Multi-Leaf Collimator Leaf-Sequence Plan Optimization
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Solution Overview
Problem
Optimizing radiation-treatment leaf-sequence plans is challenging due to physical limitations of multi-leaf collimators, which can render planned modifications impossible to achieve, leading to inefficiencies in tracking target movement and maintaining effective treatment plans.
Innovation Solution
Determining physical movement limitations of multi-leaf collimators and target movement, then constraining planned leaf positions based on these factors and adjacent leaf positions to ensure physically plausible modifications that adapt to target changes during treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic modifications are planned to adapt to target movement during treatment, then adaptability is improved, but physical limitations of multi-leaf collimators may render modifications impossible to achieve
Solution Approach 1:
The system performs preliminary determination of physical movement limitations of the multi-leaf collimator before finalizing the treatment plan. By预先 establishing the maximum movement capabilities and time constraints of each leaf, the optimization process can proactively design achievable leaf sequences that adapt to target movement while respecting physical limitations, rather than attempting modifications after the fact.
Solution Approach 2:
The system introduces dynamic constraints into the leaf-sequence optimization process by incorporating real-time target movement information and collimator physical limitations. The optimization algorithm dynamically adjusts leaf position plans based on predicted target movement while ensuring that requested positions remain within the achievable ranges determined by the collimator's physical capabilities and treatment timing.
2Reliability
If leaf positions are modified to track target movement, then treatment effectiveness is improved, but treatment time may increase due to additional adjustments
Solution Approach 1:
The system determines achievable leaf positions and movement constraints in advance, before the actual treatment delivery. By pre-calculating the maximum movement capabilities and time requirements for each leaf, the optimization process can efficiently generate leaf sequences that achieve target tracking within the predetermined time budget, avoiding time-consuming adjustments during treatment.
Solution Approach 2:
The system optimizes multiple parameters simultaneously including leaf positions, movement speeds, and timing sequences to achieve effective target tracking within acceptable treatment time. By adjusting these parameters in the optimization process rather than during actual treatment, the system maintains treatment effectiveness while minimizing time loss.
3Adaptability or versatility
If complex modifications are made to accommodate target position changes, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system establishes comprehensive physical limitation data for each leaf (maximum movement distance, speed, acceleration) before optimization. This preliminary characterization of device capabilities allows the optimization algorithm to work within well-defined constraints, simplifying the planning process by eliminating the need for complex real-time calculations and reducing the computational burden during treatment planning.
Data Source
AI summary
Determine first information regarding physical-movement limitations pertaining to at least one multi-leaf collimator and also determine second information regarding movement of the treatment target with respect to the given patient. Then, while optimizing a radiation-treatment leaf-sequence plan, constrain individually-planned leaf positions as a function, at least in part, of the first information, the second information, and planned positions of adjacent leaves. By one approach, the first information can comprise information regarding a speed (such as a maximum speed) at which individual leaves of the multi-leaf collimator are able to move during a treatment session. By one approach, the second information can comprise information regarding a distance (such as a maximum distance) that one or more parts of the treatment target may possibly move as compared to a presumed position used during the optimizing of the radiation-treatment leaf-sequence plan.