Multiparameter Synchronous Measurement With IVUS Images for Intelligently Diagnosing Coronary Cardiac Disease

Abstract

Intravascular ultrasound (IVUS) can provide high-resolution cross-sectional images of coronary arteries, showing detailed information of the vascular lumen, tube wall, and athermanous plaques, which is helpful for the discovery or identification of early coronary atherosclerotic plaques. Multiple parameters extractable from the IVUS image can help the cardiologist analyze the pathology and assist in disease diagnosis and postoperative treatment. Typically, cardiologists manually label the intima and adventitia in the IVUS image, and obtain a limited number of parameters through the IVUS instrument, which is time consuming and labor-intensive. To assist the cardiologist in automatically obtaining more clinically relevant value parameters, a fully automatic IVUS multiparameter extraction framework is proposed. Based on the intima and adventitia obtained by DeepLab V3+, we propose a targeted noise reduction preprocessing framework adapted to IVUS. The framework implements the basic parameter extraction of IVUS through two newly proposed algorithms. And through the standard medical formula, the basic parameters are converted into 10 standard medical indicators. Standardized medical indicators are obtained by clinically relevant basic parameters. In terms of accuracy, this article used a clinical database obtained from Qilu Hospital of Shandong University and compared the results of the framework with the gold standard of cardiologists. The relative error of continuous IVUS main parameters between frames did not exceed 10.10%. The relative error of independent IVUS did not exceed 10.03%. Based on the distribution consistency of the parameters and the gold standard, a Bland-Altman plot of the parameters is proposed. It was verified that this distribution is basically in line with the gold standard of cardiologists. The algorithm in this article obtained a total of 10 parameters, far exceeding the parameters obtained by cardiologists and traditional IVUS machines. Its accuracy and speed can also meet the requirements of cardiologists for clinical diagnosis.