Automatic OCT Pullback Trigger Using Blood-Clearing Edge Detection
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Solution Overview
Problem
Intravascular optical coherence tomography (OCT) systems struggle to capture clear images of blood vessel lumens due to the scattering of near-infrared light by red blood cells, making it difficult to reconstruct images when blood is present.
Innovation Solution
A system and method to identify when blood has been sufficiently cleared from a blood vessel by analyzing edge offsets in consecutive image frames, determining initial and final clearing states, and automatically initiating a catheter pullback procedure for image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If intravascular OCT imaging is performed with blood present in the lumen, then continuous imaging can be maintained, but image quality deteriorates due to strong light scattering by red blood cells
Solution Approach 1:
The system performs preliminary detection of blood clearing status by analyzing edge offsets in consecutive image frames before initiating the pullback procedure. This allows the system to identify when blood has been sufficiently cleared from the lumen, ensuring optimal imaging conditions are achieved before data collection begins
Solution Approach 2:
The system continuously monitors image frames during the flushing process and uses feedback from edge offset analysis to determine when blood clearing is sufficient. The real-time analysis of edge positions provides feedback that triggers the pullback at the optimal moment, balancing image quality with imaging continuity
2Reliability
If the pullback procedure is initiated immediately after flushing, then imaging time is maximized, but blood may not be sufficiently cleared resulting in poor image quality
Solution Approach 1:
The system replaces manual assessment of blood clearing status with automated image processing techniques. By substituting mechanical/visual assessment with computational analysis of edge offsets and image frame characteristics, the system objectively determines when sufficient clearing has occurred without relying on operator judgment or fixed time delays
Solution Approach 2:
The system changes the parameter used for clearing assessment from subjective visual evaluation to quantitative edge offset measurement. By measuring the positional parameters of edges in image frames and analyzing their offsets from the lumen center, the system provides an objective, measurable criterion for determining adequate blood clearing
3Productivity
If manual assessment of blood clearing is used, then operator judgment can adapt to individual cases, but imaging delays increase and productivity decreases
Solution Approach 1:
The system performs self-assessment of blood clearing status through automated image processing. The OCT system analyzes its own image frames to determine when blood has been sufficiently cleared, eliminating the need for operator intervention or external assessment tools. This self-service capability significantly reduces imaging delays and improves productivity
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 real-time, accurate identification of blood clearing states, allowing for optimal image acquisition without blood interference, thereby maximizing the utility of flush medium and minimizing delays in data collection.
Implementation Method 1
OCT combines the principles of ultrasound with the imaging performance of a microscope and a form factor that is familiar to clinicians. Whereas ultrasound produces images from backscattered sound 'echoes,' OCT uses infrared light waves that reflect off the internal microstructure within the biological tissues.
Implementation Method 2
OCT uses infrared light waves that reflect off the internal microstructure within the biological tissues.
Implementation Method 3
A potential limitation of cardiovascular OCT is that it cannot produce clear images of a lumen wall when blood is present within the lumen, as the components of red blood cells strongly scatter the near-infrared light, making image reconstruction difficult.
Data Source
AI summary
Aspects of the disclosure relate to the identification of when a blood vessel has been sufficiently cleared of blood so as to capture intravascular images of the vessel wall. The disclosed systems and methods allow for the identification of an initial and a final blood clearing based on the identification of edges within scanlines of a plurality of image frames. The edges of a plurality of scanlines may be analyzed to determine an average edge offset for each image frame, and the average edge offsets for a plurality of image frames may be averaged over various time-windows, so as to determine when the initial and final blood clearing events have occurred. Once a final blood clearing event has been identified, the disclosed system may automatically initiate a catheter pullback procedure, so as to capture intravascular images over a length of the vessel that has been sufficiently cleared of blood.