Four-Dimensional MRI Data Acquisition During Subject Motion
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Solution Overview
Problem
Current magnetic resonance imaging (MRI) techniques face inefficiencies in acquiring four-dimensional data sets for repetitive motion, particularly in handling irregular breathing patterns and ensuring complete data acquisition without the need for additional monitoring devices.
Innovation Solution
The method divides the acquisition into two operational phases: the first phase involves building a motion phase mapping by acquiring initial k-space portions and storing motion signals, while the second phase uses this mapping to predict and acquire subsequent k-space portions based on the predicted motion phases, allowing for efficient completion of the four-dimensional data set.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion phase mapping is built up before acquiring k-space portions, then motion prediction accuracy is improved, but acquisition time is increased
Solution Approach 1:
The system performs preliminary motion phase mapping by acquiring initial k-space portions and storing motion signals during a first operational portion before the main data acquisition. This preliminary action builds up the motion phase mapping that enables accurate motion prediction during subsequent acquisitions, resolving the contradiction by preparing the prediction model in advance rather than during the critical imaging phase.
Solution Approach 2:
The acquisition process is segmented into two distinct operational portions: a first portion for building motion phase mapping with initial k-space acquisitions, and a second portion for efficient data acquisition using motion prediction. This segmentation allows the system to invest time in motion characterization separately from the time-critical imaging phase, improving overall efficiency.
2Measurement precision
If additional triggering devices are used to monitor irregular breathing patterns, then motion detection accuracy is improved, but device complexity is increased
Solution Approach 1:
The MRI system uses its own acquired data (initial k-space portions and motion signals) to build the motion phase mapping and enable motion prediction, rather than relying on external triggering devices. The system serves its own motion monitoring needs using internally acquired information, eliminating the need for additional respiratory belts, cameras, or other external monitoring equipment.
Solution Approach 2:
The acquired motion signals serve multiple purposes: they are used both for building the motion phase mapping and for predicting subsequent motion phases. The same data acquisition infrastructure is utilized for both motion characterization and image data collection, making the system multi-functional without adding separate monitoring devices.
3Productivity
If conventional MRI acquisition is used without motion prediction, then acquisition simplicity is maintained, but productivity is reduced
Solution Approach 1:
The system dynamically adapts the acquisition process by using motion prediction to determine which k-space portions to acquire next. Rather than following a fixed acquisition sequence, the system adjusts its acquisition strategy based on real-time motion phase predictions, optimizing the acquisition process to match the subject's actual motion patterns and improving productivity.
Solution Approach 2:
The system implements feedback by using acquired motion signals to update the motion phase mapping, which in turn improves subsequent motion predictions and guides further acquisition decisions. This closed-loop feedback mechanism allows the system to continuously optimize its acquisition strategy based on observed motion patterns, enhancing productivity while managing complexity through iterative improvement.
Data Source
AI summary
The invention provides for a magnetic resonance imaging system (100, 200) comprising a memory (148) for storing machine executable instructions (150) and pulse sequence commands (152). The pulse sequence commands are configured for acquiring a four dimensional magnetic resonance data set (162) from an imaging region of interest (109). The four dimensional magnetic resonance data set is at least divided into three dimensional data magnetic resonance data sets (400, 402, 404, 406, 408) indexed by a repetitive motion phase of the subject. The three dimensional data magnetic resonance data sets are further at least divided into and indexed by k-space portions (410, 412, 414, 416, 418, 420, 422, 424, 426, 428, 430, 432, 434, 436). The magnetic resonance imaging system further comprises a processor (144) for controlling the magnetic resonance imaging system. Execution of the machine executable instructions causes the processor during a first operational portion (310) to iteratively: receive (300) a motion signal (156) descriptive of the repetitive motion phase; acquire (302) an initial k-space portion using the pulse sequence commands, wherein the initial k-space portion is selected from the k-space portions; store (304) the motion signal and the initial k-space portion in a buffer (158) for each iteration of the first operational portion; at least partially construct (306) a motion phase mapping (160) between the motion signal and the repetitive motion phase; and continue (308) the first operational portion until the motion phase mapping is complete. Execution of the machine executable instructions causes the processor to assign (312) the initial k-space portion for each iteration of the first operational portion in the temporary buffer to the four dimensional magnetic resonance data set using the motion phase mapping. Execution of the machine executable instructions causes the processor during a second operational portion (332) to iteratively: receive (314) the motion signal; determine (316) a predicted next motion phase using the motion signal and the motion phase mapping; select (318) a subsequent k-space portion (154) from the k-space portions of the four dimensional magnetic resonance data set using the predicted next motion phase; acquire (320) the subsequent k-space portion using the pulse sequence commands; rereceive (322) the motion signal; determine (324) a current motion phase using the re-received motion signal and the motion phase mapping; assign (326) the subsequent k-space portion to the four dimensional magnetic resonance data set using the current motion phase; and repeat (328) the second operational portion until the k-space portions for each repetitive motion phase has been assigned.