Accelerated MRF Acquisition Using EPI and Segmented Trajectories
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Solution Overview
Problem
Current magnetic resonance fingerprinting (MRF) techniques require a large number of acquisitions, leading to lengthy scan times and increased specific absorption rate (SAR), with undersampling resulting in errors and image artifacts, limiting their clinical usage.
Innovation Solution
The method optimizes acquisition parameters to reduce the number of repetition time (TR) periods necessary for MRF, using echo-planar imaging (EPI) and segmented EPI sequences to fully sample k-space, thereby increasing discrimination between quantitative parameters and reducing scan time without compromising image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of TR periods are used for MRF acquisitions, then parameter estimation accuracy is improved, but scan time increases significantly
Solution Approach 1:
The patent changes the acquisition parameters by using optimized trajectories (EPI, segmented EPI, spiral) and adjusting sampling density in k-space. By modifying how k-space is sampled rather than simply reducing the number of TR periods, the system achieves faster scans while maintaining parameter estimation accuracy through the optimized sampling patterns that preserve signal evolution information.
Solution Approach 2:
The patent segments the k-space sampling process into different trajectories (EPI, segmented EPI, spiral) and divides the acquisition into multiple readouts per TR period. This segmentation allows the system to acquire multiple k-space lines or segments during each TR period, effectively reducing the total number of TR periods needed while maintaining comprehensive signal sampling for accurate parameter estimation.
2Loss of time
If undersampling is used to reduce scan time, then scan time is reduced, but image artifacts and errors increase
Solution Approach 1:
The patent employs dynamic k-space sampling trajectories (EPI, segmented EPI, spiral) that adaptively sample k-space based on the signal evolution characteristics. These dynamic trajectories optimize the sampling density and distribution to maintain image quality and reduce artifacts while achieving significant scan time reduction compared to static undersampling approaches.
Solution Approach 2:
The patent uses feedback from the measured signal evolutions to guide the optimization of acquisition parameters and trajectory selection. By analyzing the signal characteristics and using this feedback to adjust sampling strategies, the system maintains image quality and minimizes artifacts while reducing scan time through adaptive undersampling that preserves critical signal information.
3Loss of time
If the number of TR periods is reduced, then scan time is reduced, but discrimination between quantitative parameters decreases
Solution Approach 1:
The patent transitions from time-domain parameter variation to k-space trajectory optimization as an additional dimension for achieving parameter discrimination. By using optimized EPI, segmented EPI, or spiral trajectories in k-space and combining these with variable flip angle and phase encoding, the system creates sufficient signal evolution patterns to discriminate between quantitative parameters with fewer TR periods.
Solution Approach 2:
The patent performs preliminary optimization of acquisition parameters and trajectory selection before the actual MRF acquisition. By pre-calculating and selecting optimal EPI, segmented EPI, or spiral trajectories along with variable flip angle and phase encoding schemes, the system ensures that each TR period provides maximum information content for parameter discrimination, thereby reducing the total number of TR periods needed.
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 achieves a significant reduction in scan time, up to a 100-fold decrease, while maintaining accurate parameter estimation and reducing computational burden and artifacts, enabling faster and more efficient MRF acquisitions.
Implementation Method 1
a magnet system configured to generate a polarizing magnetic field about at least a portion of a subject
Implementation Method 2
a magnetic gradient system including a plurality of magnetic gradient coils configured to apply at least one magnetic gradient field to the polarizing magnetic field
Implementation Method 3
a radio frequency (RF) system configured to apply an RF field to the subject and to receive magnetic resonance signals from the subject
Data Source
AI summary
Systems and methods for accelerating magnetic resonance fingerprinting (“MRF”} acquisitions are described. Acquisition parameters can be optimized to reduce the number of acquisitions necessary while maximizing the discrimination between the physical parameters to be estimated. The systems and methods may also include implementing pulse sequences that rapidly acquire large volumes of k-space data, including echo-planar imaging (“EPI”} and segmented EPI sequences.