Respiratory motion estimation from cone-beam projections using a prior model.
Respiratory motion introduces uncertainties when planning and delivering radiotherapy for lung cancer patients. Cone-beam projections acquired in the treatment room could provide valuable information for building motion models, useful for gated treatment delivery or motion compensated reconstruction. We propose a method for estimating 3D+T respiratory motion from the 2D+T cone-beam projection sequence by including prior knowledge about the patient's breathing motion. Motion estimation is accomplished by maximizing the similarity of the projected view of a patient specific model to observed projections of the cone-beam sequence. This is done semi-globally, considering entire breathing cycles. Using realistic patient data, we show that the method is capable of good prediction of the internal patient motion from cone-beam data, even when confronted with interfractional changes in the breathing motion.
Vandemeulebroucke
Jef
J
University of Lyon, CREATIS-LRMN, France.
Kybic
Jan
J
Clarysse
Patrick
P
Sarrut
David
D
D000465:Algorithms; D016477:Artifacts; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging* / Q000502:physiology*; D009068:Movement / Q000502:physiology; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology*; D012680:Sensitivity and Specificity