Information Lecture Speakers

DANIELLE DOBBE-KALKMAN

Educational Advisor. Radboud University Medical Center, Nijmegen, The Netherlands

Danielle Kalkman is an enthusiastic and dedicated educational consultant with extensive experience in designing and improving evidence‑based learning trajectories. With a background in educational sciences and a career spanning medical education, professional development, and curriculum innovation, she has contributed to high‑quality learning at institutions such as Radboudumc Health Academy and the Dutch Expert Centre for Screening (LRCB). Danielle excels at translating research‑based insights into practical, impactful learning solutions.

She is a member of the EFOMP Education and Training Committee and an educational advisor for the EUTEMPE consortium.

SESSION – How to make your presentation radiant!

As a medical physicist you present complex information in many settings, from team meetings to large conferences. Regardless of the audience, the goal is the same: deliver a clear message that is understood and remembered.

This presentation explores two key ingredients for a radiant presentation. First, less is more. By focusing on the core message and avoiding unnecessary detail, you guide your audience along a clear path rather than a maze. Second, connection matters. Engaging with your audience captures attention, improves understanding, and boosts retention. Together, focus and connection add clarity, personality, and radiance to your presentations.

XUN JIA

Professor and Chief of Medical Physics Division. Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University

Xun Jia, PhD, FAAPM, FAIMBE, is a Professor and Chief of the Medical Physics Division in the Department of Radiation Oncology and Molecular Radiation Sciences at the Johns Hopkins University School of Medicine. He also serves as Director of the Medical Physics Education Program and Co-Lead of the Cancer Imaging and Image-Guided Therapy Program within the Sidney Kimmel Comprehensive Cancer Center.

His research focuses on AI-driven treatment planning, advanced medical imaging, and GPU-accelerated physics-based modeling. Dr. Jia leads multiple NIH-funded projects and international collaborations, and is actively involved in professional leadership through professional societies and editorial roles in major journals.

XUN JIA

Professor and Chief of Medical Physics Division. Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University

Xun Jia, PhD, FAAPM, FAIMBE, is a Professor and Chief of the Medical Physics Division in the Department of Radiation Oncology and Molecular Radiation Sciences at the Johns Hopkins University School of Medicine. He also serves as Director of the Medical Physics Education Program and Co-Lead of the Cancer Imaging and Image-Guided Therapy Program within the Sidney Kimmel Comprehensive Cancer Center.

His research focuses on AI-driven treatment planning, advanced medical imaging, and GPU-accelerated physics-based modeling. Dr. Jia leads multiple NIH-funded projects and international collaborations, and is actively involved in professional leadership through professional societies and editorial roles in major journals.

SESSION – Building intelligence in radiotherapy treatment planning

Radiotherapy treatment planning is inherently a complex decision-making process spanning multiple interconnected tasks, including target and organ delineation, prescription, plan optimization, and quality assurance. In recent years, artificial intelligence has enabled the development of powerful tools that address individual components of this workflow with growing success.

With the emergence of advanced AI decision-making capabilities, particularly foundation models and multi-agent systems, it is now both necessary and feasible to move beyond isolated tools toward building holistic, intelligent treatment planning workflows. This talk overviews this emerging paradigm and highlights recent research efforts that integrate AI across the full planning pipeline.

SERENA PSOROULAS

Senior Scientist / Medical Physicist in training. University Hospital Zurich

I am a medical physicist and senior scientist from Switzerland. My core expertise is in beam delivery, applied to photon C-arm linacs and proton gantries. My research activities focus on clinical implementation of new radiobiological concepts in clinical practice, focusing on spatially fractionated radiotherapy and ultra-high dose rates treatments (FLASH irradiations). I love working alongside clinicians, biologists and technicians, and with them trying to test the limits of conventional concepts. I also have expertise in innovative treatments for motion mitigation and treatments of moving tumors with protons.

SESSION – Technology meets biology: dose rates and FLASH – precision and spatial fractionation

Technology development in radiotherapy has given us tremendous advanced in precision and accuracy. However, for curious minds such as physicists’, the next challenge already approaches: can we improve treatments outcomes using biological effects? Preclinical experiments show remarkable results in term of normal tissue sparing and improvements of tumor control, using techniques such as FLASH and spatial fractionation (SFRT).

