Respiratory rate estimation by using realignment data from a 1-minute high-temporal-resolution MRI sequence: A feasibility study.

Authors

Leonie Zerweck, Uwe Klose, Ulrike Ernemann, Till-Karsten Hauser

Published in

Acta radiologica (Stockholm, Sweden : 1987). Pages 2841851261484876. Sep 10, 2026. Epub Sep 10, 2026.

Abstract

BackgroundBreath-hold triggered functional magnetic resonance imaging (bh-fMRI) is a widely available, easily implementable and inexpensive method to quantify cerebrovascular reactivity. Estimation of patients' respiratory rate is relevant, as it might influence bh-fMRI data quality, but respiratory sensors integrated in the scanner table are not always available.PurposeTo propose an approach to estimate patients' respiratory rate using realignment data of a 1-min high-temporal-resolution cerebral MRI sequence.Material and MethodsIn a prospective study, 15 patients with Moyamoya angiopathy underwent a 1-min MRI sequence during routine clinical MRI. The respiratory rate was obtained by analyzing patients' head motion from image realignment data. To obtain robust results, the respiratory rate was calculated using a multi-method approach, incorporating power spectral density and fast Fourier transform and weighted data from multiparametric rigid body transformation. The respiratory rate detected from respiratory sensors integrated in the scanner table was used as reference. Bland-Altman analysis was performed and intra-class correlation coefficients (ICCs) were calculated to compare the respiratory rates.ResultsBland-Altman analysis revealed a mean bias of 0.5 breaths/min and limits of agreement (LoA) ranging from -5.3 to 4.4 breaths/min, with no outliers. The overall agreement between the respiratory rate calculated from realignment data and from scanner sensor data was excellent (ICC = 0.866, 95% confidence interval = 0.607-0.955; P < 0.001).ConclusionThe calculated mean bias and LoA appear to be clinically acceptable. Estimating respiratory rate from a 1-min high-temporal-resolution MRI sequence may be a feasible method when respiratory sensors integrated in the scanner are not available.

PMID:
42720433
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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