Different Appearance of Chest CT Images of T2DM and NDM Patients with COVID-19 Pneumonia Based on an Artificial Intelligent Quantitative Method

Shan Lu,Jigang Wang,Baocheng Chang,Jun Shen,Jingxu Xu,Chencui Huang,Xianglu Meng,Wenlong Ding,Zhiheng Xing,Juhong Yang,Shiyu Zhao,Peng Fei Shan

doi:10.1155/2021/6616069

Abstract

COVID-19 is a kind of pneumonia with new coronavirus infection, and the risk of death in COVID-19 patients with diabetes is four times higher than that in healthy people. It is unclear whether there is a difference in chest CT images between type 2 diabetes mellitus (T2DM) and non-diabetes mellitus (NDM) COVID-19 patients. The aim of this study was to investigate the differences in chest CT images between T2DM and NDM patients with COVID-19 based on a quantitative method of artificial intelligence. A total of 62 patients with COVID-19 pneumonia were retrospectively enrolled and divided into group A (T2DM COVID-19 pneumonia group, n = 15) and group B (NDM COVID-19 pneumonia group, n = 47). The clinical and laboratory examination information of the two groups was collected. Quantitative features (volume of consolidation shadows and ground glass shadows, proportion of consolidation shadow (or ground glass shadow) to lobe volume, total volume, total proportion, and number) of chest spiral CT images were extracted using Dr. Wise @Pneumonia software. The results showed that among the 26 CT image features, the total volume and proportion of bilateral pulmonary consolidation shadow in group A were larger than those in group B (P=0.031 and 0.019, respectively); there was no significant difference in the total volume and proportion of bilateral pulmonary ground glass density shadow between the two groups (P > 0.05). In group A, the blood glucose level was correlated with the volume of consolidation shadow and the proportion of consolidation shadow to right middle lobe volume, and higher than those patients in group B. In conclusion, the inflammatory exudation in the lung of COVID-19 patients with diabetes is more serious than that of patients without diabetes based on the quantitative method of artificial intelligence. Moreover, the blood glucose level is positively correlated with pulmonary inflammatory exudation in COVID-19 patients.

Highlights

COVID-19 is a rapidly spreading disease that has reached the pandemic scale, affecting more than 100 countries worldwide
Whether there is a difference in chest CT images between type 2 diabetes mellitus (T2DM) and nondiabetes mellitus (NDM) COVID-19 patients is still unknown
An artificial intelligence quantitative method was used to evaluate the differences in chest CT images between T2DM and NDM patients with COVID-19 pneumonia

Summary

Introduction

COVID-19 is a rapidly spreading disease that has reached the pandemic scale, affecting more than 100 countries worldwide. The epidemic has swept over more than 200 countries and regions. On January 30, 2020, the WHO (World Health Organization) declared the epidemic a public health emergency of international concern. On March 11, 2020, the WHO characterized the epidemic as a pandemic disease. E mortality risk of International Journal of Endocrinology novel coronavirus pneumonia in DM patients is 4 times that of healthy people [4]. Whether there is a difference in chest CT images between type 2 diabetes mellitus (T2DM) and nondiabetes mellitus (NDM) COVID-19 patients is still unknown. An artificial intelligence quantitative method was used to evaluate the differences in chest CT images between T2DM and NDM patients with COVID-19 pneumonia

Methods

Results

Conclusion