Synthetic MRI Sequences for Enhanced Tissue Contrast
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Solution Overview
Problem
Conventional MRI techniques face challenges in discerning the contrast between healthy and diseased tissues, particularly when small changes in tissue properties such as T1, T2, and D* are insufficient to produce useful contrast, leading to undiagnosed abnormalities.
Innovation Solution
The use of synthetic MRI sequences, including MASDIR and MASDEA images, and synthetic T1-, T2-, T2*- and D*-bipolar filter images, which enhance image contrast by manipulating and combining inversion recovery and echo acquisition sequences to target specific tissue properties, allowing for the creation of synergistic contrast without requiring additional data acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRI sequences are used, then the imaging process is simple and fast, but the contrast between healthy and diseased tissue is insufficient to detect subtle abnormalities
Solution Approach 1:
The patent segments the imaging process into two distinct phases: (1) data acquisition using conventional MRI sequences, and (2) synthetic image generation through mathematical processing. This segmentation allows the complex contrast enhancement to be achieved without complicating the actual imaging sequence, as the synthesis occurs in post-processing using bipolar filters applied to the acquired data.
Solution Approach 2:
The patent introduces bipolar filters as an intermediary mathematical tool that processes the raw MRI data to generate synthetic images with enhanced contrast. These filters act as mediators between the conventional acquisition sequences and the final diagnostic images, enabling subtle tissue property changes to be visualized without modifying the original imaging hardware or sequences.
2Adaptability or versatility
If multiple imaging sequences are acquired to target different tissue properties, then comprehensive tissue characterization is achieved, but the scanning time increases
Solution Approach 1:
The patent makes the acquired MRI data universal by processing it through multiple different bipolar filter configurations in post-processing. A single data acquisition can generate multiple synthetic images targeting different tissue properties (T1, T2, diffusion, etc.), eliminating the need to acquire separate sequences for each tissue characteristic and thus reducing scan time while maintaining versatility.
Solution Approach 2:
The patent performs preliminary data acquisition using standard sequences that capture comprehensive tissue information, then applies various bipolar filter syntheses afterward. This preliminary action ensures all necessary data is captured in one scan, and the adaptive targeting of specific tissue properties is achieved through subsequent mathematical processing rather than additional scanning.
3Measurement precision
If the middle domain width is narrowed to improve contrast for specific T1 values, then contrast precision for target tissue is improved, but the range of detectable T1 values is reduced
Solution Approach 1:
The patent makes the middle domain width dynamic rather than fixed. Different bipolar filter syntheses can be applied with varying middle domain widths tailored to specific diagnostic needs. This dynamic adjustment allows optimization of contrast precision for particular tissue types while maintaining the ability to detect a broad range of T1 values across different imaging scenarios.
Solution Approach 2:
The patent utilizes parameter changes in the bipolar filter design, specifically adjusting the middle domain width parameter based on the target tissue properties. By changing this parameter, the system can optimize contrast precision for specific T1 ranges while still providing the capability to investigate broader T1 ranges when needed, balancing precision and versatility.
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
These sequences provide an order of magnitude increase in contrast, enabling the detection of previously undetectable changes in tissue properties, thereby improving the diagnosis of subtle diseases and abnormalities.
Implementation Method 1
synthesis of divided subtracted inversion recovery, and divided reverse subtracted inversion recovery images
Implementation Method 2
synthesis of multiplied added subtracted and/or divided echo acquisition (MASDEA) images
Data Source
AI summary
Methods include generating ultra-high contrast magnetic resonance images using synthetic pulse sequences. The techniques employ multiplied, added, subtracted and/or divided (MASDIR) inversion recovery sequences, particularly divided subtracted inversion recovery (dSIR) and divided reverse subtracted inversion recovery (drSIR) sequences. These sequences allow synthesis of narrower middle domain images from wider domain acquisitions and creation of synthetic images from tissue property maps. The methods produce increased image contrast that can reveal subtle abnormalities not visible on conventional MRI. Key aspects include using T1-bipolar filters to target specific tissues and small changes in T1, combining different tissue property filters for synergistic contrast, and quantitative T1 mapping. Clinical applications are described for detecting disease in normal-appearing tissues. The techniques enable order-of-magnitude increases in contrast compared to conventional sequences, allowing visualization of previously imperceptible changes in relaxation times.