A Diffeomorphic Framework for Surrogate-based Motion Estimation in Radiation Therapy: Concept and First Evaluation

Respiratory motion is a major obstacle in radiation therapy of thoracic andabdominal tumors. Techniques to cope with it such as gating and tracking techniquesare based on the use of breathing signals that can be acquired easily and in real-time.These signals represent only surrogates of the motion of the inner organs and tumors.Consequently, methods are needed to estimate respiratory motion patterns of the inter-nal structures based on surrogate measurements.In this contribution, a diffeomorphic framework based on a multi-linear regressionand the Log-Euclidean framework recently introduced in the context of diffeomorphicregistration is proposed to establish such a correspondence model. The feasibility ofthe approach is demonstrated by means of a leave-out evaluation using 4D CT imagesequences of ten lung tumor patients and simulating three different types of breathingsignals: spirometry records, tracking motion of points on the diaphragm, and assessingthe raising/lifting of chest wall points.