MR Thermometry Pixel Masking for Thermal Therapy Control
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Solution Overview
Problem
Existing thermal therapy systems face challenges in accurately measuring temperature during MRI-guided thermal therapy due to errors and uncertainties, leading to potential overheating, incomplete treatments, and tissue damage.
Innovation Solution
A method and system for filtering erroneous pixels in MR thermometry by using a thermal therapy applicator to deliver thermal doses, analyzing temperature data, and applying dynamic pixel masking to ignore noisy and unreliable temperature measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temperature measurements from MRI are used for feedback control in thermal therapy, then real-time monitoring capability is improved, but measurement accuracy deteriorates due to errors and uncertainties
Solution Approach 1:
The patent segments the temperature measurement data by dividing the imaging space into multiple regions (first region with higher signal-to-noise ratio and second region with lower signal-to-noise ratio). Different filtering strategies are applied to different regions based on their characteristics, allowing accurate measurement in the first region while handling errors in the second region through appropriate thresholding and validation
Solution Approach 2:
The patent changes the parameters used for temperature measurement by using multiple different measurements (e.g., different MRI sequences or parameters) to calculate temperature. By comparing and validating multiple parameter-based measurements, the system can identify and filter erroneous readings, improving overall measurement accuracy and reliability
2Object-affected harmful factors
If strict temperature monitoring is applied to prevent overheating, then patient safety is improved, but treatment duration increases due to frequent pauses for cooling
Solution Approach 1:
The patent applies preliminary filtering and validation to temperature measurements before they trigger safety responses. By pre-identifying and correcting erroneous measurements through region-based analysis and cross-validation, the system prevents false alarms that would otherwise cause unnecessary treatment pauses, thereby reducing total treatment time while maintaining safety
Solution Approach 2:
The patent implements a refined feedback mechanism that uses validated temperature measurements from the first region with higher confidence. This selective feedback approach ensures that only reliable temperature data triggers safety responses, reducing unnecessary interruptions while maintaining effective overheating prevention through continuous monitoring of critical regions
3Measurement precision
If comprehensive temperature validation is performed on all pixels, then measurement accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent reduces processing complexity by segmenting the data validation process into region-specific procedures. The first region requires comprehensive validation with multiple measurements, while the second region uses simplified validation appropriate for its lower signal-to-noise characteristics. This segmented approach maintains high measurement accuracy where needed while reducing overall computational burden
Solution Approach 2:
The patent applies local quality by using different validation strictness levels in different spatial regions. High-precision validation is applied locally in the first region where measurements are more reliable, while simplified validation is applied in the second region. This local differentiation maintains measurement accuracy in critical areas without requiring equally complex processing across the entire dataset
Data Source
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AI summary
During the delivery of thermal therapy, the measured temperature at each pixel in a cross-sectional temperature slice of a multi-pixel thermal image is compared to a maximum temperature limit. When the measured temperature of a pixel is higher than the maximum temperature limit for a predetermined number of consecutive cross-sectional temperature slices, the pixel is masked if the absolute value of the average difference between the measured temperature at the pixel and the measured temperatures at the pixel's neighbors is greater than a maximum temperature variation. The measured temperature of the masked pixel is ignored in subsequent cross-sectional temperature slices until the delivery of thermal therapy is complete.