ESTRO 2025 - Abstract Book

S124

Invited Speaker

ESTRO 2025

Abstract: Brachytherapy has been used as an alternative to surgical treatment for penile cancer for many years. There is evidence that, in the early stages of the disease, brachytherapy can be considered a method comparable to surgery regarding local control (LC) and even overall survival (OS). Given its less invasive nature, which allows for the preservation of organ function, brachytherapy appears to be a viable treatment option for patients with early-stage penile cancer. This is particularly important for those at risk of psychological consequences from partial or total penile amputation. In this lecture, we will explore key aspects of anatomy, pathology, and the standards in diagnosis and treatment. We will review literature and focus on determining which patients are most suitable for brachytherapy. Furthermore, we will take a closer look into the procedure itself, examining its steps and outcomes. To conclude, we will discuss strategies for increasing the recognition and acceptance of brachytherapy as a viable treatment option in the future.

4856

Speaker Abstracts Radiation radiobiology unleashed: Cross-disciplinary modelling breakthroughs Heiko Enderling Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA

Abstract:

Several mathematical and statistical approaches are established in radiation oncology, including the widely used Linear Quadratic (LQ) model, Biologically Effective Dose (BED), Tumor Control Probability (TCP), and Normal Tissue Complication Probability (NTCP) models. More recently, mechanistic mathematical models (including ordinary and partial differential equations) have been developed to simulate the nonlinear dynamics during radiation therapy. Mathematical models, calibrated and validated on historic clinical data, have demonstrated remarkable success in identifying innovative treatment protocols that have been subsequently validated in clinical trials in a variety of cancers and treatments. In this lecture, I will introduce the concepts of mathematical modeling and computer simulation for radiobiology and radiation biology. I will summarize cross-disciplinary modeling breakthroughs, and use individual studies to demonstrate the power of such data-driven models to guide clinical decision making, including personalizing radiation dose, dose fractionation, and organ-at-risk sparing. I will demonstrate how such models can help decipher the complex non-linear interactions of cancer cells with the immune system, and how we can develop digital twins and in silico trials to learn how to best deploy radiation to harness the patient’s immune system. I will discuss the role of artificial intelligence and machine learning in ushering in the next chapter of cross disciplinary modeling in radiation science.