TY - JOUR
T1 - Detecting Aortic Valve-Induced Abnormal Flow with Seismocardiography and Cardiac MRI
AU - Johnson, Ethan M.I.
AU - Heller, J. Alex
AU - Garcia Vicente, Florencia
AU - Sarnari, Roberto
AU - Gordon, Daniel
AU - McCarthy, Patrick M.
AU - Barker, Alex J.
AU - Etemadi, Mozziyar
AU - Markl, Michael
N1 - Funding Information:
This work was supported by NIH NHLBI R01HL133504, NIH NHLBI R01HL130619, the Hartwell Foundation, a research grant from Circle Cardiovascular Imaging, and a research grant from Cryolife Inc. The authors disclose the following conflicts of interest: EJ: none. JH: none. FGV: none. RS: none. DG: none. PM: none. AB: none. ME: none. MM: research support from Siemens Healthineers, research grant from Circle Cardiovascular Imaging, research grant from Cryolife Inc, consultant for Circle Cardiovascular Imaging, consultant for NXT Biomedical.
Funding Information:
The authors disclose the following conflicts of interest: EJ: none. JH: none. FGV: none. RS: none. DG: none. PM: none. AB: none. ME: none. MM: research support from Siemens Healthineers, research grant from Circle Cardiovascular Imaging, research grant from Cryolife Inc, consultant for Circle Cardiovascular Imaging, consultant for NXT Biomedical.
Funding Information:
This work was supported by NIH NHLBI R01HL133504, NIH NHLBI R01HL130619, the Hartwell Foundation, a research grant from Circle Cardiovascular Imaging, and a research grant from Cryolife Inc.
Publisher Copyright:
© 2020, Biomedical Engineering Society.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Cardiac MRI (CMR) techniques offer non-invasive visualizations of cardiac morphology and function. However, imaging can be time-consuming and complex. Seismocardiography (SCG) measures physical vibrations transmitted through the chest from the beating heart and pulsatile blood flow. SCG signals can be acquired quickly and easily, with inexpensive electronics. This study investigates relationships between CMR metrics of function and SCG signal features. Same-day CMR and SCG data were collected from 28 healthy adults and 6 subjects with aortic valve disease history. Correlation testing and statistical median/decile calculations were performed with data from the healthy cohort. MR-quantified flow and function parameters in the healthy cohort correlated with particular SCG energy levels, such as peak aortic velocity with low-frequency SCG (coefficient 0.43, significance 0.02) and peak flow with high-frequency SCG (coefficient 0.40, significance 0.03). Valve disease-induced flow abnormalities in patients were visualized with MRI, and corresponding abnormalities in SCG signals were identified. This investigation found significant cross-modality correlations in cardiac function metrics and SCG signals features from healthy subjects. Additionally, through comparison to normative ranges from healthy subjects, it observed correspondences between pathological flow and abnormal SCG. This may support development of an easy clinical test used to identify potential aortic flow abnormalities.
AB - Cardiac MRI (CMR) techniques offer non-invasive visualizations of cardiac morphology and function. However, imaging can be time-consuming and complex. Seismocardiography (SCG) measures physical vibrations transmitted through the chest from the beating heart and pulsatile blood flow. SCG signals can be acquired quickly and easily, with inexpensive electronics. This study investigates relationships between CMR metrics of function and SCG signal features. Same-day CMR and SCG data were collected from 28 healthy adults and 6 subjects with aortic valve disease history. Correlation testing and statistical median/decile calculations were performed with data from the healthy cohort. MR-quantified flow and function parameters in the healthy cohort correlated with particular SCG energy levels, such as peak aortic velocity with low-frequency SCG (coefficient 0.43, significance 0.02) and peak flow with high-frequency SCG (coefficient 0.40, significance 0.03). Valve disease-induced flow abnormalities in patients were visualized with MRI, and corresponding abnormalities in SCG signals were identified. This investigation found significant cross-modality correlations in cardiac function metrics and SCG signals features from healthy subjects. Additionally, through comparison to normative ranges from healthy subjects, it observed correspondences between pathological flow and abnormal SCG. This may support development of an easy clinical test used to identify potential aortic flow abnormalities.
KW - 4D flow MRI
KW - Aortic valve disease
KW - Valve disease seismocardiography
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U2 - 10.1007/s10439-020-02491-3
DO - 10.1007/s10439-020-02491-3
M3 - Article
C2 - 32180050
AN - SCOPUS:85082771955
VL - 48
SP - 1779
EP - 1792
JO - Annals of Biomedical Engineering
JF - Annals of Biomedical Engineering
SN - 0090-6964
IS - 6
ER -