Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy

Scientific Reports
Haibin ChenXuejun Gu

Abstract

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intr...Continue Reading

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Citations

Dec 13, 2018·Physics in Medicine and Biology·Haibin ChenXuejun Gu

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Methods Mentioned

BETA
imaging techniques
X-ray
PCA

Software Mentioned

Brainlab ExacTrac
SurphaMod
ExacTrac
DIR
RoiMod
Vero
TOP
AlighRT
SurMod
GPU

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