Garchinger Maier-Leibnitz-Kolloquium: The Quest for Precise Proton Therapy: Enhancing Conformality and Robustness?

by Prof. Stefan Both (University Medical Center Groningen, University of Groningen, Netherlands)

Thursday 27 Nov 2025, 16:15 → 17:15 Europe/Berlin

Lecture Hall, ground floor (west) (LMU building, Am Coulombwall 1, campus Garching)

Emerging technologies in physics, imaging, beam delivery and predicted outcomes are significantly advancing both conformality and robustness in proton therapy. High-fidelity synthetic CT generation from 3D/4D Cone Beam CT improves the accuracy of stopping-power maps by reducing registration errors and modality-dependent uncertainties. This online enhanced anatomical representation enables sharper dose gradients, tighter margins, and robustness assessment against anatomical, physiological and setup variability. Synthetic imaging also strengthens 4D dose reconstruction by ensuring spatial consistency across respiratory motion phases, providing a more accurate assessment of interplay effects and dose degradation at the time of treatment. Proton arc dose delivery, achieved through multiple static beams or continuous rotational pencil-beam scanning, expands the geometric degrees of freedom for dose modulation. By distributing dose across a large number of beam paths, arc delivery enhances angular sampling, increases conformality and potentially decreases range perturbations compared with conventional limited number of fixed beam angle scanning. Dose-guided patient treatment positioning can further reinforce both conformality and robustness by evaluating delivered dose and predicted outcomes rather than relying solely on anatomical surrogates. Fast Monte Carlo and optimization may enable near real time detection of deviations in coverage and predicted outcomes, allowing corrections based on clinically meaningful metrics towards value-based treatment adaptation. Together, these innovations form a physics driven framework for highly precise, adaptive, and resilient proton therapy.

Hybrid access via ZOOM:
https://lmu-munich.zoom.us/j/98457332925?pwd=TWc3V1JkSHpyOTBPQVlMelhuNnZ1dz09
Meeting ID: 984 5733 2925
Passcode: 979953

kolloquium-27-11-25.pdf