MRI Navigator Motion Correction for Non-Rigid Joint Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Magnetic resonance imaging of large joints, such as the knee, faces challenges in motion correction due to non-rigid body motion, which existing techniques struggle to accurately model and compensate for, leading to image artifacts like blurring and ghosting.
Innovation Solution
The method involves dividing the magnetic resonance (MR) navigator field of view into multiple sub-sections, assuming rigid motion within each, and using ultra-fast SMS-EPI navigator techniques to track motion, allowing for rapid acquisition and compensation, which can be integrated into the MRI sequence for real-time adjustment or retrospective reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If rigid body motion correction is applied to large joint imaging, then motion artifacts are reduced, but the accuracy of motion modeling deteriorates because large joints undergo non-rigid motion
Solution Approach 1:
The patent divides the large joint into multiple sub-volumes, each of which is assumed to undergo rigid body motion. Navigator echoes are acquired for each sub-volume separately, allowing independent motion tracking. This segmentation approach resolves the contradiction by applying rigid body models locally to small regions where they are valid, rather than forcing a global rigid body model on the entire non-rigid joint.
Solution Approach 2:
The patent applies different motion correction strategies to different regions of the joint. By assuming rigid body motion only within small local sub-volumes rather than globally, the method achieves accurate motion modeling locally while handling non-rigid motion overall. Each sub-volume receives tailored motion correction based on its local rigid body assumptions.
2Measurement precision
If multiple navigator echoes are acquired for each sub-volume, then motion tracking precision is improved, but scan time increases
Solution Approach 1:
The patent combines multiple navigator echo acquisitions for different sub-volumes into a single integrated pulse sequence. By merging the acquisition of navigator echoes from multiple sub-volumes into one coordinated process rather than separate sequential acquisitions, the method achieves precise multi-region motion tracking without proportionally increasing total scan time.
Solution Approach 2:
The patent implements continuous motion tracking throughout the imaging sequence by acquiring navigator echoes continuously during the scan. This allows motion data to be collected for all sub-volumes without interrupting the imaging process, maintaining continuous useful action for both motion tracking and image acquisition simultaneously.
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 effectively compensates for non-rigid motion in large joints by allowing precise tracking and correction of motion artifacts, improving image quality and practicality in clinical settings.
Implementation Method 1
a strong, static, homogenous basic magnetic field is generated, typically having a field strength of 0.2 through 7 or more Tesla, causes nuclear spins in the subject to be oriented along the field lines of the basic magnetic field
Implementation Method 2
In order to trigger magnetic resonance signals, the examination subject is irradiated with radio-frequency excitation pulses (RF pulses), that cause the nuclear spins to deviate from the aligned orientation produced by the basic magnetic field. As the excited nuclear spins relax (i.e., return to the original orientation), they emit magnetic resonance signals.
Data Source
AI summary
In a magnetic resonance (MR) navigator-based method and apparatus, MR data are acquired from a large joint of a patient, which is not modelable as a whole based on a single rigid body model. The field of view which the MR data are acquired is divided in a processor into multiple sub-sections, with each sub-section being modelable based on a rigid body model. MR navigator signals are acquired from each of the sub-sections, and these navigator signals are used in a motion tracking algorithm that is based on a rigid body model in order to generate a modeling result that tracks the movement of the overall joint within the field of view. The modeling result can be used for prospective or retrospective motion correction of the MR data.