T Stan Gregory1, John Oshinski1, Ehud J Schmidt1, Raymond Y Kwong1, William G Stevenson1, Zion Tsz Ho Tse2. 1. From the College of Engineering, University of Georgia, Athens (T.S.G., Z.T.H.T.); Departments of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA (J.O.); Departments of Radiology (E.J.S.) and Cardiology (R.Y.K., W.G.S.), Brigham and Women's Hospital, Boston, MA. 2. From the College of Engineering, University of Georgia, Athens (T.S.G., Z.T.H.T.); Departments of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA (J.O.); Departments of Radiology (E.J.S.) and Cardiology (R.Y.K., W.G.S.), Brigham and Women's Hospital, Boston, MA. ziontse@uga.edu.
Abstract
BACKGROUND: To develop a technique to noninvasively estimate stroke volume in real time during magnetic resonance imaging (MRI)-guided procedures, based on induced magnetohydrodynamic voltages (VMHD) that occur in ECG recordings during MRI exams, leaving the MRI scanner free to perform other imaging tasks. Because of the relationship between blood flow (BF) and VMHD, we hypothesized that a method to obtain stroke volume could be derived from extracted VMHD vectors in the vectorcardiogram (VCG) frame of reference (VMHDVCG). METHODS AND RESULTS: To estimate a subject-specific BF-VMHD model, VMHDVCG was acquired during a 20-s breath-hold and calibrated versus aortic BF measured using phase-contrast magnetic resonance in 10 subjects (n=10) and 1 subject diagnosed with premature ventricular contractions. Beat-to-beat validation of VMHDVCG-derived BF was performed using real-time phase-contrast imaging in 7 healthy subjects (n=7) during 15-minute cardiac exercise stress tests and 30 minutes after stress relaxation in 3T MRIs. Subject-specific equations were derived to correlate VMHDVCG with BF at rest and validated using real-time phase-contrast. An average error of 7.22% and 3.69% in stroke volume estimation, respectively, was found during peak stress and after complete relaxation. Measured beat-to-beat BF time history derived from real-time phase-contrast and VMHD was highly correlated using a Spearman rank correlation coefficient during stress tests (0.89) and after stress relaxation (0.86). CONCLUSIONS: Accurate beat-to-beat stroke volume and BF were estimated using VMHDVCG extracted from intra-MRI 12-lead ECGs, providing a means to enhance patient monitoring during MR imaging and MR-guided interventions.
BACKGROUND: To develop a technique to noninvasively estimate stroke volume in real time during magnetic resonance imaging (MRI)-guided procedures, based on induced magnetohydrodynamic voltages (VMHD) that occur in ECG recordings during MRI exams, leaving the MRI scanner free to perform other imaging tasks. Because of the relationship between blood flow (BF) and VMHD, we hypothesized that a method to obtain stroke volume could be derived from extracted VMHD vectors in the vectorcardiogram (VCG) frame of reference (VMHDVCG). METHODS AND RESULTS: To estimate a subject-specific BF-VMHD model, VMHDVCG was acquired during a 20-s breath-hold and calibrated versus aortic BF measured using phase-contrast magnetic resonance in 10 subjects (n=10) and 1 subject diagnosed with premature ventricular contractions. Beat-to-beat validation of VMHDVCG-derived BF was performed using real-time phase-contrast imaging in 7 healthy subjects (n=7) during 15-minute cardiac exercise stress tests and 30 minutes after stress relaxation in 3T MRIs. Subject-specific equations were derived to correlate VMHDVCG with BF at rest and validated using real-time phase-contrast. An average error of 7.22% and 3.69% in stroke volume estimation, respectively, was found during peak stress and after complete relaxation. Measured beat-to-beat BF time history derived from real-time phase-contrast and VMHD was highly correlated using a Spearman rank correlation coefficient during stress tests (0.89) and after stress relaxation (0.86). CONCLUSIONS: Accurate beat-to-beat stroke volume and BF were estimated using VMHDVCG extracted from intra-MRI 12-lead ECGs, providing a means to enhance patient monitoring during MR imaging and MR-guided interventions.
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