MR Pulse Sequence Adjustment Using Patient Motion Forecasting
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Solution Overview
Problem
Patient movement during magnetic resonance (MR) imaging can significantly degrade image quality, necessitating re-recording of MR signals and limiting diagnostic effectiveness, as existing methods either correct for movement post-image acquisition or rely on external sensors and navigators that are not proactive in preventing movement artifacts.
Innovation Solution
A method that records patient movement signals before and during MR examinations to predict future movement, allowing for dynamic adjustment of the pulse sequence to minimize movement artifacts by selecting optimal imaging sequences such as SPACE, TSE, PROPELLER, or HASTE based on movement probability information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patient movement correction methods are used (navigators, external sensors, cameras), then movement artifacts can be reduced, but device complexity and measurement time increase
Solution Approach 1:
The system uses the patient's own physiological signals (breathing, heartbeat) detected by MR-compatible sensors to automatically adjust pulse sequence parameters, eliminating the need for external correction systems like cameras or complex navigators
Solution Approach 2:
The pulse sequence parameters (such as timing, repetition rate) are dynamically adjusted based on real-time analysis of patient movement signals, allowing the system to adapt to patient state without adding complex hardware
2Reliability
If multiple averagings are performed to reduce movement influence, then image quality improves, but measurement time increases
Solution Approach 1:
The system dynamically determines the number of averagings needed based on real-time patient movement assessment, performing only as many repetitions as necessary to achieve acceptable image quality rather than always using fixed high numbers of averagings
Solution Approach 2:
Movement signals are continuously monitored and fed back to adjust the acquisition protocol in real-time, allowing the system to reduce or skip averagings when patient movement is minimal and maintain quality when movement occurs
3Reliability
If inherently robust sequences (radial, PROPELLER) are used, then resistance to movement improves, but productivity and image quality for certain applications decrease
Solution Approach 1:
The system dynamically selects between different pulse sequence types (conventional vs. robust sequences like PROPELLER) based on real-time patient movement assessment, using efficient sequences when appropriate and robust sequences only when movement requires it
Solution Approach 2:
Instead of always using robust sequences, the system changes pulse sequence parameters adaptively based on patient state, maintaining high productivity when possible and switching to movement-resistant sequences only when necessary
4Reliability
If recordings are only carried out in certain breathing or ECG states, then movement artifacts are reduced, but measurement time and complexity increase
Solution Approach 1:
Patient movement characteristics are assessed in advance during positioning or preliminary scans, allowing the system to pre-determine optimal pulse sequence parameters before the actual diagnostic imaging begins
Solution Approach 2:
Real-time monitoring of physiological signals provides feedback to adjust acquisition timing and parameters, allowing flexible synchronization with breathing or cardiac cycles without requiring strict gating that would extend measurement time
Data Source
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AI summary
The invention relates to a method for setting the pulse sequence of a magnetic resonance (MR) examination of a patient, an MR device (10), and a computer program. The method comprises the following steps: A motion signal is acquired, which depends on the patient's movement. Based on the motion signal and a determination information, a motion probability information is determined. This motion probability information includes a probability of future patient movement. The pulse sequence is set based on this motion probability information.