Electric Field Distribution Approximation for Faster TTFields Planning
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Solution Overview
Problem
Current methods for optimizing the placement of transducer arrays for Tumor Treating Fields (TTFields) therapy are time-consuming and inefficient, relying on finite element methods that require hours of computation, limiting the evaluation of array locations and potentially resulting in suboptimal treatment plans.
Innovation Solution
A novel method utilizing random forest regression and machine learning techniques for fast estimation of TTFields intensity, incorporating key parameters to optimize array placement on a patient's scalp, reducing computation time to minutes while improving the accuracy of electric field distribution estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If finite element methods are used to estimate TTFields intensity distribution, then measurement precision is improved, but computation time increases significantly (requiring 3-4 hours)
Solution Approach 1:
The patent creates a digital twin or virtual model of the patient's head anatomy using MRI scans, allowing repeated simulations without physical experimentation. This virtual copy enables fast computation by pre-calculating field distributions for various transducer positions, avoiding time-consuming real-time finite element analyses during treatment optimization.
Solution Approach 2:
The system performs preliminary computations by pre-calculating electric field distributions for multiple transducer array positions and storing them in a database. During treatment planning, these pre-computed results are retrieved and interpolated to determine optimal positions, eliminating the need for time-consuming real-time simulations.
2Reliability
If multiple transducer array locations are evaluated during optimization, then treatment efficacy is improved, but computation time increases limiting the number of positions that can be assessed
Solution Approach 1:
The system pre-computes and stores electric field distributions for numerous transducer array positions in advance, creating a lookup table that can be quickly queried during optimization. This allows evaluation of many positions without real-time computation, significantly increasing the number of positions that can be assessed within practical time limits.
Solution Approach 2:
The patent introduces an intermediary database that stores pre-computed field distribution data. This database acts as a mediator between the optimization algorithm and the complex physics calculations, allowing rapid retrieval of field information for different positions without re-running time-consuming finite element simulations.
3Manufacturing precision
If accurate electric field distribution calculations are performed, then treatment planning accuracy is improved, but the complexity and time required for calculations increases
Solution Approach 1:
The patent uses a simplified virtual model of the patient's head that copies essential anatomical features and tissue properties needed for accurate field estimation. This streamlined digital representation maintains treatment planning accuracy while reducing computational complexity compared to full finite element models.
Solution Approach 2:
The system changes the approach from solving complex partial differential equations in real-time to using pre-computed parameter tables and interpolation. By transforming the problem from continuous physics simulation to discrete data lookup and interpolation, the system maintains accuracy while dramatically reducing computational complexity.
Data Source
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Figure 3A~3B
AI summary
Methods, systems, and apparatuses are described for fast approximation of electric field distribution.