Monitoring tumor motion by real time 2D/3D registration during radiotherapy

Abstract

Background and purpose: In this paper, we investigate the possibility to use X-ray based real time 2D/3D registration for non-invasive tumor motion monitoring during radiotherapy.

Materials and methods: The 2D/3D registration scheme is implemented using general purpose computation on graphics hardware (GPGPU) programming techniques and several algorithmic refinements in the registration process. Validation is conducted off-line using a phantom and five clinical patient data sets. The registration is performed on a region of interest (ROI) centered around the planned target volume (PTV).

Results: The phantom motion is measured with an rms error of 2.56 mm. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is shown. Videos show a good match between X-ray and digitally reconstructed radiographs (DRR) displacement. Mean registration time is 0.5 s.

Conclusions: We have demonstrated that real-time organ motion monitoring using image based markerless registration is feasible.

Fig. 1

Illustration of the method used to define the ROI for the clinical patient data sets. The contours of the planning CT from DICOM-RT data (a) were used to derive a 3D surface model of the organs, PTV and CTV (b, only the 3D model of the right lung is shown); the points that define the vertices of the 3D surface model were projected into the 2D X-ray imaging plane using the first transformation matrix T_init (c). The convex hull that enclosed all points of the organs is shown in (d). The convex hull of the PTV was used as the ROI for the 2D/3D registration.

Fig. 2

The patient data sets used for off-line validation of the method. One representative slice of the CT planning data for each patient with the contours of the right lung (green), left lung (magenta), CTV (cyan) and PTV (red) is shown in the first row. The second row shows the initial X-rays with the contours projected by the help of the initial transformation matrix T_init, the projected PTV is the ROI used for the registration of the X-ray to the CT planning.

Fig. 3

Recorded displacements of the phantom extracted by 2D/3D registration with 5 dofs. The first row (a) depicts the translations and rotations parameters obtained after each X-ray registration. (b) The reconstructed motion of the centroid of the cylinder along CC (blue line), LR (green line), AP (red line) directions. The black dotted line represents the movement of the phantom recorded by a tracking system. (c) A screenshot of video1.mpg (available online) showing checkerboard images of X-ray and corresponding registered DRR images acquired during phantom motion. Please note that the frame rate of the reconstructed videos is 5 Hz (about the acquisition rate of the X-ray imager), and not the actual speed of the registration (which is about 2 Hz).

Fig. 4

Reconstructed motion of the centroid of the tumor along CC (blue line), LR (green line), AP (red line) directions for patients 1, 2, 3 and 5. The diaphragm motion of each patient is also shown (except for patient 4) as a black dotted line. Note that the displacement scale is different for each plot.