Moving them to the clinic however requires additional effort – not only from the technology development. I will review in this presentation my experience in implementing FLASH and SFRT in clinical practice, highlighting the challenges still awaiting in this field.

LUISA ALTABELLA

Senior Medical Physicist specializing in Quantitative MRI and MR-Guided Adaptive Radiotherapy. AOUI Verona

I completed my studies in Medical Physics in 2015, following research at Italian National Institute of Health focused on preclinical MR imaging. Since then, I have specialized in quantitative MRI for clinical body and neuro applications. I have also gained significant experience in radiotherapy, mainly in imaging application in RT and adaptive radiotherapy. I am currently responsible for the medical physics aspects of the MRI-Linac recently installed in our institution.

I have authored over 30 peer-reviewed publications, coordinate the AIFM-Working Group on MRI Quantification, and served as Scientific Chair for the 2024 EFOMP-AIFM course on Quantitative MRI.

LUISA ALTABELLA

Senior Medical Physicist specializing in Quantitative MRI and MR-Guided Adaptive Radiotherapy. AOUI Verona

I completed my studies in Medical Physics in 2015, following research at Italian National Institute of Health focused on preclinical MR imaging. Since then, I have specialized in quantitative MRI for clinical body and neuro applications. I have also gained significant experience in radiotherapy, mainly in imaging application in RT and adaptive radiotherapy. I am currently responsible for the medical physics aspects of the MRI-Linac recently installed in our institution.

I have authored over 30 peer-reviewed publications, coordinate the AIFM-Working Group on MRI Quantification, and served as Scientific Chair for the 2024 EFOMP-AIFM course on Quantitative MRI.

SESSION – MR – guided radiotherapy: from adaptive to biological optimization Magnetic

Resonance-guided radiotherapy (MRgRT) has transitioned from conventional inter-fractional adjustments to real-time online adaptive radiotherapy, enhancing dose escalation and healthy tissue sparing. The current frontier, biological optimization, leverages functional MRI to map tumor heterogeneity and metabolic response.

Central to this paradigm are Quantitative Imaging Biomarkers (QIB); however, their clinical utility depends on rigorous standardization. Without crossplatform reproducibility and validated acquisition protocols, biological data remains prone to inter-vendor variability. Establishing standardized QIBs is essential to move MRgRT from purely anatomical adaptation toward.

LUC BEAULIEU

Full professor and Associate Dean for research, strategic development and partnerships and Faculty of Sciences and Engineering, Université Laval. Medical Physicist and Senior Researcher. CHU de Québec – Université Laval

Prof. Beaulieu is internationally recognized for his pioneering contributions to radiation therapy dosimetry and for the development of novel technologies and algorithms in radiation medicine, particularly in brachytherapy. He has served on and chaired numerous national and international working and task groups, including within the AAPM and ESTRO. For over two decades, Prof. Beaulieu has collaborated closely with industrial partners on the design, development, and validation of biomedical algorithms and devices, leading to multiple patents and three active industrial licenses.

He has mentored more than 190 highly qualified personnel and authored over 300 peer-reviewed publications. Since 2018, he has been continuously listed among the world’s top 2% most-cited researchers. Prof. Beaulieu is a Fellow of the COMP, AAPM, and ABS.

SESSION – Automation of brachytherapy workflow: recent advances and implementations

Automation has the potential of rapidly transforming brachytherapy by improving efficiency, robustness, and treatment quality. This talk reviews recent advances and clinical implementations of automated brachytherapy workflows, with a focus on real-time tracking, optimization, and artificial intelligence. Electromagnetic tracking is a good example of an enabler for accurate catheter reconstruction and motion awareness, as well as adaptive workflows.

Similarly multi-criteria optimization frameworks are discussed as powerful tools to efficiently explore patient-specific trade-offs between target coverage and organs-at-risk sparing while minimizing clinical planning time. Finally, emerging artificial intelligence approaches are highlighted for key time-consuming tasks, including workflow orchestration, decision support and others. These technologies are paving the way toward adaptive, more reproducible, and truly patient-specific brachytherapy.