Iterative motion-compensated reconstruction for image-guided radiation therapy

In image-guided radiation therapy (IGRT) an additional kV imaging system next to the linear particle accelerator provides information for an accurate patient positioning. However, due to the limited gantry rotation speed during treatment the typical acquisition time is much longer than the patient´s breathing cycle resulting in low image quality. In particular, respiratory motion causes severe artifacts such as blurring and streaks in tomographic images. Compensating for motion is an interesting option and capable of providing high quality respiratory-correlated 4D volumes. The particular challenge is to do this without knowledge from prior scans and without specific requirements on the acquisition. State-of-the-art methods for estimation of the motion vector fields suffer from image artifacts that appear in intermediated image frames. In applications like ours conventional registration algorithms tend to register artifacts rather than anatomy. Our proposed registration method addresses the image artifact problem by additionally using temporal constraints within the registration process like the cyclic motion patterns of respiration. This cyclic regularization avoids the algorithm being sensitive to the above-mentioned streak artifacts. Hence, this registration algorithm consists of two components, the spatial and the temporal part, and one of them might be dominating. For this very reason the cyclic registration method is supplemented by an iterative refinement to avoid a potential underestimation of motion and simultaneously to comply with the temporal constraints. The iterative and cyclic registration method is verified using simulated rawdata and patient data. It shows low sensitivity on image artifacts and deals with potential underestimation of motion at the same time. In this way, the motion is accurately estimated and a motion compensation corrects for it. Our iterative and cyclic registration method is capable of high quality motion estimation only on bas- s of respiratory-correlated reconstructions. Thus, motion-compensated image reconstruction without knowledge from prior scans and without specific requirements on the acquisition becomes feasible in image-guided radiation therapy.