Suppression of MR gradient artefacts on electrophysiological signals based on an adaptive real-time filter with LMS coefficient updates.

Electrocardiogram (ECG) acquisition is still a challenge as gradient artefacts superimposed on the electrophysiological signal can only be partially removed. The signal shape of theses artefacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false triggering/gating of the MRI. For their real-time suppression, an adaptive filter is proposed. The adaptive filter is based on the noise-canceller configuration with LMS coefficient updates. The references of the noise canceller are the three gradient signals that are acquired simultaneously with the noisy ECG. Tests were done on patients, on volunteers and using an MR-safe ECG simulator. The noise canceller's performance was measured offline, simulating real-time processing by point-by-point operations. To create worst-case scenarios, clinical sequences with strong- and fast-switching gradients have been chosen. The noise-cancelling filter reduces the gradient artefacts' peak amplitudes by 80-99% after adaptation, without changing the desired ECG signal shape. The estimated reduction of total average power of the MR gradient artefacts is 62-98%. The proposed filter is capable of reducing artefacts due to strong- and fast-switching gradients in real-time applications and worst-case situations. The quality of the ECG is sufficiently high that a standard one-lead QRS-detector can be used for gating/triggering the MRI. For permanent patient monitoring, further improvements are needed.