A non-invasive central arterial pressure waveform estimation system using ultrasonography for real-time monitoring
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Hae-Seung Lee and Charles G. Sodini.
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This thesis details non-invasive evaluation of a central arterial blood pressure (ABP) waveform using a low-cost ultrasound scanning system. ABP bears significant clinical value in cardiovascular pathophysiology. Non-invasive evaluation of the full ABP waveform has been long desired by medical communities due to its anticipated opportunities to greatly enhance cardiovascular patient care. In addition, central ABP has been focused on because of its close association with the adverse outcomes of cardiovascular events. This work mainly explores monitoring of carotid arterial pulsation and local pulse wave velocity (PWV) by the designed system to estimate the ABP waveform, conducting simultaneous spectral Doppler and M-mode imaging. The system is characterized in electrical and acoustic domains to preserve adequate signal integrity to faithfully extract a spatial mean flow velocity and an arterial distension waveform. The carotid ABP waveform is estimated from the distension waveform and the local PWV with one-time calibration from an arterial-line (A-line) or a volume clamping method. The proof-of-concept study demonstrated that the carotid ABP waveform estimation is feasible. The pulse pressure estimation compared to a sphygmomanometer and a finger ABP waveform differ by 1.49±11.7 and -4.92±12.9 mmHg, respectively. The designed and characterized motion-tolerant ultrasonography extends tolerable lateral offsets up to ±8 mm while limiting error of the flow and distension waveforms within about 5%. The system is also validated under hemodynamic stress of the Valsalva maneuver and in intensive care settings compared to the A-line. This thesis demonstrates the profound potential for a portable low-cost ultrasound system toward non-invasive evaluation of a central ABP waveform in clinically relevant settings.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 163-170).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.