RESUMO
PURPOSE: The quality of a treatment plan for stereotactic body radiotherapy (SBRT) depends on an experience of each treatment planner. Therefore, the treatment plans are subjectively determined by comparison of several treatment plans developed by time consuming iterative manners, while considering the benefit to a tumor and the risk to the surrounding normal tissues. The aim of our study was to develop an automated optimization method for beam arrangements based on similar cases in a database including plans designed by senior experienced treatment planners. METHODS: Our proposed method consists of three steps. First, similar cases were automatically selected based on image features from the treatment planning point of view. We defined four types of image features relevant to planning target volume (PTV) location, PTV shape, lung size, and spinal cord positional features. Second, the beam angles of the similar case were registered to the objective case with respect to lung regions using a linear registration technique. Third, the beam direction of the objective case was locally optimized based on the cost function considering radiation absorption in normal tissues and organs at risk. The proposed method was evaluated with 10 test cases and a treatment planning database including 81 cases by using eight planning evaluation indices such as D95, lung V20, and maximum spinal cord dose. RESULTS: The proposed method may provide usable beam directions, which have no statistically significant differences with the original beam directions (P > 0.05) in terms of the seven planning evaluation indices. Moreover, the mean value of D95 for 10 test cases was improved with a statistically significant difference by using the proposed method, compared with the original beam directions (P = 0.03). CONCLUSIONS: The proposed method could be used as a computer-assisted treatment planning tool for determination of beam directions in SBRT.
RESUMO
PURPOSE: We developed a novel automated estimation method for patient setup errors based on simulated and real portal images for prostate cancer radiotherapy. METHODS: The estimation of patient setup errors in this study was based on a template matching technique with a cross-correlation coefficient and Sobel filter between the real portal image and localized pelvic template of reference image, which were DRR (digitally reconstructed radiography) images and simulated portal images. The simulated portal image was derived by projecting a CT image according to an inverse exponential power law of x-ray attenuation for a water-equivalent path length of each voxel of the CT image on each ray from a source to each pixel on the EPID (electric portal imaging device). A localized pelvic template of each patient in AP (anterior-posterior) or lateral view was automatically extracted from the DRR or simulated portal images by cropping a rectangular region, which was determined by using the mean pelvic template and four anatomical feature points. We applied the proposed method to three prostate cancer cases, and evaluated it using the residual error between the patient setup error obtained by proposed method and the gold standard setup error determined by two radiation oncologists. RESULTS: The average residual errors of the patient setup error for the DRR and simulated portal images were 0.79 and 1.26 mm in the left-right (LR) direction, 3.17 and 2.05 mm in the superior-inferior (SI) direction, 1.69 and 5.82 mm in the anterior-posterior (AP) direction, 3.84 and 6.94 mm in Euclidean distance (ED), respectively. If we used the simulated portal image for LR and SI directions and the DRR image for AP direction, the Euclidean distance was 3.22 mm. CONCLUSIONS: The proposed method has a potential to correctly estimate patient setup errors for prostate cancer radiotherapy.