Background and Motivation:
The anatomical differences between upright and conventional supine or prone positioning in radiotherapy are significant, which presents new challenges in upright treatment planning. Comprehensively understanding anatomic differences and associated dosimetric impacts is essential to define clinical indication and treatment workflow for Upright RT.
Goal:
A comprehensive set of image datasets for the listed anatomical sites for upright treatment simulations encompassing both imaging and treatment planning and comparative upright vs. supine studies.
Tasks:
My name is Daniel Richter, I am originally from Germany and am now pursuing my PhD in physics. I started my PhD in September 2025 at the Paul Scherrer Institute (PSI), where I am hosted at the Centre for Proton Therapy (CPT) under the supervision of Dr. Ye Zhang (tenured scientist at CPT/PSI), who is also my mentor at PSI. I studied Physics at Heidelberg University (Germany), earning both my Bachelor’s and Master’s degrees with a focus on fundamental and computational physics. During my Master’s thesis at the German Cancer Research Center (DKFZ), I worked on optical imaging techniques for fluorescent cancer research, which helped me build a strong foundation in quantitative imaging and computational analysis.
In the UPLIFT project DC17, “Anatomical Differences Analysis,” my role is to investigate and quantify the anatomical changes that occur when a patient moves from a traditional supine (lying down) position to an upright position. I focus on understanding how gravity-driven shifts in organ position and tissue shape can affect radiotherapy and proton therapy, where accurate targeting is crucial for tumor control while sparing healthy tissue. To achieve this, I develop and apply robust, data-driven methods that measure and characterize these differences, with the goal of translating the results into solutions that support personalized and adaptive treatment strategies. I chose this topic because I wanted to move from preclinical imaging toward clinically impactful research that combines computational and experimental approaches.
What motivates me personally is working on problems where physics, modern AI-driven medical imaging, and real-world clinical constraints meet—and where improvements can directly benefit patients. In UPLIFT’s interdisciplinary environment, I expect to advance my research skills, strengthen my professional profile, and build an international network that will support my long-term development as a researcher. Outside the lab, I enjoy rock climbing and skiing, which help me stay active and bring the same persistence and problem-solving mindset into my work.
