Automatic setup deviation measurements with electronic portal images for pelvic fields

Abstract

The purpose of this work was to develop a fully automatic tool for the detection of setup deviation for small pelvic field using, in external beam radiotherapy, an electronic portal imaging device (EPID). The algorithm processes electronic portal images of prostate cancer patients. No fiducial points or user interventions are needed. Deviation measurements are based on bone edge detection performed with Laplacian of a Gaussian (LoG) operator. Two bone edge images are then correlated, one of which is a reference image taken as the first fraction image for the purpose of this study. The electronic portal images (EPI) also show band artefacts which are removed using the morphological top-hat transform. The algorithm was first validated with 59 phantom images acquired in clinical treatment conditions with known displacements. The algorithm was then validated with 79 clinical images where bone contours were delineated manually. For the phantom images, the setup deviations were measured with a absolute mean error of 0.59 mm and 0.47 mm with a standard deviation of 0.64 mm and 0.42 mm, horizontally and vertically, respectively. A second validation was performed using clinical prostate cancer images. The measured patient displacements have an absolute mean error of 0.48 mm and 1.41 mm with a standard deviation of 0.58 mm and 1.30 mm in the X and Y directions, respectively. The algorithm execution time on a SUN workstation is 5 s. This algorithm shows good potential as a setup deviation measurement tool in clinical practice. The possibility of using this algorithm combined with decision rules based on statistical observations is very promising.

Automated 2D–3D registration of portal images and CT data using line‐segment enhancement

“…A number of semiautomated 1-4 and fully automated [5][6][7][8][9][10][11][12][13][14] 2D-2D registration methods have been developed for the determination of setup errors in prostate radiotherapy. A limitation of 2D-2D registration methods is that they are typically unable to accurately estimate all six transformation parameters, especially in the presence of out-of-plane displacements.…”

Portal imaging

“…This technique becomes less robust as the amount of information in the images decreases, with the failure rate increasing from 1% in large anteroposterior pelvic fields to 15% in small anteroposterior pelvic fields [116]. Other algorithms include core-based image analysis [117], cross-correlation [97,[118][119][120] and wavelet analysis [103]. Some of these algorithms work without any operator delineation of structures [97,103,119].…”

<title>Creation of a reference image with Monte Carlo simulations for online EPID verification of daily patient setup</title>

“…[27] First, two binary edge images are created, then the software automatically finds the best match and determines the spatial shifts between the reference and test images.…”