MRI Blood Flow Analysis Correcting Signal Non-Linearity
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Solution Overview
Problem
Magnetic Resonance Imaging (MRI) struggles to accurately measure blood flow volume due to non-linearity between MR signal values and contrast medium concentration, especially in tissues with air, leading to discrepancies with other imaging methods like X-ray computed tomography.
Innovation Solution
An image analysis device and method that calculates the concentration of contrast medium per unit volume including air by using a coefficient based on relaxation rates and times before and after contrast medium administration, correcting for non-linearity and allowing for accurate blood flow volume measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRI perfusion analysis is used to calculate blood flow volume, then the measurement process is simple, but the measurement precision is low due to non-linearity between MR signal values and contrast medium concentration
Solution Approach 1:
The patent transforms the non-linear relationship between MR signal values and contrast medium concentration into a linear relationship by applying mathematical transformations (logarithmic transformation and differential operations). This allows the use of simple linear regression analysis while achieving accurate blood flow volume measurements, thus improving measurement precision without significantly increasing analysis complexity
Solution Approach 2:
The patent replaces the conventional direct calculation method with a mathematical model-based approach that uses transformed parameters. By substituting the direct non-linear measurement with a transformed linear model, the patent achieves higher precision while maintaining computational simplicity
2Measurement precision
If MRI measures blood flow volume in tissues containing air, then the measurement covers the entire pixel volume, but the measurement precision is low because the calculated concentration does not account for air regions
Solution Approach 1:
The patent introduces a threshold value as an intermediary to distinguish between tissue regions and air regions. By comparing pixel values against this threshold, the system can identify and separate tissue-containing pixels from air-containing pixels, enabling accurate blood flow measurement in heterogeneous tissues while accounting for the presence of air regions
Solution Approach 2:
The patent segments the image data into different regions (tissue regions and air regions) based on pixel value thresholds. This segmentation allows the analysis to be performed separately on tissue regions, excluding air regions from the blood flow calculation, thereby improving measurement accuracy in tissues containing air
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 accurate calculation of local blood flow volume per predetermined volume including air, aligning with measurements from other imaging methods and correcting for signal intensity and concentration non-linearity, thus improving MRI's accuracy in perfusion analysis.
Implementation Method 1
MRI is an imaging method which magnetically excites nuclear spin of an object (a patient) placed in a static magnetic field with an RF pulse having the Larmor frequency and reconstructs an image on the basis of MR signals generated due to the excitation
Implementation Method 2
R1 value indicative of relaxation rate of contrast medium is an inverse number of longitudinal relaxation time. Thus, an R1 value of each pixel in MRI is not an average value of the corresponding pixel but a value reflecting the R1 value of the tissue region in the corresponding pixel
Data Source
AI summary
In one embodiment, an image analysis device (65) includes an acquisition unit (66) and an analysis unit (67). The acquisition unit acquires image data of a plurality of images of an imaging region of an object respectively imaged by magnetic resonance imaging before and after administration of contrast medium. The analysis unit calculates an estimated value of concentration of contrast medium per unit volume including air region by using a coefficient based on the image data before administration of contrast medium, in accordance with the image data of a plurality of images and a value related to relaxation rate or relaxation time before and after administration of contrast medium.