Evaluation of 3D fluoroscopic image generation from a single planar treatment image on patient data with a modified XCAT phantom.
Evaluation of 3D fluoroscopic image generation from a single planar treatment image on patient data with a modified XCAT phantom.
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DOI：
10.1088/0031-9155/58/4/841
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发表时间：
2013-02-21
影响因子：
3.5
通讯作者：
Lewis JH
中科院分区：
文献类型：
--
作者：
Mishra P;Li R;James SS;Mak RH;Williams CL;Yue Y;Berbeco RI;Lewis JH
Accurate understanding and modeling of respiration-induced uncertainties is essential in image-guided radiotherapy. Explicit modeling of overall lung motion and interaction among different organs promises to be a useful approach. Recently, preliminary studies on 3D fluoroscopic treatment imaging and tumor localization based on Principal Component Analysis (PCA) motion models and cost function optimization have shown encouraging results. However, the performance of this technique for varying breathing parameters and under realistic conditions remains unclear and thus warrants further investigation. In this work, we present a systematic evaluation of a 3D fluoroscopic image generation algorithm via two different approaches. In the first approach the model’s accuracy is tested for changing parameters for sinusoidal breathing. These parameters included changing respiratory motion amplitude, period, and baseline shift. The effects of setup error, imaging noise and different tumor sizes are also examined. In the second approach, we test the model for anthropomorphic images obtained from a modified XCAT phantom. This set of experiments is important as all the underlying breathing parameters are simultaneously tested, as in realistic clinical conditions. Based on our simulation results for more than 250 seconds of breathing data for 8 different lung patients, the overall tumor localization accuracy of the model in left-right (LR), anterior-posterior (AP) and superior-inferior (SI) directions are 0.1 ± 0.1 mm, 0.5 ± 0.5 mm and 0.8 ± 0.8 mm respectively. 3D tumor centroid localization accuracy is 1.0 ± 0.9 mm.
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影响因子：
3.5
作者：
Mishra P;St James S;Segars WP;Berbeco RI;Lewis JH
通讯作者：
Lewis JH
影响因子：
3.5
作者：
Söhn, M;Birkner, M;Alber, M
通讯作者：
Alber, M
影响因子：
3.8
作者：
Zhang, Qinghui;Pevsner, Alex;Mageras, Gig S.
通讯作者：
Mageras, Gig S.
影响因子：
3.8
作者：
Xu, Qianyi;Hamilton, Russell J.;Jiang, Steve B.
通讯作者：
Jiang, Steve B.
影响因子：
7.8
作者：
Hyvärinen, A;Oja, E
通讯作者：
Oja, E