A patient specific respiratory model based on 4D CT data and a time of flight camera (TOF)

Respiratory motion is an important factor leading to errors and uncertainties in radiation therapy (RT). Solutions presented to date include modeling tumor and surrounding tissues motion. Having such a model is a key point to deliver, under breathing induced motion, less dose to the normal healthy tissues and higher dose to the tumor. Many continuous motion models have been developed based on 4D CT data. All these models are reconstructed using, for instance, an external respiratory signal (RPM or respiratory belt) or the diaphragm position. Possible limitations of these models are cases where the correlation between the respiratory motion and the corresponding surrogate is less reliable. In this paper, we describe an approach based on the creation of a continuous patient specific model that takes into account respiratory signal irregularities and uses, as surrogate, a surface map acquired using a time of flight camera. This model has been validated on three patients. Our results show that using the time of flight camera surface maps for the model reconstruction and application leads to higher accuracy compared to the use of a 1D respiratory signal.