Cardiac-Synchronized Diffusion MRI for Glymphatic CSF Flow Mapping
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Solution Overview
Problem
Current methods for measuring brain glymphatic system circulation are invasive, inaccurate, and limited in their ability to provide microscopic information, particularly regarding intercellular matrix volume and fluid flow rates, and are not applicable to healthy populations.
Innovation Solution
A non-invasive diffusion magnetic resonance method using dynamic diffusion tensor imaging (DTI) combined with finger pulse oximetry to measure cardiac-cycle-dependent glymphatic system circulation by analyzing axial, radial, and mean diffusivity coefficients in brain MRI images, synchronized with heart rate fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive tracer-based optical imaging or parenchymal tracer injection is used to measure glymphatic circulation, then measurement precision may be improved, but the method causes local inflammation, disrupts AQP4 polarity, and interferes with the glymphatic system circulation
Solution Approach 1:
The patent uses diffusion MRI as an intermediary non-invasive measurement technique that indirectly measures glymphatic circulation without requiring direct tracer injection or electrode implantation into the brain parenchyma, thereby avoiding local inflammation and AQP4 polarity disruption while still obtaining circulation data
Solution Approach 2:
The patent replaces the mechanical invasive measurement system (microelectrodes, tracer injection) with a non-invasive magnetic resonance imaging system that uses diffusion-weighted imaging to measure glymphatic circulation through physiological CSF flow and diffusion processes
2Ease of operation
If dynamic contrast-enhanced MRI is used to observe macroscopic inflow and outflow velocity, then the measurement can be performed non-invasively, but it cannot reflect microscopic information such as intercellular matrix volume and flow rate
Solution Approach 1:
The patent changes the measurement parameters by using diffusion-weighted imaging with specific b-values and gradient directions to sensitively detect microscopic CSF flow and diffusion characteristics in the perivascular spaces, enabling non-invasive measurement of both macroscopic and microscopic glymphatic circulation parameters
Solution Approach 2:
The patent adds the dimension of diffusion sensitivity to the MRI measurement by applying diffusion gradients in multiple directions, allowing simultaneous assessment of CSF flow velocity, intercellular matrix volume, and microscopic circulation patterns that were previously inaccessible
3Ease of operation
If traditional light imaging is used to image the brain surface, then the method is non-invasive, but the imaging range is limited to the surface of the cortex
Solution Approach 1:
The patent replaces traditional optical imaging with magnetic resonance imaging, which uses electromagnetic fields at MRI frequencies to penetrate the skull and image deep brain structures, thereby expanding the imaging range from the cortical surface to the entire brain volume while maintaining non-invasive measurement
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
Enables non-invasive, precise measurement of cerebrospinal fluid flow rates and directional characteristics in both large and small perivascular spaces, providing detailed insights into cardiac-dependent glymphatic system dynamics.
Implementation Method 1
Diffusion MRI, as a non-invasive means of measuring the diffusion of water molecules
Implementation Method 2
magnetic resonance imaging (MRI) system
Data Source
AI summary
The present invention discloses a diffusion magnetic resonance (MR) method for measuring arterial pulsation dependence of perivascular cerebrospinal fluid flow in glymphatic system: DTI acquisition: Brain MRI images were acquired using dynamic diffusion tensor imaging (DTI); Cardiac signal synchronization: Simultaneously collect heart rate fluctuation time-series signals; Peak coordinate determination: Identify the peak timing of cardiac pulsation signals from the time-series data; Image realignment: Reorganize brain MR images according to their temporal positions within the cardiac cycle; Temporal interpolation: Perform uniform time-sampling reconstruction to generate equidistant diffusion MRI datasets across the cardiac cycle; Parameter calculation: Compute axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) at each voxel level; Mask-based analysis: Generate characteristic curves of AD/RD/MD and spin density(S) dynamics using region-specific masks in individual space. This method enables non-invasive measurement of: (1) Cerebrospinal fluid (CSF) flow velocity/direction in large perivascular spaces during heartbeats; (2) Microvascular perivascular CSF dynamics through diffusion parameter analysis.