Monte Carlo simulation of region-of-interest reconstruction for real-time tumor tracking by OpenPET

We are developing the OpenPET which can provide an open space to make the patient observable and accessible during PET measurements. In addition, we have proposed a real-time imaging system for the OpenPET which is expected to be used in PET-guided tumor tracking radiation therapy. We conducted a feasibility study on tumor tracking using 18F-FDG by Monte Carlo simulation of a human body-sized OpenPET and showed that the tumor tracking is feasible with a time window of 0.5 s if the tumor contains sufficient radioactivity. Although we have demonstrated real-time tumor tracking using a small OpenPET prototype, the delay was 2 s. On a human body scale, the image matrix size become huge compared to the body size of the small prototype and delay can be increased. Therefore, further improvement of the reconstruction speed is essential. From this viewpoint, image reconstruction of the entire field-of-view (FOV) is time consuming and not required for the purpose of tumor tracking. In this study, we developed a region-of-interest (ROI) reconstruction method for the OpenPET and evaluated the tumor tracking accuracy. Although conventional wisdom states that the ROI reconstruction requires a priori information of a small region inside the ROI and 180° scanning without angular truncation for accurate image reconstruction, the computer simulation showed that the ROI reconstruction method without any a priori information had equivalent accuracy in terms of tumor tracking compared with the case reconstructing the entire region. The ROI reconstruction method was more than 10 times faster than the entire FOV reconstruction method.