Patient-Specific MRI Nerve Stimulation Thresholds
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Solution Overview
Problem
Current magnetic resonance imaging (MRI) systems face challenges in achieving optimal image quality without causing peripheral nerve stimulation, as conventional methods do not accurately account for individual patient variations and position-dependent stimulation, leading to unnecessary restriction of gradient amplitudes.
Innovation Solution
A method for determining peripheral nerve stimulation during MRI by calculating model-based candidate stimulations based on patient-specific parameters, such as muscle and fat percentage, and adjusting gradient strength to minimize nerve stimulation while maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If gradient amplitudes are limited by a monitoring device to avoid peripheral nerve stimulation, then patient comfort is improved, but image quality deteriorates due to restricted gradient performance
Solution Approach 1:
The patent changes the parameter used for stimulation assessment from a generic statistical model to patient-specific parameters including body constitution (fat and muscle distribution), anatomical position, and nerve susceptibility. This allows customization of gradient amplitude limits for each patient, preventing unnecessary restrictions while avoiding stimulation.
Solution Approach 2:
The patent performs preliminary determination of patient-specific stimulation thresholds before the actual MR measurement. By calculating the individual stimulation model in advance based on patient anatomy and position, the system can optimize gradient parameters beforehand, ensuring both patient comfort and optimal image quality without compromise during scanning.
2Device complexity
If a statistical stimulation model is used that accounts for only a certain percentage of test subjects, then device complexity is reduced, but measurement precision deteriorates because individual patient variations are not captured
Solution Approach 1:
The patent transitions from using population-average statistical parameters to patient-specific parameters including body composition (fat and muscle percentage and distribution), anatomical dimensions, and position-dependent factors. This parameter transformation enables precise individualized stimulation threshold determination while maintaining computational feasibility through efficient calculation methods.
3Reliability
If gradient performance is restricted to avoid stimulation in all patients, then reliability is improved by preventing adverse effects, but productivity deteriorates due to longer scanning times and reduced gradient efficiency
Solution Approach 1:
The patent performs preliminary calculation of patient-specific stimulation thresholds before the MR measurement. This advance preparation allows the system to determine the maximum safe gradient amplitudes for each patient individually, enabling optimal gradient performance during scanning without risking stimulation, thus maintaining both safety and efficiency.
Solution Approach 2:
The patent implements dynamic adaptation of gradient parameters based on calculated patient-specific thresholds. Rather than using fixed conservative limits for all patients, the system adjusts gradient amplitudes dynamically according to each patient's individual tolerance, maximizing scanning efficiency while ensuring safety.
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 allows for precise determination of peripheral nerve stimulation, optimizing gradient strength for individual patients, thereby improving image quality and reducing patient discomfort and scanning time, while increasing the efficiency of MRI processes.
Implementation Method 1
During a MR imaging process, a patient is exposed to magnetic fields that vary over time, in particular gradient fields. These gradient fields induce electrical fields in the patient's body, so that the patient experiences a stimulation of his peripheral nerves.
Data Source
AI summary
A method for determining peripheral nerve stimulation during MR imaging of a patient in a MR scan unit for a MR pulse sequence is described. In the method, a plurality of model-based candidate stimulations are determined dependent on a unit vector potential of the gradient magnet field generated during MR imaging and dependent on candidate data models for different object parameter values. A model-based candidate data stimulation is selected as a stimulation model for the patient dependent on an individual patient model. A distribution of a vector potential of a gradient magnetic field acting on the patient is determined as a function of a unit gradient current for a determined position of the patient in the MR scanning unit. The nerve stimulation of the patient is determined for the determined position based on the selected candidate stimulation and a gradient current of a gradient pulse of the MR pulse sequence.