Hemodynamic Spectroscopy With Vascular Compartment Modeling
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Solution Overview
Problem
Existing hemodynamic models for brain disorders face challenges in achieving a balance between complexity and the number of free parameters, often oversimplifying cerebral hemodynamics and oxygen transport processes, while previous approaches introduce numerous approximations to describe complex microvascular networks.
Innovation Solution
A method involving coherent hemodynamic oscillations induced by periodic physiological maneuvers or spontaneous oscillations, combined with a multiple vascular compartment hemodynamic model, allows for the analysis of hemoglobin concentration and oxygenation data using near-infrared spectroscopy or fMRI, employing a frequency-resolved measurement scheme to infer physiological characteristics without detailed architectural assumptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If previous approaches use simplified hemodynamic models, then the number of free parameters is reduced, but the model oversimplifies cerebral hemodynamics and oxygen transport processes
Solution Approach 1:
The patent segments the cerebral vasculature into multiple vascular compartments (arterial, capillary, venous) to capture the complexity of hemodynamic processes. This compartmentalization allows the model to represent different physiological processes in each compartment while maintaining a manageable number of parameters through shared constraints and relationships between compartments.
Solution Approach 2:
The patent transforms the complex vascular network description from spatial architectural parameters to temporal hemodynamic parameters (flow rates, transit times, oxygen extraction fractions). This parameter transformation reduces the number of independent parameters needed while preserving the essential physiological behavior of the system.
2Reliability
If previous approaches describe complex microvascular networks with detailed architectural assumptions, then model accuracy improves, but the number of free parameters increases significantly
Solution Approach 1:
The patent extracts the essential hemodynamic and oxygen transport processes from the complex microvascular architecture, separating the functional behavior from the detailed structural description. By focusing on measurable physiological parameters rather than anatomical details, the model achieves accuracy without requiring numerous architectural parameters.
Solution Approach 2:
The patent creates a universal hemodynamic model that can describe multiple vascular compartments and physiological processes using a unified framework. The same basic equations and parameter types apply across different compartments, reducing the total number of parameters needed compared to separate detailed models for each vascular region.
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
This approach effectively predicts localized cerebral autoregulation and cerebrovascular reactivity, providing a compromise between model complexity and parameter count, enhancing diagnostic capabilities for brain disorders.
Implementation Method 1
Dynamic data on the concentrations of oxy-hemoglobin and deoxy-hemoglobin in tissue are collected (e.g., with near-infrared spectroscopy)
Data Source
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AI summary
A method for inferring characteristics of a physiological system includes measuring one or more physiological signals in the physiological system and inferring characteristics of the physiological system from the one or more measured physiological signals using a multiple vascular compartment hemodynamic model, the multiple vascular compartment hemodynamic model defining a relationship between the one or more measured physiological signals and the characteristics of the physiological system. When the one or more measured physiological signals include coherent oscillations at a plurality of frequencies, the method is termed coherent hemodynamics spectroscopy. The multiple vascular compartment hemodynamic model is based on an average time spent by blood in one or more of said vascular compartments and a rate constant of oxygen diffusion.