Integration of the lung motion into 3D phantoms

Introduction Currently, S factor computations in internal radiation therapy or TPS quality controls in external radiation therapy are only performed in 3D, i.e. without taking into account physiological or metabolic movements. That is why we propose to add a dimension representing time to the IRSN phantoms and thus enable these protocols in 4D. Materials and methods The NEMOSIS platform (based on an Artificial Neural Network – ANN) has already been presented and validated in previous works, which were dedicated to the customized simulation of internal lung motions. To adapt it to phantoms that were determined according to anthroporadiametric data, new entries (perimeter and height of a cylinder representing the lungs) were added to the ANN. The IRSN phantoms (12 phantoms of heights varying between 165 and 185 cm) only account for the organ contours. To make NEMOSIS able to proceed these contours, we have elaborated an algorithm that automatically tracks the evolutions of the lung contours of each patient on every 4DCT. After the learning step of the patient data, our platform is used to simulate the motion of phantoms. Results Thanks to this approach, 32,480 points were computed and added to our dataset, which is constituted of 16 patients over 10 respiratory phases. The similarity index, calculated between the simulated volumes and 4D, is strictly greater than 0.94 and thus allow the validation of our approach applied to a test patient. The motion of the phantoms computed by NEMOSIS is consistent and represents realistic variations according to the lung localization and phase. The hysteresis is also depicted, but measured variation of the lung volume for this phantom is of only 0.185 l. Conclusion Perspectives: Despite very promising results, the quality of the motion simulation can still be improved by taking into account the deformation of the diaphragm. However, our 4D simulation of the lung motion of phantoms can already be validated.