Vessel Pressure-Ratio Curves for Automatic Stenosis Step Detection
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Solution Overview
Problem
Existing medical devices and methods struggle to accurately and consistently identify significant stepped changes in pressure ratio curves to determine the presence and extent of stenoses in blood vessels, which is crucial for determining appropriate treatment strategies.
Innovation Solution
An Automatic Step Detection (ASD) process and algorithm are employed to analyze pressure ratio curves by applying threshold values within set windows to identify and optimize the starting and ending points of significant stepped changes, using a processor to calculate and display these changes in real-time or near-real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to identify stepped changes in pressure ratio curves, then the analysis process is simple, but the measurement precision and reliability of stenosis detection is insufficient
Solution Approach 1:
The pressure ratio curve is divided into multiple windows (first window, second window, third window, fourth window) with different sizes and threshold values. The first and third windows use larger sizes with higher threshold values for general change detection, while the second and fourth windows use smaller sizes with lower threshold values for optimized position identification. This segmentation allows the system to achieve high measurement precision for stenosis detection by analyzing different portions of the curve with appropriately tuned parameters.
Solution Approach 2:
The system dynamically adjusts the window sizes and threshold values based on the specific characteristics of the pressure ratio curve and the detection requirements. By having multiple window configurations (larger windows for general detection, smaller windows for optimized positioning) and adjusting threshold values accordingly, the system adapts its analysis parameters to achieve both high precision and appropriate complexity levels.
2Reliability
If a single threshold value and window size are used for step detection, then the device complexity is low, but the measurement precision and reliability of identifying stepped changes is insufficient
Solution Approach 1:
The detection algorithm is segmented into multiple stages with different window sizes and threshold values. The first stage uses a first window with a first threshold value to identify general changes, while the second stage uses a second window with a second threshold value to optimize the starting point position. Similarly, the third stage uses a third window with a third threshold value to identify general ending points, and the fourth stage uses a fourth window with a fourth threshold value to optimize ending point positions. This segmentation significantly improves reliability by systematically verifying detection results through multiple levels of analysis.
Solution Approach 2:
The system performs preliminary detection using larger windows and higher threshold values to identify potential stepped changes before optimizing the positions using smaller windows and lower threshold values. This preliminary action filters out false positives early in the process while maintaining the ability to detect subtle changes, thereby improving overall reliability without requiring the most complex analysis to be performed throughout the entire process.
Data Source
AI summary
A method, device, and system for evaluating a vessel of a patient, and in particular the hemodynamic impact of a stenosis within the vessel of a patient. Proximal and distal pressure measurements are made using first and second instrument while the first instrument is moved longitudinally through the vessel from a first position to a second position and the second instrument remains in a fixed longitudinal position within the vessel. A series of pressure ratio values are calculated, and a pressure ratio curve is generated. One or more stepped change in the pressure ratio curve are then identified and/or located using an Automatic Step Detection (ASD) process and/or algorithm. The ASD includes identifying a general position of a starting point of the stepped change by identifying a change in the pressure ratio values within a first window along the pressure ratio curve that is at or above a first threshold change value, and identifying an optimized position of the starting point by identifying a change in the pressure ratio values within a second window along the pressure ratio curve that is at or above a second threshold change value, wherein the second window is smaller than the first window, and the second threshold change value is smaller than the first threshold change value.