For pretreatment QA, the authors found that this tool allowed verification of dwell positions and dwell times in about 6 min.
PurposeThree-dimensional printing has been implemented at our institution to create customized treatment accessories, including lead shields used during radiation therapy for facial skin cancer. To effectively use 3-dimensional printing, the topography of the patient must first be acquired. We evaluated a low-cost, structured-light, 3-dimensional, optical scanner to assess the clinical viability of this technology.Methods and materialsFor ease of use, the scanner was mounted to a simple gantry that guided its motion and maintained an optimum distance between the scanner and the object. To characterize the spatial accuracy of the scanner, we used a geometric phantom and an anthropomorphic head phantom. The geometric phantom was machined from plastic and included hemispherical and tetrahedral protrusions that were roughly the dimensions of an average forehead and nose, respectively. Polygon meshes acquired by the optical scanner were compared with meshes generated from high-resolution computed tomography images. Most optical scans contained minor artifacts. Using an algorithm that calculated the distances between the 2 meshes, we found that most of the optical scanner measurements agreed with those from the computed tomography scanner within approximately 1 mm for the geometric phantom and approximately 2 mm for the head phantom. We used this optical scanner along with 3-dimensional printer technology to create custom lead shields for 10 patients receiving orthovoltage treatments of nonmelanoma skin cancers of the face. Patient, tumor, and treatment data were documented.ResultsLead shields created using this approach were accurate, fitting the contours of each patient's face. This process added to patient convenience and addressed potential claustrophobia and medical inability to lie supine.ConclusionsThe scanner was found to be clinically acceptable, and we suggest that the use of an optical scanner and 3-dimensional printer technology become the new standard of care to generate lead shielding for orthovoltage radiation therapy of nonmelanoma facial skin cancer.
This paper investigates the feasibility and accuracy of using a computer vision algorithm and electronic portal images to track the motion of a tumour-like target from a breathing phantom. A multi-resolution optical flow algorithm that incorporates weighting based on the differences between frames was used to obtain a set of vectors corresponding to the motion between two frames. A global value representing the average motion was obtained by computing the average weighted mean from the set of vectors. The tracking accuracy of the optical flow algorithm as a function of the breathing rate and target visibility was investigated. Synthetic images with different contrast-to-noise ratios (CNR) were created, and motions were tracked. The accuracy of the proposed algorithm was compared against potentiometer measurements giving average position errors of 0.6 ± 0.2 mm, 0.2 ± 0.2 mm and 0.1 ± 0.1 mm with average velocity errors of 0.2 ± 0.2 mm s−1, 0.4 ± 0.3 mm s−1 and 0.6 ± 0.5 mm s−1 for 6, 12 and 16 breaths min–1 motions, respectively. The cumulative average position error reduces more rapidly with the greater number of breathing cycles present in higher breathing rates. As the CNR increases from 4.27 to 5.6, the average relative error approaches zero and the errors are less dependent on the velocity. When tracking a tumour on a patient's digitally reconstructed radiograph images, a high correlation was obtained between the dynamically weighted optical flow algorithm, a manual delineation process and a centroid tracking algorithm. While the accuracy of our approach is similar to that of other methods, the benefits are that it does not require manual delineation of the target and can therefore provide accurate real-time motion estimation during treatment.
Knowledge‐based planning (KBP) can be used to estimate dose–volume histograms (DVHs) of organs at risk (OAR) using models. The task of model creation, however, can result in estimates with differing accuracy; particularly when outlier plans are not properly addressed. This work used RapidPlan™ to create models for the prostate and head and neck intended for large‐scale distribution. Potential outlier plans were identified by means of regression analysis scatter plots, Cook's distance, coefficient of determination, and the chi‐squared test. Outlier plans were identified as falling into three categories: geometric, dosimetric, and over‐fitting outliers. The models were validated by comparing DVHs estimated by the model with those from a separate and independent set of clinical plans. The estimated DVHs were also used as optimization objectives during inverse planning. The analysis tools lead us to identify as many as 7 geometric, 8 dosimetric, and 20 over‐fitting outliers in the raw models. Geometric and over‐fitting outliers were removed while the dosimetric outliers were replaced after re‐planning. Model validation was done by comparing the DVHs at 50%, 85%, and 99% of the maximum dose for each OAR (denoted as V50, V85, and V99) and agreed within −2% to 4% for the three metrics for the final prostate model. In terms of the head and neck model, the estimated DVHs agreed from −2.0% to 5.1% at V50, 0.1% to 7.1% at V85, and 0.1% to 7.6% at V99. The process used to create these models improved the accuracy for the pharyngeal constrictor DVH estimation where one plan was originally over‐estimated by more than twice. In conclusion, our results demonstrate that KBP models should be carefully created since their accuracy could be negatively affected by outlier plans. Outlier plans can be addressed by removing them from the model and re‐planning.
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