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Breathing-induced tumor motion is a major source of uncertainty during radiotherapy treatment of lung cancer patients. This research developed a methodology to quantify breathing-induced anatomical motion during radiotherapy treatments using magnetic resonance imaging (MRI).

With a so-called four-dimensional (4D)-MRI, the average breathing motion can be quantified and used to determine patient-specific treatment volumes on the day of treatment, instead of relying on a 4D computed tomography (CT) scan acquired during the treatment preparation phase several days earlier. Due to the uncertainty, healthy lung tissue is irradiated as well to ensure that the tumor receives a sufficient amount of radiation dose. The motion information derived from the 4D-MRI was used to determine the time-weighted average anatomy of the subject. Based on this time-weighted average anatomy, the irradiated volume can be reduced, as the breathing-induced uncertainty is lower. This thesis also investigated whether this method could be used to quantify motion in under half a second, which could enable real-time adaptation of the radiation beam. This was successfully demonstrated in an experiment without a human subject. In other studies, visual biofeedback based on the breathing of the subject was used to regularize and stabilize the breathing of healthy volunteers and one patient during scans. This effectively reduced the breathing variability and thus uncertainties, which in turn can lead to smaller irradiated treatment volumes and, consequently, fewer side effects.