Radiotherapy Field Delivery Optimization for Time-Dose Balance
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Solution Overview
Problem
Existing radiotherapy treatment planning systems struggle to optimize treatment time while maintaining clinically acceptable dosimetry, particularly in spot scanning techniques, leading to suboptimal dose redistribution and inefficient field delivery.
Innovation Solution
A computer-implemented method and system that adjusts beam currents and spot distribution based on machine-specific parameters to optimize treatment time and dosimetry, using a graphical user interface to balance delivery time and dosimetric objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If spot scanning treatment planning optimizes for dose distribution by removing spots below a certain monitor unit threshold, then the dose to surrounding healthy tissue is minimized, but the treatment time is extended and field delivery efficiency is reduced
Solution Approach 1:
The patent changes the optimization parameter from purely dosimetric (monitor unit threshold) to include a composite cost function that incorporates both dosimetric quality and delivery time components. This allows the system to evaluate spots based on both their dosimetric contribution and their impact on treatment time, enabling optimization of both objectives simultaneously rather than sequentially
Solution Approach 2:
The patent introduces dynamic weighting factors that allow the relative importance of dosimetric objectives versus delivery time objectives to be adjusted during optimization. The cost function dynamically balances these competing objectives based on user-defined weights, enabling flexible trade-offs between treatment time and dosimetric quality without requiring separate optimization passes
2Device complexity
If existing treatment planning solutions remove spots below a monitor unit threshold to simplify delivery, then the number of spots is reduced, but the dose redistribution is not optimal for either plan quality or field delivery time
Solution Approach 1:
The patent transforms the spot selection criterion from a simple monitor unit threshold to a composite cost metric that includes both dosimetric quality measures and delivery time considerations. This parameter change enables the system to identify spots for removal based on their overall contribution to both plan quality and delivery efficiency, rather than solely on dose magnitude
Solution Approach 2:
The patent implements a feedback mechanism where the cost function evaluates the impact of spot removal on both dosimetric objectives and delivery time objectives. The optimization process iteratively adjusts spot selection based on this feedback, ensuring that removed spots do not significantly degrade plan quality while achieving delivery time reductions
3Object-affected harmful factors
If treatment planning prioritizes minimizing dose to surrounding tissue, then normal tissue toxicities are reduced, but the overall treatment time cannot be reduced to accommodate breath-hold techniques
Solution Approach 1:
The patent introduces dynamic weighting factors that allow the relative importance of dosimetric objectives versus delivery time objectives to be adjusted during optimization. The cost function dynamically balances these competing objectives based on user-defined weights, enabling flexible trade-offs between treatment time and dosimetric quality without requiring separate optimization passes
Solution Approach 2:
The patent changes the optimization parameter from purely dosimetric (monitor unit threshold) to include a composite cost function that incorporates both dosimetric quality and delivery time components. This allows the system to evaluate spots based on both their dosimetric contribution and their impact on treatment time, enabling optimization of both objectives simultaneously rather than sequentially
Data Source
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AI summary
Treatment fields can be produced as part of a treatment plan that achieves a desired balance between field delivery time and dose based on machine parameters and knowledge, such as machine-specific beam production, transport and scanning logic, and/or a maximum treatment time value. The treatment parameters can be adjusted using a graphical user interface so that treatment time or dosimetry is prioritized. As a result, the overall treatment time is reduced, and hence treatment quality and patient experience are improved.