Magnetic Resonance Elastography Inversion for Lung Tissue Shear Stiffness
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Solution Overview
Problem
Magnetic resonance elastography (MRE) faces challenges in accurately measuring shear stiffness of lung tissue due to low signal-to-noise ratio (SNR) caused by lung's low physical density and ultra-short T2* value, leading to underestimation of shear stiffness and potential misinterpretation of disease processes.
Innovation Solution
A method using MRI to calculate mechanical properties by acquiring MRE data, reconstructing images, producing a complex wave image, and calculating the principal frequency of the spatial frequency spectrum to estimate shear stiffness, which is more robust to low SNR data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If direct inversion of the Helmholtz equation is used to calculate shear modulus from MRE wave displacement data, then the method is simple and works well in moderate-to-high SNR data sets, but it underestimates shear stiffness in low SNR data sets such as lung tissue
Solution Approach 1:
The patent applies preliminary filtering and preprocessing to the MRE wave displacement data before performing the inversion calculation. By pre-processing the data to enhance signal quality and reduce noise effects, the method prepares the input data in a state that enables accurate shear stiffness estimation even in low SNR conditions, resolving the contradiction between simplicity and precision.
2Ease of operation
If conventional MRE pulse sequences are used to acquire lung tissue data, then the acquisition process is straightforward, but the ultra-short T2* value causes significant signal decay during echo time resulting in low SNR
Solution Approach 1:
The patent modifies key acquisition parameters including using ultrashort echo time (UTE) sequences to capture the rapidly decaying signal from lung tissue before it disappears. By changing the echo time to be comparable to or shorter than the T2* relaxation time, the method preserves signal intensity and achieves adequate SNR while maintaining operational feasibility.
3Adaptability or versatility
If MRE is applied to lung tissue with low physical density, then the method can potentially detect disease processes, but the decreased proton density reduces the number of contributing protons leading to decreased SNR
Solution Approach 1:
The patent introduces advanced signal processing techniques as intermediaries between the low-SNR raw MRE data and the final shear stiffness calculation. These intermediary processing steps include noise filtering, signal enhancement, and robust inversion algorithms that bridge the gap between the limited signal available from low-density lung tissue and the reliable mechanical property measurements needed for diagnostic 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
This approach provides a more accurate estimation of shear stiffness in lung tissue, reducing errors and improving diagnostic sensitivity and specificity by being less sensitive to SNR degradation, especially in low-density tissues like the lung.
Implementation Method 1
Magnetic resonance elastography (MRE) is a phase-contrast MRI technique that is capable of spatially resolving the shear stiffness of biological tissues
Implementation Method 2
MRE provides a sensitive metric for the detection of both benign and malignant processes in tissues
Data Source
AI summary
A method for calculating a mechanical property of a material using a magnetic resonance imaging (“MRI”) system is provided. The method is particularly robust to image data having low signal-to-noise ratio (“SNR”). An MRI system is used to acquire magnetic resonance elastography (“MRE”) data from a subject containing the material. Exemplary materials include lung tissue. Images are reconstructed from the MRE data and used to produce a wave image from which a spatial frequency spectrum is produced. A principal frequency of the spatial frequency spectrum is produced and used to calculate a mechanical property of the material. For example, shear stiffness may be calculated.