MR Attenuation Map Generation Using Phase and Magnitude Classification
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Solution Overview
Problem
Current methods for generating attenuation or density maps in magnetic resonance (MR) systems, particularly for radiation therapy planning, face challenges due to the lack of direct correlation between MR signal intensity and radiation attenuation or tissue density, leading to inaccuracies and inefficiencies, especially in patients with abnormal anatomy or multiple tissue types within a single pixel or voxel.
Innovation Solution
The development of a method that utilizes MR signal phase and magnitude to classify tissue types and generate tissue-specific or material-specific attenuation or density values for each pixel or voxel, employing ultra-short TE acquisition sequences and phase unwrapping to create accurate and quantitative maps, which are then combined into patient-specific attenuation or density maps for improved accuracy and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If segmentation techniques are used to differentiate tissues from MR images, then tissue classification is achieved, but accuracy deteriorates for patients with abnormal anatomy and multiple tissue types within a single voxel
Solution Approach 1:
The patent applies segmentation by dividing each voxel into multiple tissue compartments (e.g., soft tissue, bone, air) with individual attenuation values. Instead of assigning a single attenuation value to the entire voxel, the method segments the voxel content and calculates a composite attenuation value based on the proportion of each tissue type, thereby improving accuracy for complex anatomical structures
Solution Approach 2:
The patent implements local quality by assigning different attenuation values to different tissue types within the same voxel. Each tissue compartment (soft tissue, bone, air) is assigned its specific attenuation value based on its local properties, allowing the system to account for heterogeneity within voxels and improve dosimetry accuracy for patients with abnormal anatomy
2Measurement precision
If manual review and adjustment steps are incorporated into segmentation techniques, then classification accuracy is improved, but patient throughput deteriorates
Solution Approach 1:
The patent applies self-service by implementing an automated iterative process that performs segmentation, evaluation, and refinement without manual intervention. The system automatically adjusts segmentation parameters and re-runs the classification process multiple times, allowing the algorithm to self-correct and improve accuracy while maintaining high patient throughput
Solution Approach 2:
The patent implements preliminary action by performing multiple iterations of segmentation and evaluation before final classification. The system pre-processes the MR images with initial segmentation parameters, evaluates the results, and automatically refines the segmentation in subsequent iterations, ensuring high accuracy is achieved before patient review
3Measurement precision
If CT is used for attenuation correction in PET, then accurate attenuation values are obtained, but the system cannot be integrated with MR-based imaging workflows
Solution Approach 1:
The patent applies mechanics substitution by replacing the CT-based attenuation correction system with an MR-based system. Instead of using X-ray attenuation measurements from CT, the method uses MR signal characteristics (phase and magnitude) to derive attenuation values, thereby integrating attenuation correction into the MR imaging workflow while maintaining accuracy
Solution Approach 2:
The patent implements parameter changes by transforming MR signal parameters (phase and magnitude) into attenuation values. The method changes the physical parameters used for attenuation measurement from X-ray based (CT) to MR signal based, allowing the system to generate attenuation maps directly from MR images through mathematical transformation of signal characteristics
Data Source
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AI summary
A magnetic resonance (MR) system (10) generates an attenuation or density map. The system (10) includes a MR scanner (48) defining an examination volume (16) and at least one processor (54). The at least one processor (54) is programmed to control the MR scanner (48) to apply imaging sequences to the examination volume (16). In response to the imaging sequences, MR data sets of the examination volume (16) are received and analyzed to identify different tissue and/or material types found in pixels or voxels of the attenuation or density map. One or more tissue-specific and/or material-specific attenuation or density values are assigned to each pixel or voxel of the attenuation or density map based on the tissue and/or material type(s) identified as being in each pixel or voxel during the analysis of the MR data sets. In one embodimnt, the tissue and/or material types are identified on the basis of a time series of MR phase images.