Automated Imaging Plan Generation for Radiation Therapy
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Solution Overview
Problem
The current methods for selecting imaging parameters and units in particle and radiation therapy are labor-intensive and prone to errors, relying solely on medical staff and lacking automation, which hampers efficient patient throughput and treatment planning.
Innovation Solution
An automated method and device using an evaluation module to determine imaging unit parameters and settings based on stored functional relationships and input data, including patient and tumor characteristics, to create an optimized imaging plan, which can be updated continuously with new data for improved accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated planning is implemented, then patient throughput is increased and human error is reduced, but device complexity increases
Solution Approach 1:
The evaluation module automatically determines imaging parameters and unit selections based on stored functional relationships and input data, enabling the system to plan treatments independently without requiring manual intervention from medical staff for each parameter selection
Solution Approach 2:
Functional relationships and imaging parameters are pre-stored in the evaluation module before treatment planning, allowing the system to retrieve and apply appropriate parameters automatically during the planning process without requiring real-time manual configuration
2Measurement precision
If manual selection of imaging parameters is used, then device complexity is kept low, but treatment planning time increases and accuracy decreases
Solution Approach 1:
The manual mechanical process of selecting imaging parameters is replaced with an automated electronic evaluation module that processes input data and determines parameters based on stored functional relationships, significantly reducing planning time while maintaining or improving accuracy
Solution Approach 2:
The system uses stored functional relationships that are updated based on experience and results, creating a feedback loop where the evaluation module continuously improves its parameter selection accuracy by learning from past treatment outcomes and imaging results
Data Source
AI summary
A device for planning an irradiation is provided. The device includes an evaluation module with an input for receiving input data, a memory and an output for outputting determined output data. The evaluation module is designed for using the input data that includes the type and number of the imaging units present, variables characterizing the tumor and/or variables characterizing the patient, in order to determine the output data that includes the type of the imaging unit, the frequency of use of the imaging unit and/or the parameters for setting the imaging unit to be used in the form of an imaging plan with the aid of a functional relationship, which is based on experience, stored in the memory.