Model-Based Risk Assessment for Motion Effects in 3D Radiotherapy of Lung Tumors

Although 4D CT imaging becomes available in an increasing number of radiotherapy facilities, 3D imaging and planning is still standard in current clinical practice. In particular for lung tumors, respiratory motion is a known source of uncertainty and should be accounted for during radiotherapy planning - which is difficult by using only a 3D planning CT. In this contribution, we propose applying a statistical lung motion model to predict patients' motion patterns and to estimate dosimetric motion effects in lung tumor radiotherapy if only 3D images are available. Being generated based on 4D CT images of patients with unimpaired lung motion, the model tends to overestimate lung tumor motion. It therefore promises conservative risk assessment regarding tumor dose coverage. This is exemplarily evaluated using treatment plans of lung tumor patients with different tumor motion patterns and for two treatment modalities (conventional 3D conformal radiotherapy and step-&- shoot intensity modulated radiotherapy). For the test cases, 4D CT images are available. Thus, also a standard registration-based 4D dose calculation is performed, which serves as reference to judge plausibility of the modelbased 4D dose calculation. It will be shown that, if combined with an additional simple patient-specific breathing surrogate measurement (here: spirometry), the model-based dose calculation provides reasonable risk assessment of respiratory motion effects.