Segmented Diffusion-Weighted MRI Acquisition Within Single Repetition Time
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Solution Overview
Problem
Current diffusion-weighted magnetic resonance imaging (DWI) techniques face challenges in reducing measurement time while maintaining image quality, particularly due to the limitations of existing acceleration techniques and the susceptibility of segmented recording methods to phase inconsistencies.
Innovation Solution
The method involves radiating a series of RF pulses and switching diffusion gradients to generate multiple diffusion-weighted echo signals within a single repetition time, allowing for the segmented recording of diffusion-weighted measurement data in the readout direction. This approach enables the acquisition of multiple diffusion-weighted datasets with different diffusion weightings within a single excitation, reducing overall measurement time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If segmented recording methods are used to reduce measurement time, then productivity is improved, but measurement precision deteriorates due to phase inconsistencies
Solution Approach 1:
The patent applies segmentation by dividing the k-space recording into multiple segments that are acquired sequentially within a single repetition time. Each segment is recorded with a specific segment-selection gradient, allowing parallel acquisition of multiple diffusion-weighted datasets from different k-space regions. This segmentation enables reduced measurement time while maintaining data consistency through synchronized gradient switching.
Solution Approach 2:
The patent employs periodic action through the systematic switching of segment-selection gradients in a defined sequence. Each gradient switching cycle corresponds to the acquisition of one segment, creating a periodic pattern that ensures consistent phase relationships across all segments. This periodic gradient switching resolves phase inconsistencies by maintaining temporal synchronization between gradient application and signal acquisition.
2Measurement precision
If multiple diffusion-weighted datasets are acquired with different weightings, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent merges the acquisition of multiple diffusion-weighted datasets with different weightings into a single repetition time. By combining multiple diffusion-weighted acquisitions that would traditionally require separate TR periods into one synchronized recording sequence, the patent achieves multiple b-values simultaneously. This merging eliminates the time loss associated with sequential acquisitions while preserving the precision of diffusion weighting through controlled gradient application.
Solution Approach 2:
The patent maintains continuity of useful action by acquiring multiple diffusion-weighted datasets without interruption within a single TR period. The continuous acquisition process eliminates idle time between measurements, ensuring that the useful action of data acquisition proceeds uninterrupted. This continuity preserves measurement precision while minimizing time loss by eliminating gaps between diffusion-weighted acquisitions.
3Manufacturing precision
If diffusion gradients are switched to achieve different diffusion weightings, then manufacturing precision is improved, but use of energy increases
Solution Approach 1:
The patent applies partial action by using segment-selection gradients that selectively activate only the necessary portions of k-space for each diffusion weighting. Instead of applying full gradient strength across the entire k-space for each diffusion-weighted acquisition, the method uses partial gradient switching tailored to the specific segment being recorded. This partial action maintains precise diffusion weighting control while reducing the cumulative energy consumption of gradient switching.
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 method significantly reduces the overall measurement time required for diffusion-weighted imaging while minimizing the impact of object movement, such as breathing, by allowing for temporally closely connected recordings of different diffusion-weighted datasets.
Implementation Method 1
the examination object is positioned in a magnetic resonance device in a relatively strong, static, homogeneous main magnetic field, also known as the B0 field... in order to trigger nuclear spin resonances that are measurable as signals, high-frequency excitation pulses (RF pulses) are radiated into the examination object
Implementation Method 2
the examination object is positioned in a magnetic resonance device in a relatively strong, static, homogeneous main magnetic field... so that its nuclear spins become oriented along the main magnetic field
Implementation Method 3
Diffusion should be understood to be the Brownian motion of molecules in a medium... additional gradients that reveal the diffusion direction and weighting are inserted into a pulse sequence to make visible or measure the diffusion properties of the tissue... tissue with rapid diffusion (e.g., cerebrospinal fluid (CSF)) is subject to a stronger signal loss than tissue with slow diffusion
Implementation Method 4
switching a first diffusion-rephasing gradient in the desired diffusion direction, which rephases the magnetization remaining in the transverse plane so that after the first diffusion-rephasing gradient, a first echo signal is formed
Data Source
AI summary
A plurality of diffusion-weighted measurement datasets (including at least one initial and one further measurement dataset) are recorded following a common excitation and thus within a repetition time (TR) using segmented recording in the readout direction.