7-Tesla Functional Cardiovascular MR Using Vectorcardiographic Triggering-Overcoming the Magnetohydrodynamic Effect.

Area of Science:

• Cardiovascular Imaging
• Magnetic Resonance Imaging
• Biomedical Engineering

Background:

• Ultra-high-field (7 tesla) cardiovascular magnetic resonance (CMR) offers enhanced resolution.
• The magnetohydrodynamic effect significantly distorts electrocardiogram (ECG) signals at 7T, impacting gating accuracy.
• Accurate ECG gating is crucial for quantitative cardiac volume and flow assessment.

Purpose of the Study:

• To evaluate the technical feasibility of a 7T MRI scanner using an ECG trigger learning algorithm.
• To quantitatively assess cardiac volumes and vascular flow using this novel triggering method.
• To determine the accuracy and reliability of the ECG trigger learning algorithm at 7T.

Main Methods:

• 10 healthy volunteers underwent 7T CMR scans using a research MRI scanner and specialized cardiac coils.
• A vectorcardiogram ECG system with a learning phase outside the magnetic field was employed.
• Cine CMR and 2D phase contrast flow imaging were performed after B0 shimming; artifacts were semi-quantitatively assessed.

Main Results:

• The vectorcardiogram learning method successfully acquired 7T CMR scans in all participants (100%).
• Quantitative analysis of 3,142 R-waves demonstrated high sensitivity (97.6%) and specificity (98.7%).
• Mean image quality score of 0.9 allowed sufficient quantification of cardiac volumes, ejection fraction, and blood flow.

Conclusions:

• Reliable cardiac ECG triggering is feasible at 7T in healthy volunteers using a state-of-the-art trigger device, despite magnetohydrodynamic effect distortions.
• The method provides sufficient image quality for quantitative analysis of cardiac function and flow.
• This ECG triggering approach may benefit other ultra-high-field MRI applications, including functional MRI with physiologic noise correction.