Multi-Slice MRI Reconstruction Using RF Phase Tagging
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Solution Overview
Problem
Current methods for simultaneous multi-slice MRI struggle with noise amplification and accurate separation of aliased pixels, particularly in close spatial proximity, leading to suboptimal image quality and increased scan time.
Innovation Solution
A method for reconstructing images from simultaneously acquired data from multiple slice locations using tailored RF phase tagging, which involves exciting slices with unique phases and acquiring reference images to unalias and correct phase drifts, allowing for improved separation of aliased signals and reduced noise amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If simultaneous multi-slice MRI is performed using conventional methods, then scan time is reduced, but noise amplification increases and image quality deteriorates
Solution Approach 1:
The patent divides the simultaneous multi-slice acquisition into separate slice-specific acquisitions with unique RF phase tags. Each slice is excited with a distinct phase, allowing the signals to be separated during reconstruction. This segmentation approach maintains the speed benefits of simultaneous acquisition while avoiding the noise amplification and aliasing problems that plague conventional simultaneous multi-slice methods.
Solution Approach 2:
The patent introduces RF phase tagging as an intermediary mechanism to encode slice-specific information. By applying unique phase shifts to each slice's RF excitation, the system creates distinguishable signal signatures that enable accurate slice separation during reconstruction. This intermediary phase encoding resolves the conflict between fast simultaneous acquisition and high-quality image reconstruction.
2Measurement precision
If slices are excited with unique phases for separation, then aliasing is reduced, but phase drift correction becomes necessary
Solution Approach 1:
The patent performs preliminary phase drift correction by acquiring reference images at the beginning of the scan sequence. These reference images capture the phase state of each slice before physiological motion and magnetic field drift occur. By establishing this baseline phase information in advance, the system can later correct for phase drifts during reconstruction without compromising slice separation accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where reference images are continuously acquired and used to update phase correction parameters throughout the scan. The system monitors phase drifts in real-time by comparing current images against reference data, then applies corrective phase adjustments to maintain accurate slice separation. This closed-loop feedback approach manages the complexity of phase correction while preserving measurement precision.
3Productivity
If multiple receiver coils are used for parallel imaging, then acquisition speed increases, but spatial encoding complexity increases
Solution Approach 1:
The patent applies local quality by assigning unique RF phase tags to specific slice locations rather than using uniform encoding across all slices. Each slice receives a customized phase profile tailored to its spatial position, which simplifies the reconstruction process for multi-coil simultaneous multi-slice imaging. This localized phase encoding approach reduces the overall spatial encoding complexity while maintaining high imaging speed.
Solution Approach 2:
The patent changes the phase parameter of the RF excitation pulses as a function of slice location. By systematically varying the phase parameter across different slices, the system creates distinct signal signatures that simplify the unaliasing process. This parameter modulation strategy reduces the computational complexity of handling multiple receiver coils simultaneously while preserving the accelerated imaging benefits.
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 enables faster acquisition of high-resolution functional connectivity data across the whole brain, reducing scan time and improving image quality by effectively addressing noise amplification and aliasing issues, making it suitable for fMRI applications like resting-state and functional connectivity assessments.
Implementation Method 1
MRI uses the nuclear magnetic resonance ('NMR') phenomenon to produce images. When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the nuclei in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) that is in the x-y plane and that is near the Larmor frequency, the net aligned moment, Mz, may be rotated, or 'tipped,' into the x-y plane to produce a net transverse magnetic moment, Mxy. A signal is emitted by the excited nuclei or 'spins,' after the excitation signal B1 is terminated
Implementation Method 2
The MR signals acquired with an MRI system are signal samples of the subject of the examination in Fourier space, or what is often referred to in the art as 'k-space.' Each MR measurement cycle, or pulse sequence, typically samples a portion of k-space along a sampling trajectory characteristic of that pulse sequence. Magnetic field gradients (Gx, Gy, and Gz) are employed for the spatial encoding of the signals.
Data Source
AI summary
A method for reconstructing a plurality of images depicting a subject from image data that is simultaneously acquired from a corresponding plurality of slice locations with a magnetic resonance imaging (MRI] system is provided. Image data is acquired following the application of radio frequency (RF] energy to the plurality of slice locations. The RF energy is tailored to provide a different phase to each of the plurality of slice locations. Reference image data is also acquired for each slice location following the application of RF energy that has the same phase as is used to excite the respective slice location for the acquisition of the image data. Aliased images are reconstructed from the image data, and reference images are reconstructed from the reference image data. Using both of these image sets, an unaliased image is produced for each of the plurality of slice locations.