Scanned ion beam therapy of lung tumors is severely limited in its clinical applicability by intrafractional organ motion, interference effects between beam and tumor motion (interplay) as well as interfractional anatomic changes. To compensate for dose deterioration by intrafractional motion, motion mitigation techniques, such as gating have been developed. The latter confines the irradiation to a predetermined breathing state, usually the stable end-exhale phase. However, optimization of the treatment parameters is needed to further improve target dose coverage and normal tissue sparing. The aim of the study presented in this dissertation was to determine treatment planning parameters that permit to recover good target coverage and homogeneity during a full course of lung tumor treatments. For 9 lung tumor patients from MD Anderson Cancer Center (MDACC), a total of 70 weekly time-resolved computed tomography (4DCT) datasets were available, which depict the evolution of the patient anatomy over the several fractions of the treatment. Using the GSI in-house treatment planning system (TPS) TRiP4D, 4D simulations were performed on each weekly 4DCT for each patient using gating and optimization of a single treatment plan based on a planning CT acquired prior to treatment. It was found that using a large beam spot size, a short gating window (GW), additional margins and multiple fields permitted to obtain the best results, yielding an average target coverage (V95) of 96.5%. Two motion mitigation techniques, one approximating the rescanning process (multiple irradiations of the target with a fraction of the planned dose) and one combining the latter and gating, were then compared to gating. Both did neither show an improvement in target dose coverage nor in normal tissue sparing. Finally, the total dose delivered to each patient in a simulation of a fractioned treatment was calculated and clinical requirements in terms of target coverage and normal tissue sparing were considered. The results showed that the total V95 obtained for the entire course of the treatment was similar to the one obtained for the planning CT, which shows that interfractional variability was successfully compensated. For 4 patients out of 9, V95 > 95% was thus obtained for both the planning CT and the total dose target coverage. For the rest of the cohort, a slight modification of the contours or dose reduction should permit to obtain a better clinical treatment plan that could be delivered over the course of the treatment. In the presented study, intrafractional motion occuring during the treatment of lung tumors was efficiently mitigated using optimized treatment planning parameters and gating, while interfractional variability showed the largest impact on dose delivery. Nevertheless, this variability was efficiently mitigated, as shown by target dose coverage obtained at the end of the treatment which was very close to the one obtained for the planning CT.