Purpose: Present a general cost‐effective robust clinical process that can analytically evaluate and correct patient setup error for head and neck radiotherapy by comparing orthogonal megavoltage portal images (PI) with corresponding digitally reconstructed radiographs (DRR). Method and Materials: Adobe Photoshop CS2 is used to interactively segment images. Scripts are available to automate many steps, including image enhancement. MATLAB is a software package with many features for rapid matrix computations and image analysis. The closest point distance (CPD) for each PI point to a DRR point forms a set of homologous points. The translation T that aligns the PI to the DRR is equal to the difference in centers of mass. The original PI points are transformed and the process repeated with an Iterative Closest Point (ICP) algorithm. Analytical results are displayed as a cumulative histogram of the percentage of points exceeding CPD. The total area Σ under the histogram is a general error metric. A color coded image is provided to display the anatomical location of the PI points with respect to the DRR and their CPD. Results: The ICP algorithm always converged. The integral Σ was consistently lower for the analytical IGRT, with a mean reduction of 16%. The process was tested retrospectively by three users. Typical user dependence was below 0.5 mm. The time for segmentation of two images and computations was under ten minutes. The process has been integrated with a Visual Basic Toolbox that guides the user through the required all the steps from importing the daily Portal Image, segmentation, computing the translation, and printing a standard report. Conclusion: Inexpensive commercial software has been shown to be useful for on line analytical IGRT. The process developed is robust, consistently better then IGRT, provides documented error metrics, and can be customized by the user for individual applications.
Individual plan quality indices were combined into a single figure of merit for various beam parameters that can be used to analytically select the optimum dosimetric plan.
Purpose: Present a metric to compare the outer rectal wall surface cumulative daily treatment dose with the original plan. Materials and Methods: The rectum outer surface was contoured for 28 fractions of a patient undergoing prostate tomotherapy without bowel preparation. The rectal variations could be divided into three ranges corresponding to a rectal filling of “empty”, “half” and “full” with approximately 61%, 21% and 18% of the data in each respective region. We use points on the outer surface of the rectum to calculate a Dose Surface Histogram (DSH). The set of points on the planning surface is the reference for all daily treatments. Doses on the daily contour are mapped onto the reference contour. Every point on the planning contour has a homologous point on the daily contour. Rapid calculations are performed using an in‐house MATLAB algorithm. For each treatment fraction, the dose D(i) to point i on the planning contour is equal to the dose D(j) where j is the previously determined corresponding point on the daily contour. The cumulative dose to point i is the sum of all the daily D(j). Results: A DSH was calculated for the plan and a representative daily MVCT slice. The cumulative DSH was compared to the nominal “average” DSH computed by simply averaging the plan and daily DSHs. There are significant differences above 80% of the prescribed dose. DSHs for a representative contour in each of the empty, half, and full rectum regions indicated 5% difference between the cumulative and planned rectum for doses below 70% and variations of 10 to 20% at higher doses. Conclusions: Cumulative DSHs accurately indicate the dosimetric effect of daily variations in rectal filling. A general technique to compute cumulative DSHs has been developed as an efficient metric to determine if adaptive planning is required.
Purpose:It has been argued that a 3D‐conformal technique (3DCRT) is suitable for SBRT due to its simplicity for non‐coplanar planning and delivery. It has also been hypothesized that a high dose delivered in a short time can enhance indirect cell death due to vascular damage as well as limiting intrafraction motion. Flattening Filter Free (FFF) photon beams are ideal for high dose rate treatment but their conical profiles are not ideal for 3DCRT. The purpose of our work is to present a method to efficiently segment an FFF beam for standard 3DCRT planning.Methods:A 10×10 cm Varian True Beam 6X FFF beam profile was analyzed using segmentation theory to determine the optimum segmentation intensity required to create an 8 cm uniform dose profile. Two segments were automatically created in sequence with a Varian Eclipse treatment planning system by converting isodoses corresponding to the calculated segmentation intensity to contours and applying the “fit and shield” tool. All segments were then added to the FFF beam to create a single merged field. Field blocking can be incorporated but was not used for clarity.Results:Calculation of the segmentation intensity using an algorithm originally proposed by Xia and Verhey indicated that each segment should extend to the 92% isodose. The original FFF beam with 100% at the isocenter at a depth of 10 cm was reduced to 80% at 4cm from the isocenter; the segmented beam had +/−2.5 % uniformity up to 4.4cm from the isocenter. An additional benefit of our method is a 50% decrease in the 80%‐20% penumbra of 0.6cm compared to 1.2cm in the original FFF beam.Conclusion:Creation of two optimum segments can flatten a FFF beam and also reduce its penumbra for clinical 3DCRT SBRT treatment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.