Seismocardiography-Based Cardiac Computed Tomography Gating Using Patient-Specific Template Identification and...

Area of Science:

• Biomedical Engineering
• Cardiovascular Imaging
• Signal Processing

Background:

• Electrocardiography (ECG) alone has limitations in accurately triggering cardiac computed tomography angiography (CTA) due to cardiac motion.
• Prospective gating of CTA requires precise identification of quiescent cardiac phases for optimal image quality.
• Seismocardiography (SCG) offers a novel approach to capture mechanical heart activity.

Purpose of the Study:

• To develop and evaluate a sub-system for fusing SCG with ECG to improve cardiac CTA triggering.
• To identify SCG waveforms corresponding to heart sounds and determine their phases within cardiac cycles.
• To model the relationship between SCG phases and heart rate.

Main Methods:

• A sub-system was developed to analyze SCG waveforms and their relation to cardiac phases.
• B-mode echocardiography was used as the gold standard for phase identification.
• Synchronous ECG, SCG, and echocardiography data were collected from healthy subjects and cardiac patients.

Main Results:

• The proposed algorithm identified 79% of SCG waveforms in systole and 68% in diastole.
• SCG-based prediction demonstrated less average phase error compared to ECG-based prediction.
• ECG-based gating accuracy is sensitive to heart rate variability, while SCG-based gating is sensitive to morphological variability.

Conclusions:

• SCG-based prediction of cardiac phases is a viable method for improving CTA triggering.
• This approach has the potential to enhance real-time image quality in CTA.
• Further development of multi-modal systems integrating SCG could significantly advance cardiovascular imaging.