Abstract
COVID-19 is a highly contagious disease that can cause severe pneumonia. Patients with pneumonia undergo chest X-rays (XR) to assess infiltrates that identify the infection. However, the radiographic characteristics of COVID-19 are similar to the other acute respiratory syndromes, hindering the imaging diagnosis. In this work, we proposed identifying quantitative/radiomic biomarkers for COVID-19 to support XR assessment of acute respiratory diseases. This retrospective study used different cohorts of 227 patients diagnosed with pneumonia; 49 of them had COVID-19. Automatically segmented images were characterized by 558 quantitative features, including gray-level histogram and matrices of co-occurrence, run-length, size zone, dependence, and neighboring gray-tone difference. Higher-order features were also calculated after applying square and wavelet transforms. Mann-Whitney U test assessed the diagnostic performance of the features, and the log-rank test assessed the prognostic value to predict Kaplan-Meier curves of overall and deterioration-free survival. Statistical analysis identified 51 independently validated radiomic features associated with COVID-19. Most of them were wavelet-transformed features; the highest performance was the small dependence matrix feature of “low gray-level emphasis” (area under the curve of 0.87, sensitivity of 0.85, [Formula: see text]). Six features presented short-term prognostic value to predict overall and deterioration-free survival. The features of histogram “mean absolute deviation” and size zone matrix “non-uniformity” yielded the highest differences on Kaplan-Meier curves with a hazard ratio of 3.20 ([Formula: see text]). The radiomic markers showed potential as quantitative measures correlated with the etiologic agent of acute infectious diseases and to stratify short-term risk of COVID-19 patients.
Keywords: COVID-19; Chest radiography; Coronavirus; Medical image analysis; Radiomics.
【저자키워드】 COVID-19, coronavirus, Radiomics, Chest radiography, Medical image analysis, 【초록키워드】 Biomarker, Infectious diseases, Pneumonia, Infection, diagnostic, respiratory diseases, Image analysis, Retrospective study, sensitivity, Cohort, survival, Characteristics, Features, Patient, chest X-ray, chest X-rays, contagious disease, severe pneumonia, respiratory, disease, Quantitative, patients, predict, COVID-19 patients, Chest radiography, marker, Analysis, statistical analysis, etiologic agent, acute respiratory diseases, Support, Prognostic value, dependence, hazard ratio, log-rank test, Kaplan-Meier curves, measure, acute infectious disease, Radiographic, Kaplan-Meier curve, zone, acute infectious diseases, Formula, Kaplan-Meier, Mann-Whitney, Mann-Whitney U test, contagious, uniformity, text, MOST, histogram, risk of COVID-19, feature, imaging diagnosis, highest, identify, diagnosed, characterized, calculated, undergo, correlated, co-occurrence, the log-rank test, with COVID-19, 【제목키워드】 novel,