Fetal Heart Ultrasound Phase Analysis Without Synchronized ECG
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Solution Overview
Problem
Existing ultrasound technologies face challenges in accurately evaluating cardiac functions of fetuses due to difficulties in obtaining synchronized electrocardiographic waveforms and determining the position and posture of fetal hearts, leading to cumbersome manual settings and reduced precision in speckle tracking applications.
Innovation Solution
The ultrasound diagnosis apparatus employs a data processing function to calculate variance distributions and center positions of fetal hearts using high variance images, followed by principal component analysis to estimate heart size and posture, enabling automatic setting of cardiac phase analysis without relying on synchronized ECG signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual settings are used to determine fetal heart position and posture, then the system can accommodate various fetal positions, but the operation becomes cumbersome and time-consuming
Solution Approach 1:
The system automatically determines fetal heart position and posture by analyzing ultrasound images itself, without requiring manual intervention. The processor extracts feature points from the ultrasound image, determines heart position and posture based on these features, and sets the analysis region automatically, making the system self-sufficient in adapting to various fetal positions
Solution Approach 2:
The system performs preliminary analysis of the ultrasound image to determine fetal heart position and posture before conducting the actual cardiac function analysis. By pre-determining the analysis region and parameters based on image features, the system prepares everything needed for accurate measurement in advance, eliminating the need for manual setup during the analysis phase
2Measurement precision
If synchronized ECG signals are required for cardiac phase analysis, then measurement precision can be maintained, but the system cannot be applied to fetuses where ECG signals are difficult to obtain
Solution Approach 1:
The system extracts cardiac phase information directly from ultrasound image data by analyzing the movement and deformation of fetal heart structures. By taking out the dependency on external ECG signals and using only the ultrasound image features and temporal changes in heart wall motion, the system maintains measurement precision while becoming applicable to fetal cases where ECG signals are unavailable
Solution Approach 2:
The system uses ultrasound image features and heart wall motion data as an intermediary to determine cardiac phases. Instead of directly using ECG signals, the processor analyzes intermediate parameters such as the position of heart walls, chamber volumes, and motion patterns from ultrasound sequences to infer cardiac phase information, thereby bridging the gap between ultrasound imaging and cardiac phase identification
3Extent of automation
If automatic determination of fetal heart position is implemented, then manual intervention is reduced, but the complexity of image processing increases
Solution Approach 1:
The system segments the fetal heart region from the surrounding tissue by identifying specific feature points in the ultrasound image. The processor divides the complex image analysis into manageable steps: detecting key anatomical landmarks, determining their spatial relationships, and using these to define the analysis region. This segmentation approach automates the process while keeping each processing step relatively simple and interpretable
Data Source
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AI summary
An ultrasound diagnosis apparatus (1) according to an embodiment includes processing circuitry (180). The processing circuitry (180) is configured to specify a region being a part of a heart on the basis of two- or three-dimensional moving image data rendering the heart. The processing circuitry (180) is configured to obtain a reference waveform that makes it possible to estimate a cardiac phase, on the basis of the region in the moving image data specified.