Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10731338 | Physica Medica | 2016 | 6 Pages |
Abstract
Respiratory movement information is useful for radiation therapy, and is generally obtained using 4D scanners (4DCT). In the interest of patient safety, reducing the use of 4DCT could be a significant step in reducing radiation exposure, the effects of which are not well documented. The authors propose a customized 4D numerical phantom representing the organ contours. Firstly, breathing movement can be simulated and customized according to the patient's anthroporadiametric data. Using learning sets constituted by 4D scanners, artificial neural networks can be trained to interpolate the lung contours corresponding to an unknown patient, and then to simulate its respiration. Lung movement during the breathing cycle is modeled by predicting the lung contours at any respiratory phases. The interpolation is validated comparing the obtained lung contours with 4DCT via Dice coefficient. Secondly, a preliminary study of cardiac and Åsophageal motion is also presented to demonstrate the flexibility of this approach. The application may simulate the position and volume of the lungs, the Åsophagus and the heart at every phase of the respiratory cycle with a good accuracy: the validation of the lung modeling gives a Dice index greater than 0.93 with 4DCT over a breath cycle.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Radiation
Authors
Pierre-Emmanuel Leni, Rémy Laurent, Michel Salomon, Régine Gschwind, Libor Makovicka, Julien Henriet,