ARMA Model for Respiratory Tissue Tracking in HIFU Therapy
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Solution Overview
Problem
Current methods for thermal treatment of tissues undergoing displacement during a respiratory cycle, such as thermal ablation, face inefficiencies due to the need for frequent MRI tracking and harmonic motion models that lack predictive power for elastic deformation and changing elastic properties of tissues.
Innovation Solution
An ARMA-based model is created through deformable registration of salient tissue features tracked over multiple respiratory cycles, allowing for predictive targeting of thermal energy without continuous MRI tracking, enabling uninterrupted thermal energy delivery and model validation during treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequent MRI tracking is performed to monitor tissue location during thermal treatment, then targeting accuracy is improved, but treatment time is significantly extended
Solution Approach 1:
The system performs preliminary MRI tracking over multiple respiratory cycles before treatment to build a predictive model of tissue motion. This pre-acquired data is then used to predict tissue location throughout the treatment without requiring continuous tracking, thus maintaining accuracy while reducing time loss.
Solution Approach 2:
The system uses acquired MRI data to continuously update and refine the predictive model of tissue motion during treatment. This feedback mechanism allows the system to adapt to actual tissue behavior while minimizing the frequency of tracking acquisitions, balancing accuracy with treatment efficiency.
2Manufacturing precision
If thermal energy application is gated to specific points in the respiratory cycle to ensure accurate targeting, then treatment precision is improved, but productivity is reduced
Solution Approach 1:
The system transitions from static, cycle-gated thermal application to dynamic, continuous thermal delivery. The predictive model dynamically adjusts the thermal energy targeting in real-time based on predicted tissue location, allowing uninterrupted treatment while maintaining precision.
Solution Approach 2:
The system enables continuous thermal energy application throughout the entire treatment period without periodic interruptions for tracking or gating. The predictive model ensures accurate targeting is maintained continuously, maximizing treatment productivity while preserving precision.
3Device complexity
If harmonic motion models are used to predict tissue location, then model simplicity is maintained, but predictive accuracy deteriorates for tissues with elastic deformation
Solution Approach 1:
The system changes the fundamental parameters of the motion model from simple harmonic oscillation to a data-driven predictive model based on actual MRI-tracked tissue behavior. This allows the model to capture complex elastic deformations and changing tissue properties while maintaining computational efficiency through the use of established predictive algorithms.
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 significantly reduces treatment time by allowing continuous thermal energy application and adaptive adjustment to changes in tissue elasticity, ensuring accurate targeting of diseased tissues while minimizing healthy tissue damage.
Implementation Method 1
creating an Autoregressive Moving Average (ARMA) based model of the tissue targeted for thermal therapy and using the model to guide the application of thermal energy over multiple respiratory cycles
Implementation Method 2
The thermal treatment, particularly the thermal ablation, of lesions, tumors or other diseased tissue has been practiced for some time
Implementation Method 3
high intensity focused ultrasound (HIFU) has been used to reach internal tissue
Implementation Method 4
The model is conveniently created by tracking the spatial position of salient features representative of different portions of the tissue of interest with MRI over multiple respiratory cycles
Implementation Method 5
The model is conveniently created by tracking the spatial position of salient features representative of different portions of the tissue of interest with MRI over multiple respiratory cycles for a number of subjects and subjecting the data so collected to deformable/elastic registration and ARMA treatment
Data Source
AI summary
The present application discloses a technique for targeting therapeutic thermal energy to human tissue that is subject to displacement during a respiratory cycle using ARMA modeling. It discloses using an ARMA treatment of MRI tracking data of salient features of the tissue of interest to predict the spacial position of the portion of the tissue to be treated and using this prediction to guide the application of the thermal energy. It also discloses that this technique is particularly useful when the tissue of interest undergoes elastic deformation in a respiratory cycle and high energy focused ultrasound (HIFU) is used to ablate diseased tissue such as a cancerous tumor.