SU-E-J-243: Possibility of Exposure Dose Reduction of Cone-Beam Computed Tomography in An Image Guided Patient Positioning System by Using Various Noise Suppression Filters

Abstract

Purpose: To investigate the possibility of exposure dose reduction of the cone‐beam computed tomography (CBCT) in an image guided patient positioning system by using 6 noise suppression filters. Methods: First, a reference dose (RD) and low‐dose (LD)‐CBCT (X‐ray volume imaging system, Elekta Co.) images were acquired with a reference dose of 86.2 mGy (weighted CT dose index: CTDIw) and various low doses of 1.4 to 43.1 mGy, respectively. Second, an automated rigid registration for three axes was performed for estimating setup errors between a planning CT image and the LD‐CBCT images, which were processed by 6 noise suppression filters, i.e., averaging filter (AF), median filter (MF), Gaussian filter (GF), bilateral filter (BF), edge preserving smoothing filter (EPF) and adaptive partial median filter (AMF). Third, residual errors representing the patient positioning accuracy were calculated as an Euclidean distance between the setup error vectors estimated using the LD‐CBCT image and RD‐CBCT image. Finally, the relationships between the residual error and CTDIw were obtained for 6 noise suppression filters, and then the CTDIw for LD‐CBCT images processed by the noise suppression filters were measured at the same residual error, which was obtained with the RD‐CBCT. This approach was applied to an anthropomorphic pelvic phantom and two cancer patients. Results: For the phantom, the exposure dose could be reduced from 61% (GF) to 78% (AMF) by applying the noise suppression filters to the CBCT images. The exposure dose in a prostate cancer case could be reduced from 8% (AF) to 61% (AMF), and the exposure dose in a lung cancer case could be reduced from 9% (AF) to 37% (AMF). Conclusion: Using noise suppression filters, particularly an adaptive partial median filter, could be feasible to decrease the additional exposure dose to patients in image guided patient positioning systems.