Ventricular Contractility and Compliance Measured During Axial Flow Blood Pump Support: In Vitro Study

Deep Neural Network to Accurately Predict Left Ventricular Systolic Function Under Mechanical Assistance

Characterizing left ventricle (LV) systolic function in the presence of an LV assist device (LVAD) is extremely challenging. We developed a framework comprising a deep neural network (DNN) and a 0D model of the cardiovascular system to predict parameters of LV systolic function. DNN input data were systemic and pulmonary arterial pressure signals, and rotation speeds of the device. Output data were parameters of LV systolic function, including end-systolic maximal elastance (E_max,lv), a variable essential for adequate hemodynamic assessment of the LV. A 0D model of the cardiovascular system, including a wide range of LVAD settings and incorporating the whole spectrum of heart failure, was used to generate data for the training procedure of the DNN. The DNN predicted E_max,lv with a mean relative error of 10.1%, and all other parameters of LV function with a mean relative error of <13%. The framework was then able to retrieve a number of LV physiological variables (i.e., pressures, volumes, and ejection fraction) with a mean relative error of <5%. Our method provides an innovative tool to assess LV hemodynamics under device assistance, which could be helpful for a better understanding of LV-LVAD interactions, and for therapeutic optimization.

Red blood cells aggregability measurement of coagulating blood in extracorporeal circulation system with multiple-frequency electrical impedance spectroscopy

Red blood cells (RBCs) aggregability A_G of coagulating blood in extracorporeal circulation system has been investigated under the condition of pulsatile flow. Relaxation frequency f_c from the multiple-frequency electrical impedance spectroscopy is utilized to obtain RBCs aggregability A_G. Compared with other methods, the proposed multiple-frequency electrical impedance method is much easier to obtain non-invasive measurement with high speed and good penetrability performance in biology tissues. Experimental results show that, RBCs aggregability A_G in coagulating blood falls down with the thrombus formation while that in non-coagulation blood almost keeps the same value, which has a great agreement with the activated clotting time (ACT) fibrinogen concertation (F_bg) tests. Modified Hanai formula is proposed to quantitatively analyze the influence of RBCs aggregation on multiple-frequency electrical impedance measurement. The reduction of RBCs aggregability A_G is associated with blood coagulation reaction, which indicates the feasibility of the high speed, compact and cheap on-line thrombus measurement biosensors in extracorporeal circulation systems.