MRI cT1 Standardization Using Field and Iron Correction
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Solution Overview
Problem
Existing MRI scanners face challenges in generating standardized T1 maps due to variations in magnetic field strength, iron concentration, and manufacturer-specific differences, limiting the application of cT1 measurements across different MRI systems.
Innovation Solution
A method involving dual MR image acquisition with a short breath-hold, followed by a field strength correction and iron correction, using Bloch simulation and VFA acquisition to generate a corrected wT1 map, which is then standardized to simulate cT1 images on a 3T scanner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If T1 maps are generated using different MRI scanners with varying magnetic field strengths and manufacturer-specific sequences, then cT1 measurements can be obtained, but the measurements lack standardization and reproducibility across different systems
Solution Approach 1:
The patent transforms T1 measurements into cT1 by applying parameter transformations that account for magnetic field strength differences and scanner-specific characteristics. This involves changing the measurement parameters through mathematical correction factors and lookup tables that standardize the output across different scanner conditions.
Solution Approach 2:
The patent introduces an intermediary standardized reference framework that mediates between different scanner measurements. This intermediary system uses reference phantoms and correction algorithms to translate diverse scanner outputs into a common standardized cT1 metric that can be compared across systems.
2Measurement precision
If parametric maps are extracted from acquired images with different contrast, then tissue characterization can be achieved, but the process becomes complicated due to noise, small number of datapoints, and confounding sources of MRI signal intensity
Solution Approach 1:
The patent performs preliminary actions by acquiring multiple images with different inversion times and contrast settings before extraction. This preliminary data collection ensures sufficient datapoints are available to overcome noise and confounding factors during the subsequent parametric map extraction process.
Solution Approach 2:
The patent employs feedback mechanisms in the extraction process by iteratively refining parametric map estimates using the acquired multi-contrast images. The system uses feedback from the image data to adjust and improve the accuracy of extracted parameters while accounting for noise and confounding signals.
3Manufacturing precision
If images are collected to freeze cardiac and respiratory motion for accurate T1 mapping, then alignment precision is improved, but the data acquisition becomes more challenging and time-consuming
Solution Approach 1:
The patent uses periodic action by acquiring images at specific periodic intervals during the cardiac and respiratory cycles. By timing the acquisitions to occur at consistent phases of these periodic motions, the method achieves good alignment without requiring complete motion freezing, thus reducing acquisition time.
Solution Approach 2:
The patent applies partial action by acquiring a limited set of images at specific inversion times rather than continuous imaging. This partial sampling approach provides sufficient data for accurate T1 mapping while minimizing the total acquisition time and reducing the burden of motion management.
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
Enables the generation of standardized cT1 maps on any MRI scanner, improving reproducibility and spatial resolution, and allowing for consistent treatment decisions based on cT1 thresholds.
Implementation Method 1
Magnetic Resonance (MR) Imaging (MRI) scanning technology can be used to acquire images of the human body that have a contrast that is dependent upon the nuclear magnetic resonance (NMR) relaxation properties of the imaging nucleus
Implementation Method 2
A method involving dual MR image acquisition with a short breath-hold, followed by a field strength correction and iron correction, using Bloch simulation and VFA acquisition to generate a corrected wT1 map
Data Source
AI summary
A method of analysing MRI images is described. The method comprising the steps of: acquiring a first medical MR image, and a second medical MR image, of a subject at the same nominal magnetic field strength; analysing the first and second MR images to determine a wT1 map from the first and second images; applying a field strength correction based on modification of the nominal field strength used for the first and second MR image acquisitions, and an iron correction to correct for differences in the iron concentration from a normal level using a T2*map, to the wT1 map from the first and second images to generate a corrected wT1 map; using the corrected wT1 map to determine simulated signals for a subject with normal iron levels, and fitting the simulated signals to a standard cT1 to determine a standard cT1 image for the subject.