Denoising of the gradient artifact present in simultaneous studies of muscle blood oxygen level dependent (BOLD) signal and electromyography (EMG)
The MR-induced gradient artifact affects EMG recordings during simultaneous muscle BOLD/EMG acquisitions. However, no dedicated hardware can remove the gradient artifact easily, and alternative methods are expensive and time-consuming. This study aimed to develop three denoising methods requiring di...
Gespeichert in:
Veröffentlicht in: | Magnetic resonance imaging 2024-09, Vol.111, p.179-185 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The MR-induced gradient artifact affects EMG recordings during simultaneous muscle BOLD/EMG acquisitions. However, no dedicated hardware can remove the gradient artifact easily, and alternative methods are expensive and time-consuming. This study aimed to develop three denoising methods requiring different processing levels and MR-compatible hardware.
At two time points, surface EMG was recorded from the lower leg of 6 participants (50:50 sex ratio, age = 26.24.6 yrs., height = 173.59.2 cm, weight = 71.511.4 kg) using a plantar flexion-based block design consisting of 30s of rest followed by 30s of flexion for 5 min, under three conditions: inside the MRI bore, with and without a BOLD sequence (3 T, BOLD sequence, GRE EPI, 10 slices, 64×64 matrix, 2 mm thickness, and TE/TR/flip = 35/3000 ms/70), and outside the MRI environment. Simultaneous BOLD/EMG recordings were denoised using average artifact subtraction with three methods of artifact template creation, each having varying timing and hardware requirements. Method M1 builds the artifact template by recording the scanner triggers coming from the MRI; M2 creates the artifact template with a constant artifact period computed as TR/[number of slices]; M3 estimates the artifact template by looking at the periodicity of the gradient artifact located in the EMG recordings. Following postprocessing, SNR analysis was performed, comparing rest-to-flexion periods, to assess the efficacy of denoising methods and to compare differences between conditions.
Linear mixed-effects models showed no significant differences in the mean SNR between denoising methods (p = 0.656). Furthermore, EMG SNR measurements were significantly affected by the magnetic environment (p |
---|---|
ISSN: | 0730-725X 1873-5894 1873-5894 |
DOI: | 10.1016/j.mri.2024.05.004 |