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International audience; Objective: Despite being routinely acquired during MRI examinations for triggering or monitoring purposes, electrocardiogram (ECG) signal recording and analysis remain challenging due to the inherent magnetic environment of an MRI scanner. The ECG signals are particularly distorted by the induction of electrical fields in the body by the MRI gradients. In this study, we propose a new hardware and software solution for the acquisition of ECG signal during MRI up to 3 T.Approach: Instead of restricting the sensor bandwidth to limit these gradient artifacts, the new sensor architecture has a higher bandwidth, higher sampling frequency and larger input dynamics, in order to acquire the ECG signals and the gradient artifacts more precisely. Signal processing based on a novel detection algorithm and blanking are then applied for improved artifact suppression.Main results: The proposed sensor allows the gradient artifacts to be acquired more precisely, and these artifacts are recorded with peak-to-peak amplitudes two orders of magnitude larger than for QRS complexes. The proposed method outperforms a state-of-the-art approach both in terms of signal quality (+9% 'SNR') and accuracy of QRS detection (+11%).Significance: The proposed hardware and software solutions open the way for the acquisition of high-quality of ECG gating in MRI, and improved diagnostic quality of ECG signals in MRI.

International audience; Electrocardiogram (ECG) is required during magnetic resonance (MR) examination for monitoring patients under anaesthesia or with heart diseases and for synchronizing image acquisition with heart activity (triggering). Accurate and fast QRS detection is therefore desirable, but this task is complicated by artefacts related to the complex MR environment (high magnetic field, radio-frequency pulses and fast switching magnetic gradients). Specific signal processing has been proposed, whether using specific MR QRS detectors or ECG denoising methods. Most state-of-the-art techniques use a connection to the MR system for achieving their task, which is a major drawback since access to the MR system is often restricted. This paper introduces a new method for on-line ECG signal enhancement, called ICARE, which takes advantage of using multi-lead ECG and does not require any connection to the MR system. It is based on independent component analysis (ICA) and applied in real time. This algorithm yields accurate QRS detection for efficient triggering.