Diffusion Dictionary Imaging for Inflammation Detection
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Solution Overview
Problem
Current imaging techniques for neuroinflammation, such as PET, are limited by the need for radioactive tracers and complex, expensive processes, while diffusion MRI struggles to accurately image inflammation due to challenges in existing techniques.
Innovation Solution
The development of Diffusion Dictionary Imaging (DDI) systems and methods using a DDI computing device that processes magnetic resonance signals to reconstruct diffusion MRI images, employing a comprehensive diffusion dictionary and weighted apparent diffusion coefficient to capture microstructure hallmarks associated with immune cell activation, allowing for safe and accurate inflammation imaging without radioactive tracers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If PET imaging is used for inflammation imaging, then measurement precision is improved, but device complexity and cost increase due to radioactive tracers and complicated imaging process
Solution Approach 1:
The patent creates a computational copy of the complex PET imaging process through DDI algorithms that process standard diffusion MRI data. Instead of requiring actual radioactive tracers and complex PET hardware, the system uses computational models (dictionaries of diffusion patterns) to replicate inflammation detection capabilities from simpler, more accessible MRI sequences, thereby maintaining measurement precision while reducing device complexity and cost
2Measurement precision
If PET imaging is used for inflammation imaging, then measurement precision is improved, but loss of substance increases due to radioactive tracers
Solution Approach 1:
The patent enables the imaging system to serve itself by using endogenous water molecules already present in the body as the contrast source, eliminating the need for exogenous radioactive tracers. The diffusion MRI sequences naturally detect water diffusion patterns, and the DDI algorithms process these endogenous signals to provide inflammation imaging, thereby maintaining measurement precision while completely eliminating radioactive substance usage
Solution Approach 2:
The system creates a computational model that copies the inflammation detection capability of PET imaging using only endogenous water diffusion signals. The diffusion dictionary contains pre-computed patterns of water diffusion in inflamed versus normal tissue, allowing the system to identify inflammation without any radioactive tracers, thus eliminating substance loss while preserving diagnostic accuracy
3Ease of operation
If standard diffusion MRI is used for inflammation imaging, then ease of operation is improved, but measurement precision deteriorates due to inability to accurately capture immune cell activation
Solution Approach 1:
The patent transforms standard diffusion MRI data by applying specific parameter changes in the computational domain. The DDI algorithm processes the raw diffusion data through a diffusion dictionary that encodes specific diffusion patterns associated with immune cell activation. By changing the parameter space from raw diffusion coefficients to diffusion pattern matching against inflammatory signatures, the system enhances measurement precision while maintaining ease of operation with standard MRI sequences
4Measurement precision
If PET imaging is used for inflammation imaging, then measurement precision is improved, but ease of operation worsens due to limited application to subset of patients
Solution Approach 1:
The patent creates a accessible copy of PET imaging capability using standard diffusion MRI sequences that are widely available on clinical MRI scanners. The DDI algorithm processes data from these common sequences to provide inflammation imaging, copying the diagnostic value of PET while eliminating the need for specialized equipment and radioactive tracers, thereby dramatically improving patient accessibility while maintaining measurement precision
Solution Approach 2:
The system replaces expensive, complex PET imaging with a cheaper, more accessible alternative using standard diffusion MRI sequences. The computational DDI algorithm acts as a low-cost processing layer that extracts inflammation information from routinely acquired MRI data, making the technology accessible to all patients rather than limiting it to a subset who can undergo PET imaging
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
DDI provides low-cost, accurate, and safe inflammation imaging for various conditions, suitable for patients who cannot tolerate radioactive tracers, by extracting inflammatory features from endogenous contrast, enhancing computation speed and specificity to immune cell activation.
Implementation Method 1
diffusion MRI utilizes endogenous contrast from water molecules abundant in the human body
Implementation Method 2
receive, from at least one user device, one or more magnetic resonance (MR) signals
Data Source
AI summary
A computing device for diffusion dictionary imaging (DDI) of microstructure and inflammation of a patient is provided. The DDI computing device is connected to other computing devices, such as a magnetic resonance imaging (MRI) scanner. The DDI computing device receives magnetic resonance (MR) signals from the MRI scanner. Once received, the DDI computing device records the one or more MR signals to a memory device. The DDI computing device computationally processes the one or more MR signals to reconstruct a diffusion MRI image using diffusion dictionary data. The MR signals include values that are used as input to algorithms of the DDI data to reconstruct the diffusion MRI image. A database is used to store DDI data, artificial intelligence (AI) data, diffusion dictionary data, and MR data.