Respiratory Motion Correction in Cardiac MRI via Phase Shifts
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Solution Overview
Problem
Current cardiac magnetic resonance (CMR) perfusion imaging techniques face challenges with motion-induced artifacts due to respiratory motion, particularly in k-t accelerated and compressed sensing methods, which limit spatial and temporal resolution and image quality.
Innovation Solution
The method involves acquiring magnetic resonance data for the heart region, performing rigid motion registration to derive linear phase shifts, and applying these shifts to correct motion artifacts, enabling motion-corrected image reconstruction using techniques like k-t PCA or k-t SLR, thereby reducing respiratory-induced blurring and improving image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If k-t accelerated techniques are used to reduce data acquisition time, then productivity is improved, but measurement precision deteriorates due to motion-induced artifacts
Solution Approach 1:
The patent segments the image reconstruction process into multiple independent time frames, each corresponding to a single heartbeat. This allows motion correction to be applied selectively to each frame before combining them, thereby maintaining high acquisition speed while improving image quality by addressing motion artifacts frame-by-frame rather than treating the entire dataset as a single unit.
Solution Approach 2:
The patent applies linear phase shifts to the acquired data based on registered motion parameters. By changing the phase parameters of the k-space data according to measured respiratory motion, the method corrects motion-induced artifacts while preserving the accelerated acquisition benefits, thus resolving the contradiction between speed and image quality.
2Measurement precision
If non-rigid registration techniques are applied to correct cardiac and respiratory motion, then measurement precision is improved, but device complexity increases and reliability decreases due to image degradation from repeated spatial interpolation
Solution Approach 1:
The patent extracts only the necessary rigid motion parameters (translation and rotation) from the data using robust registration techniques, rather than applying complex non-rigid registration to the entire image. This extracted motion information is then used to apply linear phase shifts, achieving effective motion correction without the degradation caused by repeated spatial interpolation inherent in non-rigid methods.
Solution Approach 2:
The patent replaces the mechanical approach of spatial interpolation (re-sampling images to align them) with a mathematical phase-shifting approach in k-space. This substitution eliminates the need for repeated interpolation operations that degrade image quality, while still achieving accurate motion correction through phase modulation based on registered motion parameters.
3Measurement precision
If navigator gating techniques are used for free breathing coronary imaging, then measurement precision is improved, but productivity decreases due to prolonged acquisition time
Solution Approach 1:
The patent uses self-gating techniques where motion information is extracted directly from the acquired imaging data itself, rather than requiring separate navigator echoes. This allows the system to simultaneously acquire imaging data and motion information in the same signal, eliminating the need for additional navigator acquisition time and thus maintaining high productivity while achieving motion correction.
Data Source
AI summary
In some aspects, the disclosed technology relates to reducing respiratory-induced motion artifacts for accelerated imaging. In one embodiment, magnetic resonance data may be acquired for an area of a subject containing the heart. The acquired data may include motion-corrupted data due to respiration of the subject. From the acquired data, an image may be independently reconstructed for each of a plurality of time frames, with each time frame corresponding to one of a plurality of heartbeats. A region containing the heart of the subject may be automatically detected in the reconstructed images, and rigid motion registration may be performed on the region of the reconstructed images containing the heart. Based on the rigid motion registration, a linear phase shift for motion correction may be determined. The linear phase shift may be applied to the motion-corrupted data to produce linear phase-shifted data, and a k-t image reconstruction may be performed on the linear phase-shifted data to produce motion-corrected images.