Development of a 4D numerical chest phantom with customizable breathing

被引:2
|
作者
Leni, Pierre-Emmanuel [1 ]
Laurent, Remy [1 ]
Salomon, Michel [2 ]
Gschwind, Regine [1 ]
Makovicka, Libor [1 ]
Henriet, Julien [1 ]
机构
[1] Univ Bourgogne Franche Comte, UMR CNRS 6249, IRMA Chronoenvironm Lab, Besancon, France
[2] Univ Bourgogne Franche Comte, UMR CNRS 6174, FEMTO ST Lab, Besancon, France
来源
关键词
Artificial neural network; Radiation physics; Phantoms; Breath simulation; MOTION ESTIMATION; LUNG MOTION; MODELS;
D O I
10.1016/j.ejmp.2016.05.004
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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 oesophageal motion is also presented to demonstrate the flexibility of this approach. The application may simulate the position and volume of the lungs, the oesophagus 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. (C) 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:795 / 800
页数:6
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