Pulmonary MRI Motion-Compensated Reconstruction for Free-Breathing Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing dynamic pulmonary MRI methods face challenges due to low proton density, fast signal decay, respiratory motion, and variations in lung parenchyma signal intensity, leading to reduced image quality and inefficiencies in data acquisition.
Innovation Solution
A dynamic pulmonary MRI method using 3D radial UTE acquisition with interleaved spiral phyllotaxis, self-navigation for respiratory monitoring, motion-resolved reconstruction, and a motion-state weighted motion-compensated reconstruction algorithm to enhance temporal correlation and adapt to signal intensity variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If respiratory gating is used to acquire image data, then image quality is improved, but scanning efficiency deteriorates and only static image data can be acquired
Solution Approach 1:
The patent transitions from static respiratory-gated imaging to dynamic free-breathing imaging by continuously acquiring data throughout the respiratory cycle and using motion compensation algorithms to reconstruct images at different respiratory phases, enabling both high efficiency and image quality
Solution Approach 2:
The patent applies motion compensation and correction algorithms during the image reconstruction process to preemptively address respiratory motion artifacts, allowing free-breathing acquisition without sacrificing image quality
2Reliability
If UTE sequences are used to capture short T*2 signals, then signal acquisition is improved, but respiratory motion artifacts increase
Solution Approach 1:
The patent introduces self-navigation echoes and external respiratory monitoring signals as intermediaries to detect and characterize respiratory motion, which then guide the motion compensation process to eliminate artifacts while preserving signal quality
Solution Approach 2:
The patent implements feedback mechanisms where respiratory motion is continuously monitored and this information is fed back into the reconstruction algorithm to dynamically adjust and compensate for motion artifacts in real-time
3Productivity
If motion-resolved reconstruction is used, then dynamic imaging is achieved, but blurring artifacts increase with large motion displacement
Solution Approach 1:
The patent uses self-navigation echoes to provide real-time feedback on respiratory phase and position, enabling the reconstruction algorithm to correctly assign data to appropriate motion states and reduce blurring artifacts
Solution Approach 2:
The patent employs compressed sensing and parallel imaging techniques that change the sampling parameters and reconstruction approach to maintain image quality despite large motion displacements during free-breathing acquisition
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
Improves image reconstruction quality by reducing artifacts and increasing temporal correlation, enabling high-quality lung imaging and ventilation quantification with reduced scanning time.
Implementation Method 1
magnetic resonance imaging (MRI) technology has demonstrated the ability to detect pulmonary diseases
Implementation Method 2
ultrashort echo time (UTE) sequences are usually used for signal acquisition in pulmonary MRI. Such UTE sequences can capture short T*2 signals of the lung parenchyma with a sub-millisecond echo time (TE) by applying a readout gradient and starting to collect k-space signals immediately after a radio-frequency (RF) excitation
Data Source
AI summary
A dynamic pulmonary magnetic resonance imaging method, including: with an ultrashort echo time sequence, acquiring pulmonary magnetic resonance signals in a free-breathing condition; during data acquisition, monitoring a respiratory condition, obtaining a respiration curve; with the respiration curve, performing motion-resolved reconstruction on the acquired pulmonary magnetic resonance data, obtaining motion-resolved lung images; performing motion field estimation on the motion-resolved lung images; performing motion-state weighted motion-compensated reconstruction on results of the motion field estimation, obtaining dynamic pulmonary magnetic resonance images; performing ventilation map estimation on the dynamic pulmonary magnetic resonance images, obtaining a pulmonary ventilation.