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Purpose: Evaluation of three dimensional (3D) radiotherapy plans is difficult because it requires the review of vast amounts of data. Selecting the optimal plan from a set of competing plans involves making trade-offs among the doses delivered to the target volumes and normal tissues. The purpose of this study was to test an objective plan-evaluation model and evaluate its clinical usefulness in 3D treatment planning for nonsmall cell lung cancer., Methods and Materials: Twenty patients with inoperable nonsmall cell lung cancer treated with definitive radiotherapy were studied using full 3D techniques for treatment design and implementation. For each patient, the evaluator (the treating radiation oncologist) initially ranked three plans using room-view dose-surface displays and dose-volume histograms, and identified the issues that needed to be improved. The three plans were then ranked by the objective plan-evaluation model. A figure of merit (FOM) was computed for each plan by combining the numerical score (utility in decision-theoretic terms) for each clinical issue. The utility was computed from a probability of occurrence of the issue and a physician-specific weight indicating its clinical relevance. The FOM was used to rank the competing plans for a patient, and the utility was used to identify issues that needed to be improved. These were compared with the initial evaluations of the physician and discrepancies were analyzed. The issues identified in the best treatment plan were then used to attempt further manual optimization of this plan., Results: For the 20 patients (60 plans) in the study, the final plan ranking produced by the plan-evaluation model had an initial 73% agreement with the ranking provided by the evaluator. After discrepant cases were reviewed by the physician, the model was usually judged more objective or "correct." In most cases the model was also able to correctly identify the issues that needed improvement in each plan. Subsequent replanning confirmed that further manual plan optimization could be achieved in 17 patients., Conclusion: The objective plan-evaluation model was able to rank lung cancer radiotherapy plans from best to worst. It was useful in improving plans and may be useful to physicians in defining goals for patients based on the ability to effectively and safely treat their tumors.

Purpose: This article announces the availability of a convenient and useful software environment for the evaluation of three-dimensional (3D) radiotherapy treatment plans., Materials and Methods: Using standards such as American National Standards for Information Systems C and the X Window System allowed us to bring the computation and display of dose-volume histograms, dose statistics, tumor control probabilities, normal tissue complication probabilities, and a figure of merit together under one user interface. These plan evaluation tools are not stand alone, but must interact with a 3D radiation therapy planning system to obtain the required dose matrices and patient anatomical contours. Installation of the software involves a programmer who writes a software bridge between the radiation therapy planning system and the tools, thereby providing access to local data files. This design strategy confines portability issues to one area of the software., Results: Access to the other tools is through the Graphical Plan Evaluation Tool (GPET). GPET coordinates the use of each of the tools and provides graphical facilities for display of their results. Importantly, GPET assures that the displayed results of each tool have been computed with the same input specifications for all treatment plans being compared. For added convenience, the user can rearrange the resultant data to be reviewed in various ways on the video screen. The software design also allows incorporation of customized algorithms and input data for computing tumor control probability and normal tissue complication probabilities, since those currently available are controversial., Conclusion: The Graphical Plan Evaluation Tool unifies the simultaneous computation for several analytical tools and graphical display of their results. Within the constraints of the X Window System environment, this assemblage of software tools provides a portable, flexible, and convenient method for the quantitative evaluation of several radiotherapy treatment plans.

Purpose: Selecting the optimal radiation treatment plan from a set of competing plans involves making trade-offs among the doses delivered to the target volumes and normal tissues by the competing plans. Evaluation of 3-dimensional radiation treatment plans is difficult because it requires the review of vast amount of graphical and numerical data. We have developed an objective plan-ranking model based on the concepts of decision analysis., Methods and Materials: Our model ranks a set of tentative radiation treatment plans from best to worst. A figure of merit is computed for each plan based on probabilities of possible clinical complications such as non-eradication of the tumor and radiation induced damage to the nearby healthy normal tissues, and weights which indicate their clinical relevance. This figure of merit is used to rank the plans. Key issues addressed by the model include the incorporation of individual treatment preferences of the radiation oncologist and clinical features of the patient., Results: A methodology has been established for eliciting the treatment preferences of radiation oncologists. Results of this elicitation, and examples of several plan evaluations are presented. An interactive computer-based tool has been developed as one of a set of tools to assist in the evaluation of 3-dimensional radiation treatment plans., Conclusion: The paper presents a decision-analytic model incorporating radiation oncologists' treatment preferences and an interactive computer-based tool for objectively ranking competing radiation treatment plans. The tool can be used by radiation oncologists for the evaluation of competing plans, or as part of a system which tries to automatically generate optimal treatment plans using mathematical or symbolic techniques.