Real-time gating system for mouse cardiovascular MR imaging

Abstract

Mouse cardiac MR gating using ECG is affected by the hostile MR environment. It requires appropriate signal processing and correct QRS detection, but gating software methods are currently limited. In this study we sought to demonstrate the feasibility of digital real-time automatically updated gating methods, based on optimizing a signal-processing technique for different mouse strains. High-resolution MR images of mouse hearts and aortic arches were acquired using a chain consisting of ECG signal detection, digital signal processing, and gating signal generation modeled using Simulink (The MathWorks, Inc., Natick, MA, USA). The signal-processing algorithms used were respectively low-pass filtering, nonlinear passband, and wavelet decomposition. Both updated and nonupdated gating signal generation methods were tested. Noise reduction was assessed by comparison of the ECG signal-to-noise ratio (SNR) before and after each processing step. Gating performance was assessed by measuring QRS detection accuracy before and after online trigger-level adjustments. Low-pass filtering with trigger-level adjustment gave the best performance for mouse cardiovascular imaging using gradient-echo (GE), spin-echo (SE), and fast SE (FSE) sequences with minimum induced delay and maximum gating efficiency (99% sensitivity and R-peak detection). This simple digital gating interface will allow various gating strategies to be optimized for cardiovascular MR explorations in mice.