Modified Pressure-Drop Model for Arterial Stenosis Prediction
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Solution Overview
Problem
Current methods for predicting post-stenting hemodynamic metrics in arterial stenosis require modification of the pre-stent anatomical model to generate a post-stent model, which is complex and assumes various parameters, and do not directly compute the effect of a stent on blood flow and pressure.
Innovation Solution
A method that uses a modified pressure-drop model to directly compute post-stenting hemodynamic metrics without the need for an intermediate post-stent anatomical model, by simulating blood flow and pressure in the pre-stenting model and modifying the pressure-drop model to represent the effect of stenting, allowing for the prediction of fractional flow reserve (FFR) and other metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a modified pressure-drop model is used to directly compute post-stenting hemodynamic metrics, then the prediction accuracy and computational efficiency are improved, but the model complexity increases
Solution Approach 1:
The patent modifies the pressure-drop model by changing key parameters to account for stent effects. Specifically, it adjusts the pressure-drop calculation parameters to simulate the hemodynamic changes caused by stent placement, allowing direct computation of post-stenting metrics without full anatomical model reconstruction. This parameter modification approach maintains computational efficiency while improving prediction accuracy.
2Manufacturing precision
If an intermediate post-stent anatomical model is generated, then the anatomical accuracy is improved, but the computational time and process complexity increase
Solution Approach 1:
The patent extracts only the essential hemodynamic information needed for post-stenting prediction from the complex anatomical model generation process. Instead of generating a complete post-stent anatomical model, it extracts and utilizes only the pressure-drop characteristics and hemodynamic metrics, bypassing the time-consuming intermediate model generation step while maintaining prediction accuracy.
Solution Approach 2:
The patent performs preliminary modification of the pressure-drop model parameters before actual hemodynamic simulation. By pre-adjusting the model parameters to account for stent effects, it eliminates the need for intermediate anatomical model generation, directly computing post-stenting metrics from the pre-stenting model with modified parameters.
3Adaptability or versatility
If virtual stenting is performed on multiple stenosis regions, then the treatment planning comprehensiveness is improved, but the computational burden increases
Solution Approach 1:
The patent segments the treatment planning process by applying the modified pressure-drop model independently to each stenosis region. This segmentation allows virtual stenting to be performed on multiple regions without requiring a complete re-computation for each scenario, as the modified model can be efficiently applied to each segment separately, reducing overall computational burden while maintaining comprehensive treatment planning capability.
Data Source
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AI summary
A method and system for prediction of post-stenting hemodynamic metrics for treatment planning of arterial stenosis is disclosed. A pre-stenting patient-specific anatomical model of the coronary arteries is extracted from medical image data of a patient Blood flow is simulated in the pre-stenting patient-specific anatomical model of the coronary arteries with a modified pressure-drop model that simulates an effect of stenting on a target stenosis region used to compute a pressure drop over the target stenosis region. Parameter values for the modified pressure-drop model are set without modifying the pre-stenting patient-specific anatomical model of the coronary arteries. A predicted post-stenting hemodynamic metric for the target stenosis region, such as fractional flow reserve (FFR), is calculated based on the pressure-drop over the target stenosis region computed using the modified pressure-drop model.