Liver MR Elastography Setup for Precise Driver Positioning
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Solution Overview
Problem
Existing MR elastography methods face challenges in accurately positioning the oscillation generator and selecting the examination region for liver imaging, leading to potential faults and inefficiencies in the preparation and execution of MR elastography of the liver.
Innovation Solution
A method involving photographic recording, determination of liver position, and precise placement of the oscillation generator based on target positions, combined with automated selection of examination regions using trained functions and patient models, ensures accurate and efficient positioning and region selection for MR elastography.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual positioning of the oscillation generator and selection of examination region is performed by medical personnel, then flexibility and adaptability are maintained, but positioning accuracy and consistency deteriorate due to dependence on personnel experience
Solution Approach 1:
The system performs self-positioning and self-selection of examination regions through automated image analysis and machine learning algorithms. The oscillation generator position and examination region are determined automatically by the system based on photographic recordings and MR image data, eliminating dependence on medical personnel experience while maintaining high positioning accuracy
Solution Approach 2:
Manual mechanical positioning by medical personnel is replaced with automated computational methods. The system uses photographic recording analysis, trained machine learning functions, and automatic coordinate transformation to determine the oscillation generator position and examination region, substituting human judgment with algorithmic processing
2Reliability
If automated positioning and region selection methods are implemented, then positioning accuracy and consistency are improved, but the complexity of the preparation process increases
Solution Approach 1:
The system integrates multiple functions into a unified automated preparation process. The same system performs photographic recording, liver position determination, oscillation generator positioning, and examination region selection using trained functions, creating a universal platform that handles all preparation steps consistently without requiring separate manual procedures
Solution Approach 2:
The system performs preliminary analysis and determination steps before the actual MR elastography measurement. Photographic recordings are analyzed in advance to determine liver position, and trained functions pre-calculate the optimal oscillation generator position and examination region, preparing all parameters beforehand to ensure consistent and reliable results during the measurement
3Measurement precision
If precise positioning of the oscillation generator is achieved through automated methods, then the quality of MRE image data is improved, but the time required for preparation increases due to multiple processing steps
Solution Approach 1:
The automated preparation process operates continuously without interruption. The system processes photographic recordings, determines liver position, calculates oscillation generator coordinates, and selects examination regions in a continuous automated sequence, eliminating the need for repeated manual adjustments and repositioning that would otherwise be required to achieve the same level of precision
4Measurement precision
If the examination region is automatically selected based on trained functions and overview MR image data, then the accuracy of region selection is improved, but the complexity of data processing increases
Solution Approach 1:
Manual visual inspection and selection of examination regions is replaced with automated image processing algorithms. The system uses trained machine learning functions to automatically analyze overview MR image data, identify the liver and relevant examination regions, and determine optimal slice positions, substituting complex manual visual assessment with computational image analysis
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
Enables robust and time-efficient preparation of MR elastography by reducing the likelihood of faulty positioning and enhancing the quality of MRE image data through precise alignment of the oscillation generator and examination region, independent of medical personnel experience.
Implementation Method 1
an oscillation generator is required to generate the mechanical waves, in particular in the examination region of the examination object
Implementation Method 2
the phase of the magnetic resonance signals changes as a result of mechanical waves acting upon the examination object. The extent of this change depends upon the deflection (i.e. the displacement from the rest position) of the tissue as a result of the mechanical waves
Data Source
AI summary
Techniques are disclosed for preparing an MR elastography of a liver, which includes creating a photographic recording of an examination object, determining a position of the liver on the basis of the photographic recording, providing an information item regarding a target position of an oscillation generator on the basis of the position of the liver, arranging the oscillation generator on the examination object dependent upon the information regarding the target position, introducing the examination object with the oscillation generator into a patient receiving region of a magnetic resonance device, capturing overview MR image data from the examination object, and selecting an examination region for transverse slices covering at least one subregion of the liver for a recording of MRE image data on the basis of the overview MR image data.