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.
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.