title: Toward efficient biomechanical-based deformable image registration of lungs for image-guided radiotherapy.
abstract: Both accuracy and efficiency are critical for the implementation of biomechanical model-based deformable registration in clinical practice. The focus of this investigation is to evaluate the potential of improving the efficiency of the deformable image registration of the human lungs without loss of accuracy. Three-dimensional finite element models have been developed using image data of 14 lung cancer patients. Each model consists of two lungs, tumor and external body. Sliding of the lungs inside the chest cavity is modeled using a frictionless surface-based contact model. The effect of the type of element, finite deformation and elasticity on the accuracy and computing time is investigated. Linear and quadrilateral tetrahedral elements are used with linear and nonlinear geometric analysis. Two types of material properties are applied namely: elastic and hyperelastic. The accuracy of each of the four models is examined using a number of anatomical landmarks representing the vessels bifurcation points distributed across the lungs. The registration error is not significantly affected by the element type or linearity of analysis, with an average vector error of around 2.8 mm. The displacement differences between linear and nonlinear analysis methods are calculated for all lungs nodes and a maximum value of 3.6 mm is found in one of the nodes near the entrance of the bronchial tree into the lungs. The 95 percentile of displacement difference ranges between 0.4 and 0.8 mm. However, the time required for the analysis is reduced from 95 min in the quadratic elements nonlinear geometry model to 3.4 min in the linear element linear geometry model. Therefore using linear tetrahedral elements with linear elastic materials and linear geometry is preferable for modeling the breathing motion of lungs for image-guided radiotherapy applications.
authors: Radiation Medicine Program, Princess Margaret Hospital, University Health Network and the University of Toronto, Toronto, Ontario, Canada. adil.al-mayah@rmp.uhn.on.ca
authors: Adil
authors: A
authors: Al-Mayah
authors: Joanne
authors: J
authors: Moseley
authors: Mike
authors: M
authors: Velec
authors: Kristy
authors: K
authors: Brock
mesh_terms: D001696:Biomechanical Phenomena; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000503:physiopathology / Q000532:radiotherapy; D020342:Finite Element Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D001239:Inhalation; D008168:Lung / Q000000981:diagnostic imaging / Q000503:physiopathology / Q000528:radiation effects*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000503:physiopathology / Q000532:radiotherapy; D055595:Mechanical Phenomena; D008954:Models, Biological; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed