Quantification of Cardiac Kinetic Energy and Its Changes During Transmural Myocardial Infarction Assessed by Multi-Dimensional Seismocardiography

Abstract

Introduction: Seismocardiography (SCG) records cardiac and blood-induced motions transmitted to the chest surface as vibratory phenomena. Evidences demonstrate that acute myocardial ischemia (AMI) profoundly affects the SCG signals. Multidimensional SCG records cardiac vibrations in linear and rotational dimensions, and scalar parameters of kinetic energy can be computed. We speculate that AMI and revascularization profoundly modify cardiac kinetic energy as recorded by SCG.Methods: Under general anesthesia, 21 swine underwent 90 min of myocardial ischemia induced by percutaneous sub-occlusion of the proximal left anterior descending (LAD) coronary artery and subsequent revascularization. Invasive hemodynamic parameters were continuously recorded. SCG was recorded during baseline, immediately and 80 min after LAD sub-occlusion, and immediately and 60 min after LAD reperfusion. iK was automatically computed for each cardiac cycle (iKCC) in linear (iKLin) and rotational (iKRot) dimensions. iK was calculated as well during systole and diastole (iKSys and iKDia, respectively). Echocardiography was performed at baseline and after revascularization, and the left ventricle ejection fraction (LVEF) along with regional left ventricle (LV) wall abnormalities were evaluated.Results: Upon LAD sub-occlusion, 77% of STEMI and 24% of NSTEMI were observed. Compared to baseline, troponins increased from 13.0 (6.5; 21.3) ng/dl to 170.5 (102.5; 475.0) ng/dl, and LVEF dropped from 65.0 ± 0.0 to 30.6 ± 5.7% at the end of revascularization (both p < 0.0001). Regional LV wall abnormalities were observed as follows: anterior MI, 17.6% (three out of 17); septal MI, 5.8% (one out of 17); antero-septal MI, 47.1% (eight out of 17); and infero-septal MI, 29.4% (five out of 17). In the linear dimension, iKLinCC, iKLinSys, and iKLinDia dropped by 43, 52, and 53%, respectively (p < 0.0001, p < 0.0001, and p = 0.03, respectively) from baseline to the end of reperfusion. In the rotational dimension, iKRotCC and iKRotSys dropped by 30 and 36%, respectively (p = 0.0006 and p < 0.0001, respectively), but iKRotDia did not change (p = 0.41). All the hemodynamic parameters, except the pulmonary artery pulse pressure, were significantly correlated with the parameters of iK, except for the diastolic component.Conclusions: In this very context of experimental AMI with acute LV regional dysfunction and no concomitant AMI-related heart valve disease, linear and rotational iK parameters, in particular, systolic ones, provide reliable information on LV contractile dysfunction and its effects on the downstream circulation. Multidimensional SCG may provide information on the cardiac contractile status expressed in terms of iK during AMI and reperfusion. This automatic system may empower health care providers and patients to remotely monitor cardiovascular status in the near future.

Mechanocardiography in the Detection of Acute ST Elevation Myocardial Infarction: The MECHANO-STEMI Study

“…Previous experimental studies have shown significant waveform changes during acute myocardial infarction with 3-axes linear micro-accelerometers, suggesting that this methodology might be useful in the early detection of STEMI also in the clinical setting [8,29,30]. Most recently, it was demonstrated that using multi-dimensional seismocardiography, a significant drop in cardiac kinetic energy during experimental transmural myocardial infarction reflected a decrease in left ventricular contractile function [8].…”

“…Previous research has demonstrated that waveforms derived from seismocardiography and gyrocardiography reproduce the main events seen in left ventricular twist and strain rates obtained from echocardiography [3,7]. Experimental evidence also suggests that abnormalities in the heart function caused by myocardial infarction could be detected using this technology [8,9]. Clinical data on these techniques is still limited, but wearable seismocardiography can help to assess the clinical status of patients with heart failure using a machine learning algorithm [10].…”

Can Seismocardiogram Fiducial Points Be Used for the Routine Estimation of Cardiac Time Intervals in Cardiac Patients?

“…Indeed, other indexes of the heart performance, not based on the FP patterns, might be derived from the SCG signal. In literature, different alternative parameters are proposed, based on the estimation of overall signal energy (either obtained from the SCG alone or in combination with data from a gyroscope or the ballistocardiogram) ( Morra et al, 2021 ), and on the evaluation of the overall waveform characteristics through the spectral and time-frequency analysis ( Becker et al, 2014 ; Taebi and Mansy, 2017 ), dynamic-time feature matching ( Zia et al, 2020 ), hidden Markov model ( Wahlstrom et al, 2017 ), evolving fuzzy neural network ( Malcangi et al, 2020 ), and graph mining algorithms ( Inan et al, 2018 ). All these techniques extract clinical information specifically from the alterations in the waveforms caused by cardiac dysfunction.…”

Precordial Vibrations: A Review of Wearable Systems, Signal Processing Techniques, and Main Applications

“…The main obstacles to SCG clinical use are the instrumentation encumbrance, the lack of standardized sensor positioning, the influence of the inter- and intrasubject variability on SCG morphology, the lack of a standardized methodology to process the collected signal, and a reliable method for features extraction, useful to identify the underlying cardiac events [ 16 , 17 ]. However, recent research studies contributed to providing a deeper insight into these issues and proving the potential clinical feasibility of SCG for an early diagnosis of abnormal cardiac functions [ 18 , 19 , 20 , 21 , 22 ].…”