.1016/j.ijrobp.2018.05.041. Keywords: radiosurgery, radionecrosis, radiomics

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Proffered Paper Ten-year tumour control, functional preservation with high-precision conformal RT in paediatric craniopharyngiomas – subset results of a Phase-3 RCT Rakesh Jalali 1,2 , Jayant S Goda 2 , Suman Ghosh 2 , Abhishek Chatterjee 2 , Savita Goswami 3 , Nalini Shah 4 , Debnarayan Dutta 2 , Uday Krishna 1 , Tejpal Gupta 2