Multi-Criteria Optimization for Radiotherapy Technology Selection
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Solution Overview
Problem
Current radiation therapy planning methods require separate planning for each technology, leading to inefficiencies and increased waiting times due to limited availability of proton systems, which are costly and complex, making it challenging to treat multiple patients effectively and efficiently.
Innovation Solution
A method for interactive multi-criteria optimization using a graphical user interface that allows navigation across multiple technologies, including proton and photon therapies, by displaying Pareto frontiers and fuzziness intervals, enabling the selection of equivalent treatment options and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If separate planning is performed for each radiation therapy technology, then the quality of individual treatment plans can be optimized, but the overall treatment efficiency decreases and waiting times increase
Solution Approach 1:
The patent combines multiple separate technology-specific planning processes into a single integrated multi-criteria optimization framework. Instead of performing separate planning for protons, photons per rotation, and photons per IMRT, the system unifies these approaches under one optimization algorithm that simultaneously evaluates all technologies against multiple clinical criteria, thereby maintaining plan quality while improving overall treatment efficiency.
Solution Approach 2:
The optimization system is designed to be universal across different radiation therapy technologies. A single multi-criteria optimization algorithm can handle various treatment modalities (protons, photons per rotation, photons per IMRT) and different device configurations, making the planning process adaptable and efficient without requiring separate specialized planning procedures for each technology.
2Reliability
If proton therapy is used for all patients, then the therapeutic benefit is maximized, but the waiting times increase due to limited proton system availability
Solution Approach 1:
The system dynamically selects the appropriate radiation therapy technology for each patient based on real-time evaluation of multiple criteria including therapeutic benefit, device availability, and waiting times. Rather than statically assigning all patients to proton therapy, the optimization algorithm adaptively determines whether proton or photon therapy is more appropriate for each individual case, thereby reducing waiting times while maintaining therapeutic quality.
Solution Approach 2:
The optimization framework changes the decision parameter from a fixed technology assignment to a flexible, criterion-based selection. By evaluating multiple parameters (therapeutic benefit, device availability, waiting time) and adjusting the technology choice accordingly, the system can switch between proton and photon therapies based on current conditions, reducing patient waiting times while preserving therapeutic effectiveness.
3Productivity
If multiple radiation devices are utilized for overall planning, then more patients can be treated simultaneously, but the scheduling complexity increases
Solution Approach 1:
The patent merges multiple device-specific scheduling problems into a unified multi-criteria optimization framework. Instead of separately managing schedules for proton devices, photon per rotation devices, and photon IMRT devices, the system integrates all device constraints and availability into a single optimization process that simultaneously determines both technology selection and scheduling, thereby increasing patient throughput while managing complexity through unification.
4Reliability
If proton systems are prioritized for urgent cases, then treatment quality is improved, but other patients experience longer waiting times
Solution Approach 1:
The optimization system changes from a priority-based static allocation to a multi-parameter dynamic optimization. By incorporating patient urgency, device availability, and waiting times as simultaneous optimization criteria rather than fixed priorities, the system can automatically balance resource allocation across different patient groups, ensuring urgent cases receive appropriate care while minimizing waiting times for non-urgent patients through efficient use of alternative photon therapies.
Data Source
AI summary
The aim of the invention is to allow patients to be individually provided with good therapy, whereby the quality of the therapy also includes minimizing the waiting time of each patient (under “time to treatment”). Proposed is a method for designing or fashioning a therapy as a treatment plan, before treatment, and with interactive navigation on a display device (10). Multiple technologies (A, B, . . . Z) of radiation devices (100, 200, 300) are available for selection, including at least one technology (A) with a radiation device (100) for emitting protons and at least one technology (B) with a radiation device (200) for emitting photons. After designing or fashioning, for a person (P) who is to be treated with therapy that can be provided by the radiation device (100, 200, 300), the designed or fashioned plan defines a plurality of technical settings that are adjusted on the radiation device(s) of the selected technology/technologies. For at least some of the technologies (A, B, . . . Z), one Pareto frontier each (101, 201, 301) is shown as a patch in an interactive patch area on the display device (10). An operating area on the display device (10) shows a number of operating aids (21, 22, . . . ), each of which represents a criterion (c1, c2, . . . ) that is improved when a selector (21a, 22a, . . . ) of the respective operating aid is moved or operated in one direction or worsened when it is moved or operated in the opposite direction. A fuzziness interval (30, 31, 32) is defined for a target criterion (c1, c2, . . . ), which is also displayed accordingly in the interactive patch area and covers at least two Pareto frontiers (201, 301) for at least two technologies (A, B). An input from the planner interactively conveys the equivalence of two technologies to the same planner. The two technologies shown (201, 301) have the same value (c11) for the same target criterion (c1) for the respective patch.