Continuous Rapid Quantification of Stroke Volume Using Magnetohydrodynamic Voltages in 3T Magnetic Resonance Imaging

• Authors: T. Stan Gregory, University of Georgia; John Oshinski, Emory University; Ehud J. Schmidt, Brigham and Women’s Hospital; Raymond Y. Kwong, Brigham and Women’s Hospital; William G. Stevenson, Brigham and Women’s Hospital; Zion Tsz Ho Tse, University of Georgia
• Journal Title: Circulation: Cardiovascular Imaging
• Volume: Volume 8, Number 12
• Publisher: American Heart Association | 2015-12-01
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1161/CIRCIMAGING.115.003282
• Subjects: Engineering, Biomedical; Health Sciences, Radiology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Cardiac & Cardiovascular Systems; Radiology, Nuclear Medicine & Medical Imaging; Cardiovascular System & Cardiology; electrocardiogram; interventional magnetic resonance imaging; magnetic resonance imaging; stroke volume

Abstract

Background: To develop a technique to non-invasively estimate Stroke Volume (SV) in real-time during Magnetic Resonance Imaging (MRI) guided procedures, based on induced Magnetohydrodynamic Voltages (VMHD) that occur in Electrocardiogram (ECG) recordings during MRI exams, leaving the MRI scanner free to perform other imaging tasks. Due to the relationship between blood-flow (BF) and VMHD, we hypothesized that a method to obtain SV could be derived from extracted VMHD vectors in the Vectorcardiogram frame-of-reference (VMHDVCG). Methods and Results: To estimate a subject-specific BF-VMHD model, VMHDVCG was acquired during a 20-second breath-hold and calibrated versus aortic BF measured using Phase Contrast Magnetic Resonance (PCMR) in 10 subjects (n=10) and one subject diagnosed with Premature Ventricular Contractions (PVCs). Beat-to-Beat validation of VMHDVCG derived BF was performed using Real-Time Phase Contrast (RTPC) imaging in 7 healthy subjects (n=7) during a 15 minute cardiac exercise stress tests and 30 minutes after stress relaxation in 3T MRIs. Subject-specific equations were derived to correlate VMHDVCG to BF at rest, and validated using RTPC. An average error of 7.22% and 3.69% in SV estimation, respectively, was found during peak stress, and after complete relaxation. Measured beat-to-beat blood flow time-history derived from RTPC and VMHD were highly correlated using a Spearman Rank Correlation Coefficient during stress tests (0.89) and after stress relaxation (=0.86). Conclusions: Accurate beat-to-beat SV 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.