IVUS Target and Reference Detection for Standardized Vein Imaging
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Solution Overview
Problem
The interpretation of intravascular ultrasound (IVUS) images for identifying treatment targets and reference locations in peripheral vascular procedures is non-standardized, leading to varying outcomes and difficulty for novice clinicians, and there is an overreliance on trained staff due to the complexity of interpreting IVUS images of deep venous diseases.
Innovation Solution
An automatic target and reference detection system for IVUS procedures that provides a uniform strategy for interpreting IVUS imagery, including algorithms to identify target and reference locations, while allowing flexibility for expert users to override default behaviors, and supports standardization of deep venous IVUS procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual interpretation of IVUS images by clinicians is used, then diagnostic accuracy can be achieved through expert judgment, but interpretation variability and difficulty for novice clinicians increase
Solution Approach 1:
An automated analysis system serves as an intermediary between the IVUS imaging system and the clinician, providing standardized target and reference location identification. The system processes images through defined algorithms to generate objective measurements, reducing the burden on clinicians while maintaining diagnostic accuracy through standardized protocols.
Solution Approach 2:
The manual mechanical process of visual inspection and subjective judgment by clinicians is replaced with an automated computational system that applies consistent algorithms to identify target and reference locations. This substitution eliminates human variability in interpretation while maintaining or improving diagnostic accuracy through standardized criteria.
2Reliability
If standardized interpretation protocols are implemented, then consistency and reliability improve, but flexibility for expert judgment and override capabilities are reduced
Solution Approach 1:
The system implements dynamic adaptability where the level of standardization can be adjusted based on user needs. Automated analysis provides standardized results for routine cases, while the system allows expert users to override automated findings or adjust parameters for complex cases requiring specialized judgment, thus maintaining both reliability and flexibility.
Solution Approach 2:
The system serves multiple functions: it provides fully automated standardized analysis for routine interpretation, allows semi-automated operation with user adjustments for intermediate cases, and supports fully manual operation for complex expert judgment cases. This multi-functionality ensures both consistency through standardization and adaptability for expert flexibility.
3Productivity
If automated detection algorithms are used, then interpretation time and novice clinician burden are reduced, but system complexity and development requirements increase
Solution Approach 1:
The automated detection system is segmented into distinct functional modules: image acquisition interface, automated analysis engine with configurable algorithms, results generation component, and user interaction layer. This segmentation allows the complex system to be developed, tested, and maintained in manageable sections while providing high-level interpretation automation that reduces clinician workload.
4Manufacturing precision
If uniform analysis strategy is applied to all cases, then standardization and reproducibility improve, but ability to account for individual patient variations and disease heterogeneity is reduced
Solution Approach 1:
The system applies the principle of local quality by allowing different analysis parameters and criteria to be applied to different regions of interest within the same patient's images. While maintaining a uniform overall framework for reproducibility, the system can adjust local analysis settings to account for patient-specific anatomical variations and disease heterogeneity, ensuring both standardization and customization.
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
The system enhances the accuracy and efficiency of identifying treatment targets and reference locations in peripheral veins by providing standardized analysis with the option for expert override, reducing reliance on trained staff and improving clinical confidence.
Implementation Method 1
The transducers emit ultrasonic energy and receive ultrasound echoes reflected from the vessel
Data Source
AI summary
An intraluminal ultrasound imaging system is presented which includes a processor circuit configured for communication with an intraluminal ultrasound imaging catheter. The processor circuit is configured to receive a plurality of intraluminal ultrasound images obtained by the intraluminal ultrasound imaging catheter during movement within a body lumen of a patient. The body lumen includes a plurality of segments, as well as a compression within at least one segment. The processor circuit is also configured to automatically, based on the images, determine a target location within the compression and a reference location comprising a healthy portion of the lumen proximate to the compression; and output, to a display in communication with the processor circuit, a screen display that includes the target location, the reference location, and at least one quantity associated with the target location and reference location.