Myelin Fraction Mapping via Multi-Parameter Bloch Simulation
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Solution Overview
Problem
Current MRI diagnostic methods lack the ability to accurately quantify and image myelin tissue in the brain, which is crucial for diagnosing diseases such as dementia and multiple sclerosis, as they rely on relative signal intensity rather than absolute physical parameters like T1 and T2 relaxation times and proton density.
Innovation Solution
A method and system that generate a myelin fraction map by measuring multiple physical parameters (T1 and T2 relaxation times, R1 and R2 relaxation rates, and proton density) using a Bloch simulation model, allowing for the derivation of myelin water, semi-solids, and total water content, enabling precise imaging and analysis of brain tissue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple physical parameters (T1, T2, R1, R2, PD) are measured using MR quantification sequences, then measurement precision of myelin content is improved, but device complexity and acquisition time increase
Solution Approach 1:
The patent applies parameter changes by utilizing multiple different MR physical parameters (T1 relaxation time, T2 relaxation time, R1 relaxation rate, R2 relaxation rate, and proton density) to characterize myelin content. By measuring and combining these different physical parameters, the method achieves more precise quantification of myelin fraction than single-parameter methods, resolving the contradiction between measurement precision and parameter complexity through systematic multi-parameter analysis.
2Measurement precision
If multiple physical parameters are measured to derive myelin fraction, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent applies preliminary action by performing Bloch simulations to generate expected signal intensities for various tissue compositions before actual measurement. The pre-computed look-up tables store simulated signal values for different combinations of myelin fraction, water fraction, and semi-solid fraction. During actual MR measurement, the acquired signal intensities are directly compared against these pre-computed tables to rapidly determine tissue composition, significantly reducing the time required for data analysis while maintaining high measurement precision.
3Measurement precision
If Bloch simulation model with look-up tables is used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-computing Bloch simulations for various tissue compositions and storing results in look-up tables before actual clinical use. The simulation model predicts signal intensities for different combinations of myelin fraction (0-100%), water fraction, and semi-solid fraction. These pre-computed tables are stored in memory and used during actual measurements to rapidly match acquired signals with simulated values, avoiding the need to perform complex simulations in real-time while maintaining high quantification accuracy.
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 the generation of absolute myelin fraction maps per unit volume, providing detailed insights into brain tissue composition, including myelin water fraction, edema, and total myelin content, facilitating improved diagnostic capabilities with a short MR acquisition.
Implementation Method 1
When the object to be imaged is placed in a powerful, uniform magnetic field the spins of the atomic nuclei with non-integer spin numbers within the tissue all align either parallel to the magnetic field or anti-parallel
Implementation Method 2
As the excited protons relax and realign, they emit energy at rates which are recorded to provide information about their environment
Implementation Method 3
The realignment of proton spins with the magnetic field is termed longitudinal relaxation and the time (typically about 1 sec) required for a certain percentage of the tissue nuclei to realign is termed 'Time 1' or T1
Implementation Method 4
T2-weighted imaging relies upon local dephasing of spins following the application of the transverse energy pulse; the transverse relaxation time
Implementation Method 5
A Bloch simulation model (see e.g. Levesque R, Pike GB. Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T2 relaxometry: A unified view via a four-pool model. Mag Reson Med 2009;62:1487-1496) can be set up to relate tissue composition to the expected observation of MR quantification results
Data Source
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AI summary
A computerized method of generating a map of myelin tissue of a brain is described. In addition sub-maps of different myelin contents can be imaged. The method uses a simulation model comprising at least two interacting tissue compartments.