Prospective displacement and velocity-based cine 4D CT.
Four dimensional (4D) computed tomography (CT) image sorting is currently a retrospective procedure. Mismatches in displacement and/or phase of a patient's respiratory signal, corresponding with two dimensional images taken at subsequent couch positions, become visible as artifacts in reconstructed 4D CT images. These artifacts appear as undefined or irregular boundaries in the 4D CT images and cause systematic errors in patient contouring and dose calculations. In addition, the substantially higher dose required for 4D CT, compared with 3D CT, is of concern. To minimize these problems, we developed a prospective respiratory displacement and velocity based cine 4D CT (PDV CT) method to trigger image acquisition if the displacement and velocity of the respiratory signal occurred within predetermined tolerances simultaneously. The use of velocity avoids real-time phase estimation. Real-time image acquisition ensures data sufficiency, while avoiding the need for redundant data. This may potentially result in a lower dose to the patient. PDV CT was compared with retrospective 4D CT acquisition methods, using respiratory signals of 24 lung cancer patients (103 sessions) under free breathing conditions. Image acquisition was simulated for each of these sessions from the respiratory signal. The root mean square (RMS) of differences between displacements and velocities of the respiratory signal corresponding to subsequent images was calculated in order to evaluate the image-sorting accuracy of each method. Patient dose reductions of 22 to 50% were achieved during image acquisition depending on the model parameters chosen. The mean RMS differences over all sessions and image bins show that PDV CT produces similar results to retrospective displacement sorting overall, although improvements of the RMS difference up to 20% were achieved depending on the model parameters chosen. Velocity RMS differences improved between 30 and 45% when compared with retrospective phase sorting. The efficiency in acquisition compared with retrospective phase sorting varied from approximately 10% for displacement and velocity tolerances of 1 mm and 4 mm/s, respectively, to 80 to 93% for 4 mm and 4 mm/s. The lower variation in the displacement and velocity of the respiratory signal in each image bin indicates that PDV CT could be a valuable tool for reducing artifacts in 4D CT images and lowering patient dose, although the cost may be increased acquisition time.
Langner
U W
UW
Department of Radiation Oncology, Radiation Physics Division, Stanford University Cancer Center, 875 Blake Wilbur Drive, Stanford, California 94305-5847, USA. ulangner@stanford.edu
Keall
P J
PJ
D000465:Algorithms; D016477:Artifacts; D009038:Motion; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014741:Video Recording / Q000379:methods*