An active approach of pressure waveform matching for stress-based testing of arteries.

BACKGROUND: Arterial compliance assists the cardiovascular system with three key roles: (i) storing up to 50% of the stroke volume; (ii) ensuring blood flow during diastole; (iii) dampening pressure oscillations through arterial distension. In mock circulation loops (MCLs), arterial compliance was simulated either with membrane, spring, or Windkessel chambers. Although they have been shown to be suitable for cardiac device testing, their passive behavior can limit stress-based testing of arteries. Here we present an active compliance chamber with a feedback control of variable compliance as part of an MCL designed for biomechanical evaluation of arteries under physiological waveforms. MATERIALS AND METHODS: The chamber encloses a piston that changes the volume via a cascaded controller when there is a difference between the real-time pressure and the physiological reference pressure with the aim to equilibrate both pressures. RESULTS: The experimental results showed repeatable physiological waveforms of aortic pressure in health (80-120 mm Hg), systemic hypertension (90-153 mm Hg), and heart failure reduced ejection fraction (78-108 mm Hg). Statistical validation (n = 20) of the function of the chamber is presented against compared raw data. CONCLUSION: We demonstrate that the active compliance chamber can track the actual pressure of the MCL and balance it in real time (every millisecond) with the reference values in order to shape the given pressure waveform. The active compliance chamber is an advanced tool for MCL applications for biomechanical examination of stented arteries and for preclinical evaluation of vascular implants.

Detection of myocardial ischemia due to clinically asymptomatic coronary artery stenosis at rest using supervised artificial intelligence-enabled vectorcardiography - A five-fold cross validation of accuracy.

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death and disability. Conventional non-invasive diagnostic modalities for the detection of stable CAD at rest are subject to significant limitations: low sensitivity, and personal expertise. We aimed to develop a reliable and time-cost efficient screening tool for the detection of coronary ischemia using machine learning. METHODS: We developed a supervised artificial intelligence algorithm combined with a five lead vectorcardiography (VCG) approach (i.e. Cardisiography, CSG) for the diagnosis of CAD. Using vectorcardiography, the excitation process of the heart can be described as a three-dimensional signal. A diagnosis can be received, by first, calculating specific physical parameters from the signal, and subsequently, analyzing them with a machine learning algorithm containing neuronal networks. In this multi-center analysis, the primary evaluated outcome was the accuracy of the CSG Diagnosis System, validated by a five-fold nested cross-validation in comparison to angiographic findings as the gold standard. Individuals with 1, 2, or 3- vessel disease were defined as being affected. RESULTS: Of the 595 patients, 62·0% (n = 369) had 1, 2 or 3- vessel disease identified by coronary angiography. CSG identified a CAD at rest with a sensitivity of 90·2 ± 4·2% for female patients (male: 97·2 ± 3·1%), specificity of 74·4 ± 9·8% (male: 76·1 ± 8·5%), and overall accuracy of 82·5 ± 6·4% (male: 90·7 ± 3·3%). CONCLUSION: These findings demonstrate that supervised artificial intelligence-enabled vectorcardiography can overcome limitations of conventional non-invasive diagnostic modalities for the detection of coronary ischemia at rest and is capable as a highly valid screening tool.

Diagnosis of obstructive coronary artery disease by cardiogoniometry: a field test in a real-life setting.

Cardiogoniometry is an electrocardiographic and vectorcardiographic method utilizing computer-assisted analysis of cardiac potentials focusing on T-wave abnormalities resulting from myocardial malperfusion. We describe a case of diagnosis of obstructive coronary artery disease with this method and discuss the possible implications for the clinical setting.

Current state of total artificial heart therapy and introduction of the most important total artificial heart systems.

Due to the declining instances of organ donation, total artificial heart (TAH) therapy is of increasing importance for the management of end-stage biventricular heart failure. We introduce the currently most important established and novel TAH systems (SynCardia, CARMAT, ReinHeart, BiVACOR), report clinical outcomes and discuss technical requirements for the successful implementation of TAH therapy as an alternative to cardiac transplantation.

Should heart failure patients be left to fate? Temporary implementation of veno-arterial extracorporeal membrane oxygenation for haemodynamic support during excision of rectal carcinoma in an end-stage biventricular heart failure patient.

Management of end-stage heart failure patients requiring major general surgery is not well defined. Due to poor cardiorespiratory reserve, perioperative morbidity and mortality are excessively high. We report a case of temporary implementation of veno-arterial extracorporeal membrane oxygenation for haemodynamic support during excision of rectal carcinoma in an end-stage heart failure patient and describe perioperative management.

Applicability of cardiogoniometry as a non-invasive screening tool for the detection of graft vasculopathy in heart transplant recipients.

Currently available diagnostic modalities for the detection of graft vasculopathy following orthotopic heart transplantation are subject to various restrictions. We hypothesized that cardiogoniometry, a novel non-invasive diagnostic tool for the detection of atherosclerotic coronary vessel disease, is applicable in the graft vasculopathy setting. Cardiogoniometric results were obtained during routine follow-up in 49 consecutive, unselected heart transplant recipients and then retrospectively correlated blindly by an independent reader to recent angiographic findings. Sensitivity of cardiogoniometry was 100%, specificity 62.3%, positive predictive value 68.75%, negative predictive value 100%, negative likelihood ratio 0 and positive likelihood ratio 2.888. Cardiogoniometry is potentially applicable as an easy-to-perform, non-invasive screening tool predominantly for the exclusion but also for the detection of graft vasculopathy in heart transplant recipients.