Abstract 4368713: Implantable Intramyocardial Sensor for Continuous Monitoring of Ventricular Function
Abstract
Background: Heart failure management increasingly requires accurate, continuous assessment of left ventricular (LV) function, including parameters such as systolic and end-diastolic pressure (LVSP, LVEDP). These metrics are typically measured intermittently using invasive catheterization, providing only point-in-time values rather than continuous hemodynamic monitoring. Currently, no established method exists for direct, long-term monitoring of LV pressures, limiting timely detection of decompensation and individualized therapy adjustment. Objective: To develop and validate an intramyocardial cardiac monitoring system enabling real-time estimation of LV function. Methods: A micro-electro-mechanical systems (MEMS) pressure sensor array was implanted into the LV free wall and integrated with a machine learning model trained to estimate intracardiac pressures from local myocardial dynamics. Validation was performed in acute swine experiments (n=3) under dobutamine stress, using intraventricular pressure-volume catheterization as the reference standard. Results: The system estimated LVSP and LVEDP with mean differences of 0.06 ± 5.3 mmHg and 0.15 ± 3.6 mmHg, respectively. Across all markers, the average coefficient of determination exceeded 0.85, indicating strong agreement. Conclusion: This MEMS-machine learning platform enables accurate, continuous estimation of LV function without the need for intra-cardiac instrumentation. Its compact design and real-time capabilities support its potential for even less invasive epicardial implementation, remote heart failure monitoring, and personalized therapy adjustment.
Article Details
Authors (7)
Max Haberbusch
Medical University of Vienna, Vienna, Austria
Stefan Schmitt
Fraunhofer Institute for Microtechnology and Microsystems, Mainz, Germany
Peter Detemple
Fraunhofer Institute for Microtechnology and Microsystems, Mainz, Germany
Philipp Aigner
Attila Kiss
Bruno Podesser
Medical University of Vienna, Vienna, Austria
Francesco Moscato