Magnetic Resonance Fingerprinting with Exchange for Myocardial Tissue
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Solution Overview
Problem
Conventional MRI techniques struggle to distinguish and quantify multiple tissue compartments within a voxel due to magnetic exchange, leading to inaccurate relaxation parameter mapping, especially in tissues like myocardial tissue where exchange rates are rapid, making it difficult to separate intracellular and extracellular volumes effectively.
Innovation Solution
Magnetic Resonance Fingerprinting with Exchange (MRF-X) addresses this by explicitly modeling magnetic exchange between compartments, allowing for rapid and efficient quantification of T1 and T2 values, volume fractions, and exchange rates in a single scan without contrast agents, using pseudorandom flip angles and short acquisition times to differentiate signal evolutions from multiple compartments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRI techniques are used to produce relaxation parameter maps, then T1 and T2 values can be obtained, but multiple tissue compartments within a voxel cannot be distinguished due to magnetic exchange
Solution Approach 1:
The patent segments the voxel signal into multiple compartments by applying bi-exponential fitting models to separate intracellular and extracellular contributions. The signal is decomposed into distinct exponential components, each representing a different tissue compartment with its own relaxation characteristics, allowing independent quantification of T1 and T2 values for each compartment.
Solution Approach 2:
The patent changes the fitting model from a single exponential to a bi-exponential model to account for multiple compartments. By introducing additional parameters (separate T1 and T2 values for each compartment, plus volume fractions), the model can distinguish between different tissue compartments and resolve the mixing effect caused by magnetic exchange.
2Measurement precision
If long delays are used between NMR excitation and signal acquisition to sample recovery curves, then T1 mapping precision improves, but the ability to distinguish multiple compartments is lost due to signal averaging
Solution Approach 1:
The patent applies bi-exponential fitting to the signal data before performing T1 mapping to separate compartment contributions. By pre-segmenting the signal into distinct exponential components, the method preserves compartment-specific information throughout the T1 mapping process, allowing accurate T1 values to be determined for each compartment independently rather than losing this information in averaged measurements.
Solution Approach 2:
The patent uses dynamic multi-parameter fitting that adapts to the signal characteristics at different time points. The bi-exponential model dynamically separates the contributing compartments based on their distinct relaxation behaviors, enabling the method to extract accurate T1 values for each compartment even when signals are acquired at multiple time points during the recovery process.
3Difficulty of detecting and measuring
If contrast agents are used to enhance tissue differentiation, then compartment visibility improves, but harm to patients with kidney dysfunction occurs
Solution Approach 1:
The patent uses the intrinsic magnetic properties of different tissue compartments (different T1 and T2 relaxation times) to achieve compartment differentiation without external contrast agents. The bi-exponential fitting method exploits the natural relaxation behavior of intracellular and extracellular water, allowing the tissue itself to provide the contrast needed for differentiation, thereby eliminating the need for potentially harmful gadolinium-based contrast agents.
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
MRF-X enables accurate characterization of myocardial tissue by directly measuring extracellular volume fraction and quantifying T1 and T2 values for separate compartments, improving the detection of conditions like fibrotic disease and reducing the need for contrast agents, which can be harmful to patients with kidney dysfunction.
Implementation Method 1
MRF-X addresses this by explicitly modeling magnetic exchange between compartments, allowing for rapid and efficient quantification of T1 and T2 values, volume fractions, and exchange rates in a single scan
Implementation Method 2
The relaxation parameter maps are produced from nuclear magnetic resonance (NMR) signals produced in response to NMR excitation
Implementation Method 3
using pseudorandom flip angles and short acquisition times to differentiate signal evolutions from multiple compartments
Data Source
AI summary
Example embodiments associated with characterizing a sample using NMR fingerprinting are described. One example NMR apparatus includes an NMR logic that repetitively and variably samples a (k, t, E) space associated with an object to acquire a set of NMR signals that are associated with different points in the (k, t, E) space. Sampling is performed with t and/or E varying in a non-constant way. The NMR apparatus may also include a signal logic that produces an NMR signal evolution from the NMR signals and a characterization logic that characterizes a tissue in the object as a result of comparing acquired signals to reference signals. Example embodiments facilitate analyzing voxels having multiple compartments that may experience magnetic exchange. The compartments may be, for example, an intracellular volume and an extracellular volume in a tissue that experiences magnetic exchange due to the movement of water between the volumes.