MRI Scan Parameter Optimization via Dynamic TR and Flip Angle Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for calculating quantitative values in MRI imaging, such as those described in Patent Documents 1 and 2, face challenges in accuracy due to fixed scan parameters and lack of user flexibility in adjusting imaging time, particularly when prioritizing either short imaging time or accuracy.
Innovation Solution
An MRI system that determines optimal scan parameter sets using indices related to imaging time, including repetition time (TR), flip angle, and error estimation, allowing users to specify imaging conditions and prioritize either shortening imaging time or improving accuracy, thereby increasing user freedom and calculation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If scan parameters are fixed in existing quantitative value calculation methods, then the calculation process is simple, but the accuracy of quantitative value calculation deteriorates
Solution Approach 1:
The patent makes the scan parameter set dynamic by allowing automatic generation and adjustment based on imaging conditions and target information. The system can adaptively determine optimal scan parameters (TR, TE, flip angle, etc.) rather than using fixed predetermined values, thereby improving calculation accuracy while maintaining operational simplicity through automated processes.
Solution Approach 2:
The patent changes multiple scan parameters simultaneously (TR, TE, flip angle, phase increment) rather than fixing them. By varying these parameters according to imaging conditions and using error estimation to guide optimization, the system achieves higher quantitative value calculation accuracy without significantly increasing user burden.
2Loss of time
If users want to adjust imaging time by changing TR, then imaging time can be controlled, but it becomes necessary to generate the scan parameter set again and extract optimal candidates, increasing operation complexity
Solution Approach 1:
The patent implements feedback mechanisms where the system estimates errors in quantitative value calculations and uses this information to automatically adjust scan parameters. When users specify imaging time requirements, the system iteratively optimizes the scan parameter set based on error estimation results, providing both time control and operational convenience through automated feedback-driven optimization.
Solution Approach 2:
The system performs self-optimization of scan parameters by automatically generating and evaluating multiple candidate sets. The error estimation function enables the system to self-correct and select optimal parameters without requiring users to manually extract or compare multiple candidates, thereby maintaining ease of operation while achieving precise imaging time control.
3Loss of time
If only TR is adjusted to be short in the scan parameter set, then imaging time is reduced, but accuracy is not sufficiently guaranteed
Solution Approach 1:
Instead of simply shortening TR, the patent simultaneously optimizes multiple parameters including TR, TE, flip angle, and phase increment. The error estimation function guides the selection of parameter combinations that achieve both reduced imaging time and maintained accuracy by finding the optimal balance among all parameters rather than relying on TR alone.
Solution Approach 2:
The system dynamically adjusts the combination of scan parameters based on imaging conditions and error estimation results. When imaging time needs to be reduced, the system doesn't just decrease TR but adaptively reoptimizes the entire parameter set, allowing other parameters to compensate and maintain accuracy while achieving shorter imaging time.
4Measurement precision
If multiple scan parameter sets with different TR and flip angle combinations are generated, then accuracy can be improved, but the user cannot easily adjust the scan parameter
Solution Approach 1:
The patent uses error estimation as feedback to guide the presentation of scan parameter sets to users. Instead of requiring users to evaluate multiple complex parameter combinations, the system ranks them by estimated accuracy and presents the optimal set first. This feedback mechanism maintains high accuracy while simplifying user interaction by automatically identifying and presenting the best options.
Solution Approach 2:
The system performs self-evaluation of multiple scan parameter sets using error estimation and automatically selects the optimal one based on user requirements. This self-service approach eliminates the need for users to manually analyze multiple parameter combinations, thereby maintaining high accuracy through comprehensive evaluation while preserving ease of operation through automated selection.
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
Facilitates convenient and accurate setting of scan parameters, enhancing user convenience and the accuracy of quantitative value calculations by generating optimal parameter sets based on user-defined conditions.
Implementation Method 1
A magnetic resonance imaging (MRI) device is a medical image diagnostic device that mainly uses a nuclear magnetic resonance phenomenon of protons
Data Source
AI summary
An MRI device for executing an imaging operation at least three times or more with a different combination of at least a repetition time and a flip angle in the same imaging sequence, includes: a receiving unit which receives information specifying an imaging target and a constraint condition relating to an imaging time or quantitative value accuracy; and a scan parameter set generation unit which calculates at least three or more scan parameter sets having a different combination of at least the repetition time and the flip angle on the basis of the constraint condition. The MRI device uses three or more scan parameter sets generated by the optimal scan parameter set generation unit and calculates quantitative values (T1, T2,and the like) of the imaging target from a plurality of images obtained by the imaging operation.