Patient-Specific Radiation Therapy Margin Calculation
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Solution Overview
Problem
Current radiation therapy techniques, such as IMRT and IGRT, rely on generic margin models that do not account for patient-specific prostate motion, leading to inaccuracies and increased exposure of normal tissues, which can result in side effects and secondary cancers.
Innovation Solution
A system and method for determining individualized treatment planning margins based on patient-specific patterns of motion, using motion data from markers to predict target motion along x, y, and z axes, allowing for more precise treatment planning and reduced normal tissue dose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If generic margin models are used to address uncertainties in radiotherapy, then treatment planning can be simplified, but treatment precision deteriorates because patient-specific motion patterns are not accounted for
Solution Approach 1:
The patent applies local quality by transitioning from uniform generic margins to patient-specific, direction-dependent margins. The system calculates separate margin values for different spatial directions (anterior-posterior, lateral, superior-inferior) based on individual patient motion characteristics, allowing each region to have optimized margin parameters that reflect actual motion patterns in that specific direction.
Solution Approach 2:
The patent changes the parameter of margin values from fixed generic ranges to dynamic patient-specific values. By processing motion data and calculating direction-dependent margins, the system adjusts margin parameters individually for each patient and each spatial direction, transforming the margin from a static parameter to a personalized, data-driven value that reflects individual motion characteristics.
2Reliability
If larger margins are used to account for prostate motion, then treatment reliability improves, but normal tissue exposure increases leading to more side effects
Solution Approach 1:
The system applies local quality by determining direction-dependent margins that reflect actual motion patterns in each spatial direction. Instead of using uniform large margins to cover all possible motions, the system calculates specific margin values for anterior-posterior, lateral, and superior-inferior directions based on measured motion data, applying only the necessary margin protection in each direction where motion occurs.
Solution Approach 2:
The patent changes the margin parameter from conservative fixed values to data-driven patient-specific values. By processing actual motion data and calculating margins based on measured displacement and motion patterns, the system determines the minimum sufficient margin for each patient and direction, eliminating excessive margin that would unnecessarily increase normal tissue exposure while maintaining adequate reliability.
3Device complexity
If uniform margins are applied across all patients and directions, then treatment planning is simplified, but measurement precision deteriorates because individual motion patterns are not captured
Solution Approach 1:
The patent applies segmentation by dividing the treatment planning process into distinct components: motion data processing, direction-dependent margin calculation, and treatment plan generation. The motion data is segmented into different spatial directions (anterior-posterior, lateral, superior-inferior), and separate margin values are calculated for each direction based on motion characteristics specific to that direction, allowing precise capture of individual motion patterns while maintaining organized planning procedures.
Solution Approach 2:
The system changes the margin parameter from uniform fixed values to patient-specific direction-dependent values. By processing motion data and calculating margins individually for each patient and each spatial direction, the system captures individual motion patterns with high precision while organizing the complexity through systematic data processing and automated calculation procedures.
Data Source
AI summary
Methods, systems and computer-readable storage media relate to determining individualized treatment planning margins. The methods may include processing motion data of a target obtained from at least one marker for one or more periods. Each period may include a plurality of time intervals. The processing may include processing the motion data to determine an isocenter for each time interval along at least one of the axes of motion. The axes can include the x axis, the y axis, and/or the z axis. The method may include determining motion prediction data for each of the at least one of the axes; and determining treatment planning margins for each of the at least one of the axes based on the motion prediction data. The individualized treatment margins can be smaller and more optimal because the treatment margins can incorporate patient specific patterns of motion of a target (e.g., an organ).