Blood Vessel Cross-Section Modeling for Pressure Difference Accuracy
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Solution Overview
Problem
Current methods for calculating blood flow pressure difference in coronary arteries are inaccurate due to neglecting plaque size, length, angle, and shape, leading to significant errors in blood vessel cross-section modeling.
Innovation Solution
A method that establishes a blood vessel cross-section function by generating spatial models at different positions and times, using image data to create cross-section models and functions, and calculating pressure differences based on these models, incorporating plaque characteristics and regional information for correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional blood vessel cross-section modeling methods are used, then the modeling process is simple, but the accuracy of blood flow pressure difference calculation is poor due to neglecting plaque characteristics
Solution Approach 1:
The patent segments the blood vessel modeling process into multiple components: obtaining image data, generating spatial models at different positions, establishing cross-section models at multiple time points, and integrating plaque characteristics. This segmentation allows each component to be processed independently and systematically, improving overall modeling accuracy while managing complexity through structured decomposition.
Solution Approach 2:
The patent performs preliminary actions by first obtaining image data and generating spatial models before calculating blood flow pressure differences. Cross-section models are established at multiple time points in advance, and plaque characteristics are identified beforehand, so that when pressure difference calculation is needed, all necessary data and models are already prepared, improving accuracy without adding computational complexity during the final calculation phase.
2Measurement precision
If cross-section models are obtained at a single time point, then the modeling process is fast, but the accuracy is insufficient due to blood vessel dynamic changes during cardiac cycle
Solution Approach 1:
The patent merges multiple cross-section models obtained at different time points during the cardiac cycle into a comprehensive model. By combining information from multiple time points, the method captures the dynamic changes of blood vessels throughout the cardiac cycle, significantly improving modeling accuracy. The merging process integrates spatial and temporal information to create a more complete representation of blood vessel geometry.
Solution Approach 2:
The patent applies periodic action by obtaining image data and generating cross-section models at multiple specific time points within the periodic cardiac cycle. This periodic sampling captures the rhythmic changes in blood vessel geometry that occur with each heartbeat, ensuring that the model reflects the true dynamic behavior of the vessels without requiring continuous imaging.
3Measurement precision
If plaque characteristics are not considered in the model, then the calculation process is simple, but the pressure difference calculation has large errors
Solution Approach 1:
The patent applies local quality by specifically incorporating plaque characteristics into the cross-section models at the locations where plaques are present, rather than uniformly complicating the entire modeling process. The method identifies plaque regions and enhances the modeling detail locally in those areas, improving pressure difference calculation accuracy where it matters most while keeping the rest of the modeling process relatively simple.
Solution Approach 2:
The patent introduces cross-section models as intermediary structures that bridge the gap between simple imaging data and complex hemodynamic calculations. These intermediary models incorporate plaque characteristics and serve as a mediator that translates image data into accurate pressure difference calculations, simplifying the overall process while improving accuracy.
Data Source
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AI summary
The present invention relates to a method and a device for establishing a blood vessel cross-section function, a blood vessel pressure difference, and blood vessel stress. The method for establishing a blood vessel cross-section function includes the following steps: obtaining image data in at least one cardiac cycle; selecting a plurality of feature times during the one cardiac cycle; generating spatial models of a target region blood vessel corresponding to each of the feature times according to the image data; establishing a first cross-section model of the target region blood vessel at each position along an axial direction of the target region blood vessel according to each of the spatial models; and establishing a corresponding first cross-section function according to each first cross-section model. Compared with the prior art, this method can reflect actual conditions of blood vessels more accurately, and provide an intermediate variable with less error for subsequent analysis operations, so that the later calculated value is closer to the actual value.