title: Patient specific respiratory motion modeling using a limited number of 3D lung CT images.
abstract: To build a patient specific respiratory motion model with a low dose, a novel method was proposed that uses a limited number of 3D lung CT volumes with an external respiratory signal. 4D lung CT volumes were acquired for patients with in vitro labeling on the upper abdominal surface. Meanwhile, 3D coordinates of in vitro labeling were measured as external respiratory signals. A sequential correspondence between the 4D lung CT and the external respiratory signal was built using the distance correlation method, and a 3D displacement for every registration control point in the CT volumes with respect to time can be obtained by the 4D lung CT deformable registration. A temporal fitting was performed for every registration control point displacements and an external respiratory signal in the anterior-posterior direction respectively to draw their fitting curves. Finally, a linear regression was used to fit the corresponding samples of the control point displacement fitting curves and the external respiratory signal fitting curve to finish the pulmonary respiration modeling. Compared to a B-spline-based method using the respiratory signal phase, the proposed method is highly advantageous as it offers comparable modeling accuracy and target modeling error (TME); while at the same time, the proposed method requires 70% less 3D lung CTs. When using a similar amount of 3D lung CT data, the mean of the proposed method's TME is smaller than the mean of the PCA (principle component analysis)-based methods' TMEs. The results indicate that the proposed method is successful in striking a balance between modeling accuracy and number of 3D lung CT volumes.
authors.affiliation: Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130000, China University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Xueli
authors.initials: X
authors.lastname: Cui
authors.affiliation: Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Gao
authors.affiliation: Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Xia
authors.affiliation: Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
authors.forename: Yangchuan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
authors.forename: Zhiyuan
authors.initials: Z
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging* / Q000502:physiology*; D008954:Models, Biological; D009068:Movement / Q000502:physiology*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology*; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: 4D lung CT; Motion model; deformable registration; external respiratory signal; temporal fitting