Key result
HRV-based ECG-derived respiration matches recorded respiration for physiological noise correction during MRI.
Why the study?
Recording physiological signals during fMRI increases complexity and participant discomfort, especially in simultaneous EEG-fMRI studies, motivating the extraction of respiration from ECG without extra equipment.
Does ECG-derived respiration (EDR) accurately estimate respiratory fluctuations and explain BOLD-fMRI physiological noise compared to directly recorded respiration in healthy subjects?
Observational (n=15)
No
Does ECG-derived respiration (EDR) accurately estimate respiratory fluctuations and explain BOLD-fMRI physiological noise compared to directly recorded respiration in healthy subjects?
Meaningful respiratory information can be extracted from ECG within the MRI environment using heart rate variability, providing a reliable alternative for physiological noise correction in EEG-fMRI studies when direct respiration recording is unavailable.
May facilitate noise correction in MRI-EEG when direct recording unavailable; leaves open validation in patients.
Recording physiological signals during fMRI is valuable for multiple purposes but often requires additional setup, increasing complexity and participant discomfort. This is particularly challenging in simultaneous EEG-fMRI studies, which typically already include electrocardiogram (ECG) recordings. Here, we aim to leverage the known modulation of ECG by respiration to obtain an ECG-derived respiration (EDR) signal without extra equipment. We acquired EEG-fMRI data from 15 healthy subjects during resting state and two respiratory challenges (slow-paced breathing and breath-holding), with simultaneous ECG and respiratory recordings. Multiple methods were used to extract EDR signals, and the results were evaluated by comparing them with recorded respiration and assessing the quality of physiological regressors for denoising and cerebrovascular reactivity estimation. Amplitude-based EDR methods showed lower correlations with respiration, likely due to ECG distortion in the MRI. Nevertheless, coherence analysis showed that EDR preserved the relevant spectral content. EDR-based regressors were similar to those obtained from measured respiration. Notably, a method based on heart rate variability performed best overall, yielding physiological noise correction and reactivity estimates comparable to those using recorded respiration. Our results demonstrate that meaningful respiratory information can be extracted from ECG within the MRI environment, benefiting EEG-fMRI studies when respiration cannot be reliably recorded.
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Esteves et al. (2025) conducted an observational in Healthy (n=15). ECG-derived respiration (EDR) vs. Measured respiratory signals was evaluated on Variance explained in BOLD fMRI signal and similarity to measured respiration. A heart rate variability-based ECG-derived respiration method successfully extracted respiratory information from ECG in the MRI environment, performing comparably to recorded respiration for physiological noise correction.
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