S3006
Invited Speaker
ESTRO 2026
and image-guided navigation platforms allow real-time monitoring of applicator placement and facilitate intraoperative adjustments, reducing uncertainties and the need for repeated imaging. Emerging robotic- assisted solutions aim to further enhance reproducibility and standardization of needle placement, minimizing operator dependence and improving procedural consistency. Treatment planning is also undergoing significant transformation. Model-based dose calculation algorithms (MBDC), which account for tissue heterogeneities, address the limitations of conventional TG-43-based approaches and provide more accurate and patient-specific dose distributions. These methods are increasingly relevant for advanced treatment sites and support improved prediction of treatment-related toxicity. Artificial intelligence (AI) is rapidly emerging as a key enabler of workflow optimization. AI-driven tools for automated segmentation, inverse planning, and decision support have the potential to substantially reduce planning time, decrease inter-observer variability, and improve overall plan quality. In parallel, modern treatment planning systems incorporate multi-criteria and real-time optimization strategies, further enhancing efficiency and consistency. Personalization is further advanced through the use of patient-specific, 3D-printed applicators, which enable tailored implant geometries for complex anatomies. In addition, adaptive brachytherapy—supported by repeated imaging, deformable image registration, and dose accumulation—allows dynamic treatment adaptation based on anatomical and temporal changes during the treatment course. In summary, the convergence of advanced imaging, real-time navigation, AI-driven automation, and personalized treatment technologies is transforming brachytherapy into a highly precise, adaptive, and data-driven modality. These innovations are expected to play a pivotal role in the future of image-guided, patient-specific brachytherapy and in further improving clinical outcomes. 5333 Brachytherapy workflow optimisation in cervical cancer Inger-Karine Kolkman-Deurloo Dept. of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, Netherlands Image Guided Adaptive Brachytherapy (IGABT) has become the standard of care for primary treatment of Locally Advanced Cervical Cancer (LACC). This transition has been facilitated by the integration of advanced technologies, including MR imaging and
deformation and imaging artifacts continue to challenge precise image registration and target delineation. Thus, balancing the promise of new technologies with the implications for workload, training, and quality is the essential next step in the field. References: 1. Goulet, M. et al. Clinical Application of Deep Learning-Assisted Needles Reconstruction in Prostate Ultrasound Brachytherapy 2. Nicolae, A. et al. Evaluation of a Machine-Learning Algorithm for Treatment Planning in Prostate Low- Dose-Rate Brachytherapy 3. Mao, X. et al. RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning 4. Chen, J. et al. A review of artificial intelligence in brachytherapy 5. Morén, B. et al. A data-driven approach to model spatial dose characteristics for catheter placement of high dose-rate brachytherapy for prostate cancer 6. Mountris, K. A. et al. DVH-Based Inverse Planning Using Monte Carlo Dosimetry for LDR Prostate Brachytherapy 5332 New technologies to improve the workflow in brachytherapy Andre Karius Department of Radiation Oncology, University Hospital Erlangen, Erlangen, Germany Brachytherapy is a cornerstone of modern radiation oncology, enabling the delivery of highly conformal radiation doses to the target while sparing surrounding normal tissues. Owing to steep dose gradients, the precision of applicator placement and the accuracy of treatment planning are critical determinants of both tumor control and toxicity. Recent technological advances are reshaping the brachytherapy workflow toward greater precision, efficiency, and personalization. Image guidance remains central to these developments. In addition to conventional ultrasound, three-dimensional imaging modalities such as cone- beam CT (CBCT) and magnetic resonance imaging (MRI) have significantly improved visualization of anatomy, applicator position, and target volumes. The integration of multimodal imaging workflows, including ultrasound–CBCT fusion and MRI-based planning, enables more accurate implant reconstruction and target delineation, particularly in anatomically complex sites. These advances support the transition toward fully image-guided brachytherapy. Parallel progress has been made in navigation and implantation technologies. Optical tracking systems
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