TTField Electrode Placement via MRI Conductivity Mapping
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Solution Overview
Problem
Current methods for optimizing Tumor Treating Fields (TTFields) array placement on the scalp are slow and provide low-resolution images, requiring time-consuming tissue segmentation and relying on diffusion-weighted imaging or diffusion tensor imaging for conductivity measurements.
Innovation Solution
A method using two MRI images with different repetition times to create a 3D model of AC electrical conductivity or resistivity, allowing for optimized electrode placement without segmentation, by calculating the intensity ratio of the images and mapping it into a 3D model, which is more computationally efficient and provides higher resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If diffusion weighted imaging or diffusion tensor imaging is used for conductivity measurements, then electrical conductivity measurements can be obtained in an anatomic volume, but the process is slow and provides images with relatively low number of slices
Solution Approach 1:
The patent replaces the mechanical/diffusion-based imaging process (DWI/DTI) with a magnetic resonance-based approach using T1-weighted images with different repetition times. This substitution enables faster image acquisition while maintaining the capability to derive conductivity measurements through signal intensity ratio calculations.
Solution Approach 2:
The invention changes the MRI acquisition parameters by using T1-weighted images with different repetition times (TR) instead of diffusion-weighted sequences. By varying the TR parameter and calculating the signal intensity ratio between images acquired at different TR values, the method derives conductivity information faster than traditional DWI/DTI approaches.
2Measurement precision
If conventional tissue segmentation approaches are used, then anatomical volume can be analyzed, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent extracts only the necessary information (signal intensity ratios from T1-weighted images) required for conductivity estimation, eliminating the need for complete tissue segmentation. This extraction approach focuses on the specific parameter needed (conductivity) without requiring full anatomical decomposition.
Solution Approach 2:
The method creates a simplified representation of tissue properties through signal intensity ratios that directly correlate with conductivity, bypassing the need for detailed anatomical copies or segmentations. The ratio-based approach creates an efficient proxy for tissue conductivity without replicating complex anatomical structures.
3Measurement precision
If high-resolution conductivity mapping is implemented, then treatment optimization accuracy improves, but computational complexity increases
Solution Approach 1:
The patent replaces complex computational segmentation and classification algorithms with a simpler signal intensity ratio calculation approach. This substitution maintains high-resolution conductivity mapping capability while reducing computational complexity through direct mathematical relationships between MRI signal ratios and conductivity values.
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
This approach enables faster and more accurate simulation of TTFields distribution in the brain, improving treatment efficacy by optimizing electric field intensity in target tissues without the need for labor-intensive segmentation, with average errors in conductivity estimates adequate for TTFields simulations.
Implementation Method 1
obtaining first and second MRI images of the anatomic volume, with associated first and second repetition times, respectively
Implementation Method 2
creating a 3D model of AC electrical conductivity or resistivity of an anatomic volume at a given frequency below 1 MHz
Data Source
AI summary
A 3D model of AC electrical conductivity (at a given frequency) of an anatomic volume can be created by obtaining two MRI images of the anatomic volume, where the two images have different repetition times. Then, for each voxel in the anatomic volume, a ratio IR of the intensity of the corresponding voxels in the two MRI images is calculated. This calculated IR is then mapped into a corresponding voxel of a 3D model of AC electrical conductivity at the given frequency. The given frequency is below 1 MHz (e.g., 200 kHz). In some embodiments, the 3D model of AC electrical conductivity at the given frequency is used to determine the positions for the electrodes in TTFields (Tumor Treating Fields) treatment.