MRI Parametric Mapping Confidence Map Error Exclusion
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Solution Overview
Problem
Magnetic resonance imaging (MRI) parametric mapping is negatively affected by image artifacts and noise, leading to systematic errors in parameter maps, making it difficult to obtain reliable measurements in certain areas.
Innovation Solution
A method is introduced to produce confidence maps using MRI systems, which identify regions affected by error sources, allowing for the exclusion or masking of these areas in parametric maps, thereby reducing errors and providing more reliable measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parametric mapping is performed using standard MRI acquisition methods, then comprehensive parameter maps can be obtained, but systematic errors and artifacts reduce measurement reliability in certain regions
Solution Approach 1:
The patent segments the parameter map into reliable and unreliable regions by generating a confidence map that identifies error-prone areas. This segmentation allows selective use of data based on local reliability metrics, improving overall measurement precision while maintaining awareness of unreliable regions through spatial division of the imaging domain.
Solution Approach 2:
The confidence map serves as an intermediary between the raw parametric mapping data and the final interpretation. It mediates by providing reliability information that guides whether measurements in specific regions should be trusted, effectively acting as a quality control layer that translates complex error patterns into actionable reliability indicators.
2Quantity of substance
If measurements are taken from all regions in the field-of-view, then complete parameter coverage is achieved, but error-prone regions contaminate the overall parameter map quality
Solution Approach 1:
The patent applies local quality by allowing different regions of the parameter map to have different reliability characteristics. Instead of treating the entire field-of-view uniformly, the confidence map enables region-specific quality assessment, where some areas contribute high-quality data while others are identified as containing systematic errors or artifacts.
Solution Approach 2:
The patent changes the parameter representation by adding a confidence or reliability dimension to the parameter map. This transforms the traditional single-parameter mapping into a multi-parameter output that includes both the measured parameter values and their associated reliability metrics, enabling quality-based filtering of results.
3Reliability
If confidence maps are generated and used to exclude error-prone regions, then measurement reliability improves, but additional processing steps increase system complexity
Solution Approach 1:
The confidence map generation process is self-service in that it uses the same MRI acquisition data and signal models already employed for parametric mapping. The system leverages its own existing computational infrastructure and measured signals to generate reliability information, avoiding the need for separate dedicated hardware or entirely new processing pipelines.
Solution Approach 2:
The confidence map serves multiple functions: it identifies artifacts, quantifies reliability, guides measurement selection, and can inform future acquisition strategies. This multi-functionality justifies the additional processing complexity by providing a single computational product that addresses multiple quality control needs simultaneously.
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
The use of confidence maps enables the identification and exclusion of error-prone regions, resulting in more accurate parametric maps by avoiding unreliable measurements and improving the robustness of MRI-based biomarker quantification.
Implementation Method 1
MRI uses the nuclear magnetic resonance phenomenon to produce images. When a substance, such as human tissue, is subjected to a uniform magnetic field, such as the so-called main magnetic field, B0, of an MRI system, the individual magnetic moments of the nuclei in the tissue attempt to align with this B0 field, but precess about it in random order at their characteristic Larmor frequency, ω.
Implementation Method 2
the individual magnetic moments of the nuclei in the tissue attempt to align with this B0 field, but precess about it in random order at their characteristic Larmor frequency, ω
Implementation Method 3
If the substance, or tissue, is subjected to a so-called excitation electromagnetic field, B1, that has a frequency near the Larmor frequency, the net aligned magnetic moment, referred to as longitudinal magnetization, may be rotated, or 'tipped,' into the transverse plane to produce a net transverse magnetic moment, referred to as transverse magnetization.
Data Source
AI summary
A method for producing parametric maps using a magnetic resonance imaging (MRI) system is provided. The MRI system is used to acquire k-space data from a field-of-view. A series of images is reconstructed from the acquired k-space data, and a confidence map is produced using the k-space data. The confidence map depicts regions in the field-of-view that are affected by error sources. A parametric map is produced using the reconstructed series of images and the produced confidence map. Values in the parametric map associated with regions in the field-of-view depicted in the confidence map as being affected by error sources are not computed, thereby reducing errors in the parametric map.