Study design and patients
Patients who needed cardiac surgery accompanied with mitral regurgitation were prospectively selected as the research objects, from June 2020 to Oct 2020. The mitral regurgitation spectrum, pulmonary arteriolar wedge pressure (PAWP) and invasive arterial systolic pressure of radial artery of 28 patients were collected simultaneously, 13 males and 15 females, including 3 patients with rheumatic heart disease, 15 patients with mitral valve prolapse and 10 patients with coronary artery bypass grafting, patients with moderate or above aortic stenosis were excluded, aged 47-78 years (62.55±7.28 years) and PAWP 7-29mmHg (15.3±4.9mmHg).
Floating catheter
With the assistance of intravenous anesthesia, endotracheal intubation and ventilator, the floating catheter was placed through the jugular vein and the arterial systolic pressure was measured by radial artery puncture. The position of the floating catheter was determined by transthoracic ultrasound. PAWP measured by floating catheter was used to replace LAPC. The a wave after the P wave of ECG is generated by the active contraction of left atrium, and the C wave is generated by the closure of mitral valve. The V wave after ECG T wave is generated by left ventricular relaxation and left atrial passive filling during mitral valve opening (the pressure generated by this wave cannot be used as left atrial pressure). Therefore, we take the pressure measured on the PAWP pressure curve at the end of ECG P wave as LAPC. The equipment used include: Fl-005 GE anesthesia monitor (GE Healthcare Finland), Edwards 131 F7 floating catheter (Irvine, USA), PTC-6F pressure monitoring catheter (Jingzhou Yihai Technology Co., Ltd.), etc.
Echocardiography
The patient was in supine position because of perioperative period. All ultrasound examinations were performed by the same echocardiographic doctors with a Philips ultrasound system (Philips iE33 ultrasound machine; Philips Healthcare, Andover Mass). The mitral regurgitation spectrum was collected under CW, and the angle between the sampling line and the mitral regurgitation beam should be less than 15°. Select different recording speeds of 100mm / s or 150mm / s according to the speed of heart rate to obtain a dull, smooth and complete spectrum.
Formulas of LAPEp
According to Weiss exponential equation and simplified Bernoulli equation, the left ventricular relaxation time constant (τ) can be obtained,τ=P/(-dP/dt), Where P is the pressure in the left ventricle, and t is the time from -dp/dtmax, as shown in Figure 1. Bring in the intervals between different speeds to obtain the following formula,τ=(t1-t2)/ln((LAP+16)/(LAP+4)) andτ=(t1-t3)/ln((LAP+36)/(LAP+4)). Theoretically, LAP can be calculated by measuring the intervals between any two speeds. In order to facilitate calculation and measurement of , we selected the time t1, t2 and t3 when the descending branch velocity of mitral regurgitation spectrum was 1m/s, 2m/s and 3m/s respectively.
Measurement methods of LAPEp
In order to accurately measure the intervals, t1-t2 and t1-t3, it is necessary to detect the spectrum edge firstly, so we propose an intelligent method based on deep learning to complete this task. The method consists of two parts, a basic network for coarse detection and a post-processing module for refining. We adopt BCD-Unet deep learning model, which was proposed at the ICCV conference in 2019 [13], for edge detection firstly, but there are dislocation and fracture in the detection results. So we design a post-processing module to deal with these problems. The post-processing module mainly uses the polynomial fitting method to refine the edges detected by BCD-Unet, making them clearer and smoother. The overall structure of the proposed method is shown as Figure 2.
We use the data collected by the hospital to train the model Iteratively. The trained deep learning model can automatically detect the edge of mitral regurgitation spectrum. Then we encapsulated the model and built the system based on it. The system takes the mitral regurgitation spectrum as input and outputs the edge curve and LAP(directly a number), which is shown as Figure 3. The software can only measure and calculate when the descending branch of the mitral regurgitation spectrum curve is complete, and the curve between at least 1m / s and 3m / S is good. When the peak value of the curve is less than 3m / s, it will not be calculated.
Statistical analysis
The statistical analysis and data visualization were conducted by SPSS 26.0 statistical software. Paired t-test was used to compare and analyze the measurement results of LAPBP and LAPEq with LAPC method. Meanwhile, correlation analysis was performed on the measurement results of LAPBP and LAPEq with LAPC method. The difference between LAPBP and LAPC was less than 10%, which was defined as the consistency between LAPBP and LAPC, otherwise it was inconsistent. 28 patients were divided into two groups, 17 in the consistent group and 11 in the inconsistent group. The causes of inaccurate LAPBP measurement were analyzed by single factor analysis.The significant level is 0.05.