Performance studies of four-dimensional cone beam computed tomography

Abstract

Four-dimensional cone beam computed tomography (4DCBCT) has been proposed to characterize the breathing motion of tumors before radiotherapy treatment. However, when the acquired cone beam projection data are retrospectively gated into several respiratory phases, the available data to reconstruct each phase is under-sampled and thus causes streaking artifacts in the reconstructed images. To solve the under-sampling problem and improve image quality in 4DCBCT, various methods have been developed. This paper presents performance studies of three different 4DCBCT methods based on different reconstruction algorithms. The aims of this paper are to study (1) the relationship between the accuracy of the extracted motion trajectories and the data acquisition time of a 4DCBCT scan and (2) the relationship between the accuracy of the extracted motion trajectories and the number of phase bins used to sort projection data. These aims will be applied to three different 4DCBCT methods: conventional filtered backprojection reconstruction (FBP), FBP with McKinnon-Bates correction (MB) and prior image constrained compressed sensing (PICCS) reconstruction. A hybrid phantom consisting of realistic chest anatomy and a moving elliptical object with known 3D motion trajectories was constructed by superimposing the analytical projection data of the moving object to the simulated projection data from a chest CT volume dataset. CBCT scans with gantry rotation times from 1 to 4 min were simulated, and the generated projection data were sorted into 5, 10 and 20 phase bins before different methods were used to reconstruct 4D images. The motion trajectories of the moving object were extracted using a fast free-form deformable registration algorithm. The root mean square errors (RMSE) of the extracted motion trajectories were evaluated for all simulated cases to quantitatively study the performance. The results demonstrate (1) longer acquisition times result in more accurate motion delineation for each method; (2) ten or more phase bins are necessary in 4DCBCT to ensure sufficient temporal resolution in tumor motion and (3) to achieve the same performance as FBP-4DCBCT with a 4 min data acquisition time, MB-4DCBCT and PICCS-4DCBCT need about 2- and 1 min data acquisition times, respectively.

Figure 1

Hybrid digital phantom used in this study, in which an elliptical object is added into the left lung cavity of a human chest CT data set. (a) Axial view of the phantom at 0% phase. (b, c)Coronal views of the phantom at 0% and 50% phase, respectively. (d) Periodic model used to define the motion and deformation of the tumor-simulating object.

Figure 2

FBP-4DCBCT images using different acquisition times and numbers of phase bins. (a, b) Axial slices and coronal slices, respectively. Column 1–3: 5, 10 and 20 phase bins, respectively. Row 1–4: 1, 2, 3 and 4 min data acquisition times, respectively. The bottom row shows the ground truth. The display window is [−0.005, 0.03] mm⁻¹.

Figure 3

MB-4DCBCT images using different acquisition times and numbers of phase bins. (a, b)Axial slices and coronal slices, respectively. Column 1–3: 5, 10 and 20 phase bins, respectively. Row 1–4: 1, 2, 3 and 4 min data acquisition times, respectively. The bottom row shows the ground truth. The display window is [−0.005, 0.03] mm⁻¹.

Figure 4

PICCS-4DCBCT images using different acquisition times and numbers of phase bins. (a, b) Axial slices and coronal slices, respectively. Column 1–3: 5, 10 and 20 phase bins, respectively. Row 1–4: 1, 2, 3 and 4 min data acquisition times, respectively. The bottom row shows the ground truth. The display window is [−0.005, 0.03] mm⁻¹.

Figure 5

Plots of x-motion trajectories of the tumor centroid using different acquisition times and numbers of phase bins.

Figure 6

Plots of y-motion trajectories of the tumor centroid using different acquisition times and numbers of phase bins.

Figure 7

Plots of z-motion trajectories of the tumor centroid using different acquisition times and numbers of phase bins.

Figure 8

RMSE_max plots of the extracted motion trajectories from 4DCBCT images obtained by different methods. The ‘full-fan’ setup is used here. (a, b) Use 10 and 20 phase bins, respectively.

Figure 9

RMSE_max plots of the extracted motion trajectories from 4DCBCT images obtained by different methods. The ‘half-fan’ setup is used here. (a, b) Use 10 and 20 phase bins, respectively.