title: A comparison framework for breathing motion estimation methods from 4-D imaging.
abstract: Motion estimation is an important issue in radiation therapy of moving organs. In particular, motion estimates from 4-D imaging can be used to compute the distribution of an absorbed dose during the therapeutic irradiation. We propose a strategy and criteria incorporating spatiotemporal information to evaluate the accuracy of model-based methods capturing breathing motion from 4-D CT images. This evaluation relies on the identification and tracking of landmarks on the 4-D CT images by medical experts. Three different experts selected more than 500 landmarks within 4-D CT images of lungs for three patients. Landmark tracking was performed at four instants of the expiration phase. Two metrics are proposed to evaluate the tracking performance of motion-estimation models. The first metric cumulates over the four instants the errors on landmark location. The second metric integrates the error over a time interval according to an a priori breathing model for the landmark spatiotemporal trajectory. This latter metric better takes into account the dynamics of the motion. A second aim of this paper is to estimate the impact of considering several phases of the respiratory cycle as compared to using only the extreme phases (end-inspiration and end-expiration). The accuracy of three motion estimation models (two image registration-based methods and a biomechanical method) is compared through the proposed metrics and statistical tools. This paper points out the interest of taking into account more frames for reliably tracking the respiratory motion.
authors: Léon Bérard Cancer Center, 69373 Lyon, France. david.sarrut@creatis.insa-lyon.fr
authors: David
authors: D
authors: Sarrut
authors: Bertrand
authors: B
authors: Delhay
authors: Pierre-Frédéric
authors: PF
authors: Villard
authors: Vlad
authors: V
authors: Boldea
authors: Michael
authors: M
authors: Beuve
authors: Patrick
authors: P
authors: Clarysse
mesh_terms: D000465:Algorithms; D016477:Artifacts; D045853:Exhalation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000502:physiology; D008954:Models, Biological; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods