Voxelwise Spectral Profile Modeling for Multispectral MRI
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Solution Overview
Problem
Current 3D multispectral magnetic resonance imaging (MRI) techniques face challenges in effectively suppressing fat signals and removing pile-up intensity artifacts near metallic implants, which limits their utility in assessing orthopedic devices and surrounding tissues.
Innovation Solution
The method involves estimating spectral profile parameters, such as amplitude, center frequency, and width, from multispectral data using a spectral profile model, allowing for the suppression of fat signals and mitigation of pile-up intensity artifacts without additional scans or RF pulses, and enabling accelerated MSI acquisitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional 3D multispectral MRI techniques are used to image near metallic implants, then susceptibility artifacts are reduced, but fat signals and pile-up intensity artifacts remain problematic
Solution Approach 1:
The patent changes spectral parameters by estimating spectral profile parameters (amplitude, center frequency, width) at each voxel and using these to selectively suppress fat signals while preserving other tissue signals. This parameter-based approach allows differentiation and suppression of specific signal sources without affecting overall image quality
Solution Approach 2:
The patent applies local quality by performing voxelwise spectral profile analysis, where each voxel is processed individually to estimate its specific spectral characteristics. This allows localized suppression of fat signals and artifacts only where needed, rather than applying global suppression that would affect all tissues uniformly
2Measurement precision
If spectral profile modeling is performed at each voxel to suppress fat signals and remove artifacts, then image accuracy improves, but processing complexity increases
Solution Approach 1:
The patent applies preliminary action by performing spectral profile parameter estimation on calibration data acquired before the actual imaging sequence. These pre-estimated parameters are then used to guide the suppression of fat signals and artifacts during image reconstruction, reducing the computational burden during the main imaging process
Solution Approach 2:
The patent uses calibration data as a copy or proxy for the actual imaging data to estimate spectral profile parameters. This separate calibration dataset allows characterization of spectral properties without requiring additional processing of the primary diagnostic images, thereby managing complexity while maintaining accuracy
3Productivity
If undersampled multispectral data are used to accelerate acquisition, then scan time is reduced, but data completeness and image quality deteriorate
Solution Approach 1:
The patent replaces the mechanical/data acquisition system with a computational system by using spectral profile modeling and parameter estimation to infer missing data from undersampled measurements. Instead of acquiring complete data through extended sampling, the system computationally reconstructs missing information based on spectral characteristics
Solution Approach 2:
The patent applies self-service by using the spectral profile parameters estimated from the available undersampled data itself to guide the reconstruction and suppression processes. The data contains sufficient information to characterize spectral properties, which then serve to complete and enhance the reconstruction without requiring external reference data
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 enhances the accuracy and clarity of MRI images by effectively suppressing fat signals and reducing artifacts, improving the assessment of tissues near metallic implants and facilitating faster and more efficient MSI data acquisition.
Implementation Method 1
Magnetic resonance imaging ('MRI') soft-tissue contrast adds substantial value when assessing the tissue envelope around metallic implants
Implementation Method 2
A chemical shift fraction associated with signal contributions from fat spins can be estimated from the estimated width of the spectral profile
Data Source
AI summary
Described here are systems and methods for using a magnetic resonance imaging (“MRI”) system to estimate parameters of spectral profiles contained in multispectral data acquired using multispectral imaging (“MSI”) techniques, such as MAVRIC. These spectral profile parameters are reliably extracted using an iterative perturbation theory technique and utilized in a number of different applications, including fat suppression, artifact correction, and providing accelerated data acquisitions.