S1450
Interdisciplinary - Other
ESTRO 2026
distinct groups based on the selected variables, with cluster sizes ranging from 10,000 to 50,000 individuals. Specifically, Cluster 4 demonstrated a significant increase in PC incidence (Figure 1). Interestingly, the Townsend Deprivation Index, serving as a proxy for sociodemographic status, was significantly lower in Cluster 4 compared to other groups. While Cluster 4 individuals were older, which is expected for a higher PC incidence, they did not exhibit a high risk PRS. Further characteristics of the identified clusters are presented in Figure 2.
al. Prostate cancer screening with prostate-specific antigen (PSA) test: a systematic review and meta- analysis. BMJ362, k3519 (2018).3.UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction — umap 0.5.8 documentation. https://umap- learn.readthedocs.io/en/latest/. Keywords: Prostate cancer, machine learning, epidemiology Digital Poster Highlight 3539 Sim-less Based Treatments using HyperSight CBCT for Planning and Positioning Amineh O KhatibHamad, Dimitri Bragilovski, Efrat S Gur, Itamar I Avarbuch, Eldor Yukler, Anat Jarufy, Liron Epstein, Omer Gal, Oded Icht, Dror Limon Radiation Therapy, Rabin Medical Center, Petach Tikvah, Israel Purpose/Objective: Palliative and urgent radiotherapy treatments constitute a significant portion of our patient load (30– 50%), often occupying critical slots in the conventional CT simulator (CT). The objective of this study was to evaluate the feasibility of utilizing the HyperSight Cone-Beam Computed Tomography (CBCT) on a TrueBeam LINAC as a sole imaging modality for treatment planning and positioning, with the goal of establishinga "Sim-less" workflow, to reduce treatment delays and enhance patient satisfaction. Material/Methods: A TrueBeam LINAC equipped with HyperSight CBCT provided high spatial resolution images. CT to Electron Density (ED) curves were established for different HyperSight imaging protocols. The curves were approximated into a single curve comparable to literature values and was adopted clinically.A retrospective comparison was performed on 25 patients simulated using a Toshiba CT Simulator. The CBCT images acquired for setup during their actual treatments were used to generate a comparative plan. The patient cohort included a variety of sites treated with static fields, such as bone metastases. The original CT plan and the potential CBCT plan were compared using Dose Volume Histograms (DVH) and dosimetric measurements with the SunNuclear ArcCheck.Following validation, a new Sim-less protocol was implemented for patients requiring palliative static fields. The workflow emphasizes efficiency:Pre- Arrival; Contours for provisional planning are created on the diagnostic imaging.The patient is positioned according to physician setup instructions, and a HyperSight CBCT is acquired and fused with the diagnostic CT for planning.The total procedure time averaged 30 minutes door-to-door including CBCT
Conclusion: This data-driven modeling approach revealed novel risk factors for PC incidence not typically considered in traditional epidemiological studies. Notably, sociodemographic status emerged as a significant determinant of PC incidence, demonstrating an effect size potentially greater than classical risk factors such as age and genetic predisposition. Such data-driven models could be instrumental in identifying population strata at elevated risk for PC, thereby enabling targeted screening programs for those who would benefit most. References: 1.Cancer in Men: Prostate Cancer is #1 for 118 Countries Globally. https://www.cancer.org/research/acs- research-news/prostate-cancer-is-number-1-for-118- countries-worldwide.html (2024).2.Ilic, D. et
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