Brain MRS-MRI Co-Registration for Metabolite Mapping
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Solution Overview
Problem
Existing magnetic resonance spectroscopy (MRS) data analysis is challenging due to proprietary data formats, difficulty in comparing results between scans, and the need for clinically meaningful bounds that consider data acquisition parameters and patient variables, making it hard to analyze brain metabolites effectively.
Innovation Solution
An analysis system that processes MRS data, co-registers it with MRI images, and provides graphical representations with adjustable color mapping, using thresholds and ranges based on patient age, echo time, and field strength to facilitate accurate diagnosis and disease monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proprietary data formats are used for MRS data storage and analysis, then data can be stored and processed, but data accessibility and ease of analysis are reduced
Solution Approach 1:
The patent employs an intermediary system that translates proprietary MRS data formats into standardized, accessible formats. This intermediary layer maintains the reliability of original data storage while enabling broad accessibility and analysis through format conversion and standardization protocols.
2Measurement precision
If detailed spectroscopy data processing is performed to distinguish metabolites, then diagnostic precision is improved, but analysis complexity and time increase
Solution Approach 1:
The patent segments the complex spectroscopy data analysis into distinct processing stages: initial data acquisition, preprocessing filtering, metabolite peak identification, quantification, and diagnostic interpretation. This segmentation reduces analysis complexity by breaking down the overall task into manageable steps while maintaining diagnostic precision through systematic processing of each stage.
Solution Approach 2:
The patent performs preliminary actions by pre-processing MRS data through filtering, baseline correction, and noise reduction before full analysis. Reference spectra and metabolite databases are pre-established to facilitate faster, more accurate metabolite identification during actual diagnostic sessions, thereby reducing real-time analysis complexity.
3Measurement precision
If MRS data is co-registered with MRI images for spatial correlation, then diagnostic accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent merges MRS spectroscopy data with MRI imaging data through co-registration processes that align the two datasets in spatial coordinates. This merging creates a unified diagnostic view where metabolic information from MRS is overlaid on anatomical structures from MRI, improving diagnostic accuracy while the system manages the processing complexity through integrated software protocols.
4Reliability
If multiple parameters (patient age, echo time, field strength) are considered for establishing metabolite ranges, then clinical relevance is improved, but data analysis complexity increases
Solution Approach 1:
The patent systematically varies and evaluates multiple parameters including patient age, echo time, and field strength to establish clinically relevant metabolite concentration ranges. By analyzing how metabolite levels change with these parameters and establishing normalized reference ranges, the system improves clinical relevance while managing analysis complexity through structured parameter evaluation protocols.
Data Source
AI summary
In part, the disclosure relates to an analysis system in communication with one or more sources of brain region or brain tissue-specific spectroscopy data; and computer-executable logic, encoded in memory of the analysis system, for interpreting brain region or brain tissue-specific spectroscopy data, where the computer-executable logic is configured for execution of: processing the brain region or brain tissue-specific spectroscopy data to obtain one or more spectroscopic graphical representations of the brain region or brain tissue-specific spectroscopy data; co-registering such representations with regions of interest in imaging data obtained relative thereto, where the imaging data is obtained simultaneously with the spectroscopy data; and displaying a first visual representation of co-registered brain region or brain tissue-specific spectroscopy data and imaging data. The visual representation may include one or more views of brain tissue and a spatially correlated map of changes in brain region or tissue-specific spectroscopy data.