MR Spin Species Assignment Using Information Dataset
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Solution Overview
Problem
Magnetic resonance (MR) techniques, such as the Dixon method, face ambiguity in assigning combination images obtained from multi-contrast measurements to the correct spin species, particularly in water/fat separation, due to phase ambiguities and local minima issues, leading to incorrect assignments across multiple recordings.
Innovation Solution
An automated method using an information MR dataset acquired from an examination object, which includes additional information like spectroscopic data and coil sensitivity, to unambiguously assign combination images to the correct spin species by determining dominant species distribution and using this information to correct for phase ambiguities and local interchanges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Dixon technique is used to separate signals from different spin species, then signal separation capability is improved, but unambiguous assignment of combination images to spin species deteriorates due to phase ambiguities and local minima
Solution Approach 1:
The patent introduces an information MR dataset as an intermediary that provides additional object-specific information (such as spectroscopic data, T1/T2 relaxation times, or signal intensity patterns) to disambiguate the assignment of combination images to spin species. This intermediary dataset resolves the phase ambiguity by providing independent verification data that distinguishes between water and fat signals when standard Dixon subtraction/addition methods produce ambiguous results due to local minima or delta B0 variations.
2Productivity
If multiple MR datasets are recorded at different echo times, then combination images representing different spin species can be extracted, but correct identification of which image represents which spin species deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where the information MR dataset is used to verify and correct the assignment of combination images to spin species. The system extracts combination images from multiple datasets recorded at different echo times, then uses the independent information dataset to provide feedback on the correctness of assignments, allowing automatic correction of misidentifications caused by local minima or phase ambiguities in the standard Dixon processing.
3Measurement precision
If automated assignment method using information MR dataset is implemented, then assignment accuracy is improved, but measurement time and system complexity increase
Solution Approach 1:
The patent achieves universality by designing the information MR dataset acquisition to serve multiple purposes: it provides object-specific information for assignment disambiguation, can be used for other quantitative MRI parameters, and maintains compatibility with existing Dixon processing pipelines. This multi-functionality justifies the additional complexity by providing broad utility beyond just spin species assignment.
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 accurate and unambiguous global assignment of combination images to the correct spin species, improving the accuracy and consistency of MR image analysis by directly utilizing object-specific information for precise spin species identification.
Implementation Method 1
nuclear spins in the object are oriented along the constant magnetic field. To trigger nuclear spin resonances, radio-frequency excitation pulses (RF pulses) are radiated into the examination object
Implementation Method 2
the examination object is positioned in a magnetic resonance scanner in a strong static, homogeneous constant magnetic field, also called a B0 field
Implementation Method 3
the echo times are selected such that the relative phase position of different spin species of the signals contained in an MR dataset is different in the various recorded MR datasets
Data Source
AI summary
In a method and apparatus for the automatic assignment of at least one combination image of an examination object to a spin species represented in a combination magnetic resonance (MR) image, an information MR dataset is obtained and evaluated in a computer to determine information about the examination object from the captured information MR dataset. At least two MR datasets are acquired at one of at least two echo times in each case following an excitation by a multi-contrast measurement. At least one combination image is determined from the at least two MR datasets, and spin species represented in the at least one combination image are assigned on the basis of the information determined from the information MR dataset. By using additional information about the examination object determined by MR technology an automatic unambiguous global assignment of the correct spin species is enabled.