Microdosimetry Simulation for Radioembolization Dose Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for radioembolization procedures fail to accurately account for local dose variations due to random-sized gaps between particles, leading to unpredictable tumor response and treatment toxicity.
Innovation Solution
Systems and methods that determine the effective local radiation dose by calculating mean dose and particle density using a partition model, performing microdosimetry simulations to estimate dose heterogeneity, and adjusting the number and activity of particles to maximize tumor dose while minimizing normal tissue dose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (mean dose calculation) are used, then the treatment plan is simple to calculate, but the local dose distribution is inaccurate due to random gaps between particles
Solution Approach 1:
The patent segments the tumor volume into multiple smaller sub-volumes (e.g., 1 cm³ regions) to calculate local dose distributions. This segmentation allows the system to account for particle gap variations within each sub-volume, transforming the single mean dose calculation into multiple localized dose assessments that reflect actual radiation distribution patterns.
Solution Approach 2:
The patent applies local quality by calculating dose-specific parameters (mean dose, standard deviation, skewness, kurtosis) for each sub-volume individually rather than using a single global mean dose. This enables the system to capture spatial variations in dose distribution caused by random particle gaps, providing localized dose quality metrics that guide treatment optimization.
2Stability of the object's composition
If the number of particles is increased to reduce gaps, then the dose uniformity improves, but the treatment complexity and cost increase
Solution Approach 1:
The patent changes the parameter of particle number density by calculating optimal particle counts and activity levels that achieve desired dose distributions. The system uses statistical moments (mean, standard deviation, skewness, kurtosis) to model dose variations and determines the minimum number of particles required to achieve uniform dose distribution, avoiding unnecessary increase in particle count while maintaining dose homogeneity.
3Reliability
If the activity per particle is increased to achieve therapeutic dose, then the tumor treatment effectiveness improves, but the normal tissue toxicity increases
Solution Approach 1:
The patent applies local quality by calculating and optimizing activity levels for different sub-volumes based on their specific dose distributions. The system determines optimal activity per particle for each region, allowing higher activity in tumor regions with lower particle density and adjusted activity in regions with higher particle density, thereby achieving therapeutic doses in tumors while minimizing normal tissue toxicity.
Solution Approach 2:
The patent implements feedback by using measured or predicted dose distributions (characterized by statistical moments) to iteratively optimize the number of particles and activity levels. The system compares calculated dose distributions against treatment goals and adjusts particle delivery parameters accordingly, creating a closed-loop optimization process that maximizes tumor efficacy while minimizing normal tissue damage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables a therapeutic tumor dose while reducing injury to normal tissue by optimizing particle distribution and activity, providing a more precise and effective treatment plan.
Implementation Method 1
performing microdosimetry simulations to estimate dose heterogeneity within the tumor and/or normal tissue
Implementation Method 2
In an embodiment, the microdosimetry is a Monte Carlo simulation
Implementation Method 3
determining a mean dose of particles and a particle density in both the tumor and normal tissue
Data Source
AI summary
Systems and methods are configured to determine an effective local dose for a treatment procedure. The systems and methods are configured to determine a mean dose of a particle and a particle density at least a portion of tumor and at least a portion of normal tissue, perform a microdosimetry simulation or calculation, using the mean dose and the particle density, and determine the effective local dose, based on the microdosimetry simulation or calculation. A treatment plan can be arrived at pursuant to such systems and methods.