IVUS-OCT Catheter Imaging for Ischemic Risk Prediction
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Solution Overview
Problem
Conventional techniques struggle to accurately predict the onset risk of ischemic heart disease using medical images of blood vessels.
Innovation Solution
An image diagnosis system employing a dual-type catheter with IVUS and OCT capabilities, combined with machine learning models, to generate and analyze ultrasonic and optical coherence tomographic images, extracting morphological features and stress values to predict the onset risk of ischemic heart disease.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing or machine learning is used to identify features of objects in blood vessel images, then features such as luminal wall and stent can be identified, but it is difficult to predict the onset risk of ischemic heart disease
Solution Approach 1:
The patent combines multiple imaging modalities (ultrasonic tomographic imaging and optical coherence tomographic imaging) into a single integrated system. This merging of different imaging techniques allows for comprehensive extraction of morphological features that individually would be insufficient for predicting ischemic heart disease onset risk, thereby resolving the contradiction between feature identification capability and disease prediction reliability
Solution Approach 2:
The patent extracts multiple types of parameters including morphological parameters (cross-sectional area, circumference, wall thickness) and stress parameters (wall stress, circumferential stress, axial stress) from the combined imaging data. By changing from single-parameter to multi-parameter analysis, the system achieves reliable prediction of ischemic heart disease onset risk while maintaining accurate feature identification
2Loss of information
If a dual-type catheter with both IVUS and OCT capabilities is used, then comprehensive morphological features can be extracted, but device complexity increases
Solution Approach 1:
The catheter is designed with multi-functionality, integrating both ultrasonic transmission/reception and optical light emission/reception capabilities into a single device. This universal design allows the catheter to perform multiple imaging functions (IVUS and OCT) simultaneously, ensuring complete morphological feature extraction without requiring multiple separate devices, thereby managing device complexity while maintaining information completeness
3Reliability
If multiple imaging modalities are integrated to predict onset risk, then prediction accuracy improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system employs automated processing where the integrated imaging system automatically extracts morphological parameters and calculates stress parameters from the acquired images. The computer-implemented algorithm performs self-service by automatically integrating the extracted features and generating onset risk predictions without requiring manual measurement or complex post-processing, thereby improving prediction accuracy while managing the difficulty of detection and measurement
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
Accurately estimates the onset risk of ischemic heart disease, enabling timely interventions to reduce the risk of re-onset.
Implementation Method 1
a first sensor configured to transmit ultrasonic waves and receive the waves reflected by the blood vessel
Implementation Method 2
a second sensor configured to emit light and receive the light reflected by the blood vessel
Data Source
AI summary
A system includes a catheter insertable into a blood vessel and including: a first sensor configured to transmit ultrasonic waves and receive the waves reflected by the vessel, and a second sensor configured to emit light and receive the light reflected by the vessel, and a processor configured to perform the steps of: generating an ultrasonic tomographic image of the vessel based on the waves and an optical coherence tomographic image of the vessel based on the light, specifying a location of a lesion in the vessel based on the images, generating first feature data related to the lesion from the ultrasonic image and second feature data related to the lesion from the optical image, inputting the feature data into a model to generate risk information related to an onset risk of ischemic heart disease, and outputting the risk information.