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Abstract

Carbon-ion radiotherapy (CIRT) offers highly localized dose delivery and enhanced biological effectiveness. However, its precision also makes it highly sensitive to anatomical changes between treatment fractions. In-vivo monitoring of the dose delivery via detection of secondary radiation has emerged as a non-invasive method for assessing such changes. The ongoing InViMo clinical trial conducted at the Heidelberg Ion-Beam Therapy Center (HIT) and the German Cancer Research Center is evaluating the feasibility of identifying and localizing anatomical changes in patients with skull base tumors by measuring the localization of the primary carbon ions’ breakup (fragments) in the patient. The results are very promising to date. For this purpose, a monitoring system composed of seven mini-trackers was designed and developed in order to measure fragment tracks outside the patient. Interpreting the signals proved highly complex, highlighting the need for access to physical quantities that cannot be measured experimentally, such as the true origin of the fragments. The primary objective of this thesis was to develop, validate, and implement a Monte Carlo (MC) simulation framework for in-vivo monitoring of CIRT. The developed simulation framework, based on the FLUKA MC code, was first validated against experimental data using a single mini-tracker. Thereafter, the framework was extended to simulate the full monitoring system, comprising the seven mini-trackers, and integrated into FICTION, a CT-based dose calculation Monte Carlo environment developed at HIT. It was used to simulate a cohort of eight patients treated at HIT, including retrospective cases, patients from the InViMo study, and a prostate cancer case, all under realistic clinical conditions. Signal analysis demonstrated that shallow anatomical changes, such as nasal swelling or cavity filling, were successfully detected and localized using reconstructed fragment origin. Deep-seated changes, those distant from the detector or near the end of the beam range proved more challenging to resolve. For the prostate case, the signal from the clinical InViMo detection system was found not to be sufficient to capture the changes in the rectal filling. Therefore, an alternative in-table detection system was designed using the simulation framework. A significant improvement in the detectability of such changes was demonstrated. These results highlight the framework’s versatility. In conclusion, an MC–based simulation environment for studying in-vivo treatment monitoring in carbon-ion therapy was established and validated in this thesis. By enabling detailed modeling of the fragment creation and tracking in patient-specific geometries, the framework can be used for a deeper understanding of the complex clinical signal and for the optimization of monitoring strategies. Its flexibility across anatomical sites makes it a highly valuable tool for future investigations of the clinical potential of fragment-based treatment verification.